Systems and methods for concurrent measurements of plurality of protein reactions

Abstract

The present invention generally relates to a high-throughput system and method for concurrent measurements of a plurality of protein reactions. In embodiments, the high-throughput system is advantageously designed and configured to efficiently test the interactions between a set of proteins and chemical compounds. For example, by utilizing mass spectrometry and intelligent sample pooling strategies, the system generates a massive and diverse dataset of protein-compound interactions while minimizing resource usage. Advantageously, the system is capable of obtaining interaction data on a wide variety of different protein classes and is particularly suited for generating comprehensive bioactivity data for use in downstream applications such as machine learning model training for drug discovery and protein function prediction.

Description

SYSTEMS AND METHODS FOR CONCURRENT MEASUREMENTS OF PLURALITY OF PROTEIN REACTIONSCROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Patent Application No. 63 / 677,510, filed July 31, 2024 and titled “Systems and Methods for Concurrent Measurements of Plurality of Protein Reactions.”FIELD OF THE INVENTION

[0002] The present invention generally relates to systems and methods for concurrent measurements of a plurality of protein reactions.BACKGROUND

[0003] The field of bioactivity data generation and analysis has become increasingly important in various areas of biological research, drug discovery, and development of novel compounds. High-throughput screening (HTS) methods have traditionally been the primary source of such data, particularly in the pharmaceutical industry. However, current HTS approaches face several limitations that hinder the comprehensive exploration of biological interactions and the generation of balanced datasets.

[0004] Conventional HTS methods typically focus on screening a large number of compounds against a single protein target. This approach, while valuable for identifying potential drug candidates, results in an imbalanced dataset where information about many compounds is available for only a limited number of proteins. Such imbalance presents challenges in developing comprehensive understanding of protein-molecule interactions and limits the effectiveness of downstream applications, such as machine learning models for predicting bioactivity.

[0005] Furthermore, traditional HTS methods often require the development of specific assays for each protein target. This process is time-consuming, resource-intensive, and can be a bottleneck in the screening pipeline. The need for bespoke assay development not only slows down the screening process but also limits the diversity of proteins that can be efficiently studied.

[0006] Another limitation of current HTS approaches is the frequent use of labeled compounds or proteins. While labeling can provide valuable information, it introduces additional steps in the experimental workflow, potentially altering the natural behavior of the molecules under study. Moreover, not all compounds or proteins are compatible with labeling techniques, further restricting the chemical and biological space that can be explored.

[0007] Accordingly, additional systems and methods are needed.SUMMARY OF THE INVENTION

[0008] The present invention generally relates to systems and methods for concurrent measurements of a plurality of protein reactions. More particularly, the invention provides a high-throughput system for generating protein-molecule bioactivity data that addresses the limitations of current high-throughput screening (HTS) methods.

[0009] In some aspects, the techniques described herein relate to a system for concurrent measurement of a plurality of interacting molecules, the system including: a protein reservoir configured to store proteins, an interaction species reservoir configured to store interaction species, at least one processor configured to: select, from the protein reservoir, a plurality of proteins to be interacted, select, from the interaction species reservoir, at least one interaction species to be interacted, wherein the at least one interaction species and the plurality of proteins are determined according to at least one reaction pool of a pooling configuration, each reaction pool including at least two selected proteins from the plurality of proteins and at least one selected interaction species from the at least one interaction species; a reaction chamber configured for conducting individual reactions between the plurality of proteins and the at least one interaction species to generate a plurality of reaction output samples; and a molecular analysis module configured to measure the plurality of reaction output samples, wherein measuring includes concurrent measurement of at least two of the reaction output samples associated with a reaction pool selected according to the pooling configuration.

[0010] In some aspects, the techniques described herein relate to a system, wherein: the at least one interaction species includes a plurality of interaction species, the selected interaction species includes at least two interaction species, and the at least one reaction pool includes a plurality of reaction pools.

[0011] In some aspects, the techniques described herein relate to a system, wherein concurrent measurement includes measurement of all of the reaction output samples associated with the reaction pool selected according to the pooling configuration.

[0012] In some aspects, the techniques described herein relate to a system, further including a sample handling system configured to: receive control instructions from the at least one processor, and provide operative coupling between any combination of the protein reservoir, the interaction species reservoir, the reaction chamber, and the molecular analysis module, wherein operative coupling includes one or more of protein transfer, interaction species transfer, and reaction output sample transfer.

[0013] In some aspects, the techniques described herein relate to a system any, wherein the protein reservoir or the interaction species reservoir includes the reaction chamber.

[0014] In some aspects, the techniques described herein relate to a system, wherein: the reaction chamber includes a plurality a plurality of reaction vessels, each reaction vessel being configured for conducting one of the individual reactions to generate the plurality of reaction output samples; the sample handling system is configured to combine the plurality of reaction output samples into at least one combined reaction output sample according to the pooling configuration, and the molecular analysis module is configured to measure the reaction output samples in the at least one combined reaction output sample

[0015] In some aspects, the techniques described herein relate to a system wherein: the sample handling system is configured to combine proteins from the plurality of proteins with interaction species from the at least one interaction species in the reaction chamber according to the pooling configuration, the reaction chamber is configured for conducting a plurality of the individual reactions concurrently to generate a combined reaction output sample, and the molecular analysis module is configured to measure the combined reaction output sample.

[0016] In some aspects, the techniques described herein relate to a system, wherein the reaction chamber includes a plurality of individual reaction vessels, each individual reaction vessel being configured for concurrently conducting the plurality of the individual reactions according to the pooling configuration, and the molecular analysis module is configured to measure a plurality of combined reaction output samples.

[0017] In some aspects, the techniques described herein relate to a system, wherein the molecular analysis module is configured for sequential measurement of multiple combined reaction output samples, each associated with a different reaction pool.

[0018] In some aspects, the techniques described herein relate to a system, further including a reaction components reservoir configured to store a plurality of reaction components for adjusting reaction conditions.

[0019] In some aspects, the techniques described herein relate to a system, wherein the molecular analysis module is configured to directly measure at least one physicochemical property of reaction outputs associated with the plurality of reaction output samples.

[0020] In some aspects, the techniques described herein relate to a system, wherein the molecular analysis module includes a mass spectrometer employing one or more techniques selected from the group consisting of Matrix- Assisted Laser Desorption / Ionization Time-of- Flight (MALDI-TOF), Electrospray Ionization Mass Spectrometry (ESI-MS), Liquid Chromatography-Mass Spectrometry (LC-MS), Gas Chromatography-Mass Spectrometry (GC- MS), Inductively Coupled Plasma Mass Spectrometry (ICP-MS), Direct Injection Mass Spectrometry (DIMS), Ion Trap Mass Spectrometry and Secondary Ion Mass Spectrometry (SIMS).

[0021] In some aspects, the techniques described herein relate to a system, wherein the molecular analysis module includes at least one device selected from the group including: a spectrophotometer; a chromatography system; a Nuclear Magnetic Resonance (NMR) spectrometer; a fluorescence spectrometer; a Raman spectrometer; and a capillary electrophoresis system.

[0022] In some aspects, the techniques described herein relate to a system, wherein the pooling configuration includes pairings between each of the plurality of proteins with each of the at least one interaction species.

[0023] In some aspects, the techniques described herein relate to a system, wherein the reaction chamber is configured for reaction of label free proteins, label free interaction species, or both.

[0024] In some aspects, the techniques described herein relate to a system, wherein the at least one processor is further configured to obtain the pooling configuration, the pooling configuration being determined according to at least one criterion.

[0025] In some aspects, the techniques described herein relate to a system, wherein the at least one criterion includes a criterion that expected measurement results observable by the molecular analysis module of each reaction output sample associated with a reaction pool be differentiable.

[0026] In some aspects, the techniques described herein relate to a system, wherein the at least one criterion includes a criterion based on physicochemical properties of the plurality of proteins and the at least one interaction species selected for the pooling configuration.

[0027] In some aspects, the techniques described herein relate to a system, wherein the at least one criterion includes a criterion based on one or more of: molecular weights of expected reactant products associated with each reaction pool, spectral characteristics of expected reactant products associated with each reaction pool, chromatographic behavior of expected reactant products associated with each reaction pool, ionization properties of expected reactant products associated with each reaction pool, chemical stability of expected reactant products associated with each reaction pool, chemical reactivity of expected reactant products associated with each reaction pool, or hydrophilicity and / or hydrophobicity of expected reactant products associated with each reaction pool.

[0028] In some aspects, the techniques described herein relate to a system, wherein the at least one processor is further configured to demultiplex the concurrent measurement to differentiate measurement results associated with each reaction output sample within the reaction pool.

[0029] In some aspects, the techniques described herein relate to a system, wherein the at least one processor is further configured to: obtain, from the molecular analysis module, pool measurement data corresponding to measurements from a combined reaction output sample; demultiplex the pool measurement data to obtain individual measurements of outputs of the individual reactions, wherein the individual measurements include positive indications of reactions between proteins and interaction species and / or negative indications of reactions between proteins and interaction species; and store the individual measurements as demultiplexed pool measurement data in a protein reactions database.

[0030] In some aspects, the techniques described herein relate to a method for measuring a plurality of interacting molecules concurrently, the method to be performed by a system including: a protein reservoir configured to store proteins, an interaction species reservoir configured to store interaction species, a reaction chamber, a molecular analysis module, and at least one processor configured to execute the method, the method including: selecting, from theprotein reservoir, by the at least one processor, a plurality of proteins to be interacted; selecting from the interaction species reservoir, by the at least one processor, at least one interaction species to be interacted, wherein the at least one interaction species and the plurality of proteins are determined according to at least one reaction pool of a pooling configuration, each reaction pool including at least two selected proteins from the plurality of proteins and a selected interaction species from the at least one interaction species; conducting, in the reaction chamber, individual reactions between the plurality of proteins and the at least one interaction species to generate a plurality of reaction output samples; and measuring the plurality of reaction output samples, wherein measuring includes concurrent measurement, by the molecular analysis module, of at least two of the reaction output samples of a reaction pool selected according to the pooling configuration.

[0031] In some aspects, the techniques described herein relate to a method, wherein: the at least one interaction species includes a plurality of interaction species, the selected interaction species includes at least two interaction species, and the at least one reaction pool includes a plurality of reaction pools.

[0032] In some aspects, the techniques described herein relate to a method, wherein concurrent measurement includes measurement of all of the reaction output samples associated with the reaction pool selected according to the pooling configuration.

[0033] In some aspects, the techniques described herein relate to a method, further including providing, by the at least one processor to a sample handling system, control instructions to provide operative coupling between any combination of the protein reservoir, the interaction species reservoir, the reaction chamber, and the molecular analysis module, wherein operative coupling includes one or more of protein transfer, interaction species transfer, and reaction output sample transfer.

[0034] In some aspects, the techniques described herein relate to a method, wherein the protein reservoir or the interaction species reservoir includes the reaction chamber

[0035] In some aspects, the techniques described herein relate to a method, further including: conducting, in individual reaction vessels of the reaction chamber, one of the individual reactions to generate the plurality of reaction output samples; combining, by the sample handling system, the plurality of reaction output samples into at least one combined reaction output sampleaccording to the pooling configuration, and measuring, by the molecular analysis module, the reaction output samples in the at least one combined reaction output sample.

[0036] In some aspects, the techniques described herein relate to a method, further including: combining, by the sample handling system, the plurality of proteins with the at least one interaction species in the reaction chamber according to the pooling configuration; conducting, in the reaction chamber, a plurality of the individual reactions according to the pooling configuration to generate a combined reaction output sample; and measuring, by the molecular analysis module, the combined reaction output sample.

[0037] In some aspects, the techniques described herein relate to a method, wherein the reaction chamber includes a plurality of individual reaction vessels, each individual reaction vessel being configured for concurrently conducting the plurality of the individual reactions according to the pooling configuration, and the molecular analysis module is configured to measure a plurality of combined reaction output samples.

[0038] In some aspects, the techniques described herein relate to a method, further including sequentially measuring multiple combined reaction output samples, each associated with a different reaction pool.

[0039] In some aspects, the techniques described herein relate to a method, further including adjusting reaction conditions in the reaction chamber by use of reaction components stored in a reaction components reservoir.

[0040] In some aspects, the techniques described herein relate to a method, further including directly measuring at least one physicochemical property of reaction outputs associated with the plurality of reaction output samples.

[0041] In some aspects, the techniques described herein relate to a method, wherein the molecular analysis module includes a mass spectrometer employing one or more techniques selected from the group consisting of: Matrix- Assisted Laser Desorption / Ionization Time-of- Flight (MALD TOF), Electrospray Ionization Mass Spectrometry (ESLMS), Liquid Chromatography-Mass Spectrometry (LC-MS), Gas Chromatography-Mass Spectrometry (GC- MS), Inductively Coupled Plasma Mass Spectrometry (ICP-MS), Direct Injection Mass Spectrometry (DIMS), Ion Trap Mass Spectrometry and Secondary Ion Mass Spectrometry (SIMS).

[0042] In some aspects, the techniques described herein relate to a method, wherein the molecular analysis module includes at least one device selected from the group including: a spectrophotometer; a chromatography system; a Nuclear Magnetic Resonance (NMR) spectrometer; a fluorescence spectrometer; a Raman spectrometer; and a capillary electrophoresis system.

[0043] In some aspects, the techniques described herein relate to a method, wherein the pooling configuration includes pairings between each of the plurality of proteins with each of the at least one interaction species.

[0044] In some aspects, the techniques described herein relate to a method, wherein the plurality of proteins, the at least one interaction species, or both are label free.

[0045] In some aspects, the techniques described herein relate to a method, further including obtaining, by the processor, the pooling configuration, the pooling configuration being determined according to at least one criterion.

[0046] In some aspects, the techniques described herein relate to a method, wherein the at least one criterion includes a criterion that expected measurement results observable by the molecular analysis module of each reaction output sample associated with a reaction pool be differentiable.

[0047] In some aspects, the techniques described herein relate to a method, wherein the at least one criterion includes a criterion based on physicochemical properties of the plurality of proteins and the at least one interaction species selected for each reaction pool.

[0048] In some aspects, the techniques described herein relate to a method, wherein the at least one criterion includes a criterion based on one or more of: molecular weights of expected reactant products associated with each reaction pool, spectral characteristics of expected reactant products associated with each reaction pool, chromatographic behavior of expected reactant products associated with each reaction pool, ionization properties of expected reactant products associated with each reaction pool, chemical stability of expected reactant products associated with each reaction pool, chemical reactivity of expected reactant products associated with each reaction pool, or hydrophilicity and / or hydrophobicity of expected reactant products associated with each reaction pool.

[0049] In some aspects, the techniques described herein relate to a method, further including demultiplexing the concurrent measurement to differentiate measurement results associated with each reaction output sample within the combined reaction output samples.

[0050] In some aspects, the techniques described herein relate to a method, further including: obtaining, from the molecular analysis module, pool measurement data corresponding to measurements from a combined reaction output sample, demultiplexing the pool measurement data to obtain individual measurements of outputs of the individual reactions, wherein the individual measurements include positive indications of reactions between proteins and interaction species and / or negative indications of reactions between proteins and interaction species, and. storing the individual measurements as demultiplexed pool measurement data in a protein reactions database.

[0051] In some aspects, the techniques described herein relate to a method for measuring a plurality of interacting modules concurrently, the method to be performed by a system including: a protein reservoir, an interaction species reservoir, a reaction chamber, a molecular analysis module, and at least one processor configured to execute the method, the method including: selecting, by the at least one processor from the protein reservoir, a plurality of proteins to be interacted; selecting, by the at least one processor from the interaction species reservoir, at least one interaction species to be interacted, generating, by the at least one processor, a pooling configuration including one or more reaction pools, each reaction pool including at least two selected proteins from the plurality of proteins and a selected interaction species from the at least one interaction species; and for each of the plurality of pools: individually reacting, within the reaction chamber, the at least two selected proteins with the selected interaction species to generate a plurality of reaction output samples; and measuring the plurality of reaction output samples, wherein measuring includes concurrent measurement, by the molecular analysis module, of at least two reaction output samples in the plurality of reaction output samples.BRIEF DESCRIPTION OF THE DRAWINGS

[0052] FIG. 1 illustrates a flowchart of a method for concurrent measurements of a plurality of protein reactions, according to embodiments described herein.

[0053] FIG. 2 illustrates a schematic diagram of a system for concurrent measurements of a plurality of protein reactions, according to embodiments described herein.

[0054] FIG. 3 illustrates a flowchart of a method for concurrent measurements of a plurality of protein reactions, according to embodiments described herein.

[0055] FIG. 4 illustrates a pooling configuration according to embodiments described herein.

[0056] Other aspects, embodiments and features of the invention will become apparent from the following detailed description when considered in conjunction with the accompanying drawings. The accompanying figures are schematic and are not intended to be drawn to scale. For purposes of clarity, not every component is labeled in every figure, nor is every component of each embodiment of the invention shown where illustration is not necessary to allow those of ordinary skill in the art to understand the invention. All patent applications and patents incorporated herein by reference are incorporated by reference in their entirety. In case of conflict, the present specification, including definitions, will control.DETAILED DESCRIPTION

[0057] The present invention generally relates to a high-throughput system and method for concurrent measurements of a plurality of protein reactions. In embodiments, the high- throughput system is advantageously designed and configured to efficiently test the interactions between a set of proteins and chemical compounds. For example, by utilizing mass spectrometry and intelligent sample pooling strategies, the system generates a massive and diverse dataset of protein-compound interactions while minimizing resource usage. Advantageously, the system is capable of obtaining interaction data on a wide variety of different protein classes and is particularly suited for generating comprehensive bioactivity data for use in downstream applications such as machine learning model training for drug discovery and protein function prediction.

[0058] In traditional screening techniques, attempts have been previously made to screen multiple proteins concurrently. For example, some methods involve binding proteins to a carrier and adding ligands, with the assumption that at least one protein in the mixture would bind to at least one ligand. However, these approaches are limited in their ability to provide quantitative bioactivity data and often require additional preparation steps, such as binding proteins to a resin.

[0059] The inventors of the instant invention recognized that the generation of comprehensive bioactivity data is crucial for advancing our understanding of biological systems and for developing more effective computational models. Machine learning approaches, in particular, benefit from large, diverse, and balanced datasets. However, the current imbalance in available data - with an abundance of information on compounds but limited data on proteins - generally hinders the development of robust and generalizable models.

[0060] Therefore, the inventors of the instant invention recognized a pressing need for a system and method that can efficiently generate bioactivity data for a plurality of proteins concurrently. In embodiments, the system described herein are advantageously capable of handling diverse proteins and compounds, capable of quantitative data on bioactivity rather than just binding information, and / or minimize the need for protein-specific assay development or labeling techniques.

[0061] Advantageously, the system leverages advanced analytical techniques, such as mass spectrometry, spectrophotometry, nuclear magnetic resonance (NMR) spectroscopy, fluorescence spectroscopy, Raman spectroscopy, or other label-free detection methods, which can analyze compounds based on their physicochemical properties without the need for specific assay development. While some of these methods, for example, mass spectrometry, have been used in certain contexts for ligand discovery, their full potential for high-throughput, multiprotein screening has not been realized.

[0062] Additionally, the inventors of the instant invention recognized a need for a system that can handle not just binding interactions, but also more complex scenarios involving multiple substrates, products, cofactors, and potential modulators of protein activity. Such a system would provide a more comprehensive view of biological interactions, including inhibition, activation, protein-protein interactions such as complex formation, proteolytic cleavage, covalent bond formation, agonism, and other forms of modulation.

[0063] Finally, to maximize efficiency and minimize resource use, the system may, in embodiments, advantageously incorporate strategic sample pooling and advanced data processing techniques. Such features generally advantageously permit the concurrent analysis of multiple protein-compound interactions while maintaining the ability to demultiplex and accurately interpret the results. In particular, in many screening techniques, a resource bottleneck exists in the measurement or analysis of samples. Although many samples may be reacted concurrently, e.g., through the use of multiple 96, 384, or 1536 well plates, the available throughput for analysis and measurement systems may be considerably lower. In an example, a 384 well plate may be used to concurrently generate samples. Preparation, reaction, incubation and other steps to generate measurable reaction samples may be completed in a few hours or less. Measurement of all 384 generated samples, however, may take many hours or several days. If multiple 384 well plates are used for concurrent generation, this bottleneck becomes evengreater. Accordingly, the strategic sample pooling and data processing techniques described herein, which permit the measurement and analysis of many samples concurrently, e.g., through strategic combination of samples, may significantly improve overall throughput times.

[0064] The systems and methods described herein may be useful for dramatically accelerating biological research, drug discovery, and / or the development of predictive models in the life sciences. In embodiments, the bioactivity data generated by the system and method of the present invention has numerous applications beyond the scope of this patent application, particularly in training machine learning models for drug discovery and protein function prediction. For example, by providing a more balanced and comprehensive dataset, the systems and methods described herein have the potential to accelerate drug discovery processes, enhance our understanding of protein-molecule interactions, and improve the accuracy and reliability of computational models in biology and pharmacology. A more balanced dataset may include both positive and null results, which may be especially beneficial in training machine learning models.

[0065] In embodiments, the invention provides a system for producing protein-molecule bioactivity data in high throughput, wherein the system efficiently generates bioactivity data of a plurality of proteins simultaneously. In embodiments, the system comprises one or more of: a protein reservoir containing at least one or more proteins, an interaction species reservoir containing at least one interaction species, an optional additional reservoir for at least one reaction component, a multiplexer comprised of a processor, a database, and a liquid transfer apparatus, a reaction chamber, a molecular analysis module, and a demultiplexer comprised of a processor and database.

[0066] In embodiments, the molecular analysis module comprises a mass spectrometer. The mass spectrometer may be selected from a group consisting of, but not limited to, MALDI-TOF, Q-TOF ESI-MS, LC-MS, GC-MS, ICP-MS, Native MS, DIMS, Ion Trap Mass Spectrometry, SIMS and / or combinations thereof. Other examples of the molecular analysis module are discussed throughout this disclosure.

[0067] In embodiments, the molecular analysis module comprises a spectrophotometer. In embodiments, the spectrophotometer measures wavelengths of light in any number of the spectra consisting of, but limited to, the UV-visible, far UV, infrared, X-ray, near-infrared (NIR), mid-infrared, microwaves, and gamma ray spectra. In an example set of embodiments, the molecular analysis module comprises a Nuclear Magnetic Resonance (NMR) spectrometer.

[0068] In embodiments, the molecular analysis module incorporates a chromatography system. For example, the module may comprise a system for gas chromatography (GC) for separating and analyzing volatile compounds. In embodiments, the GC system may be coupled with a Flame Ionization Detector (FID), electrochemical gas sensors, and / or spectroscopic systems to quantify the reaction components or products. In embodiments, the molecular analysis module utilizes Raman spectroscopy. In embodiments, the molecular analysis module is comprised of one or more electrochemical gas sensors.

[0069] In embodiments, a method comprises concurrent measurements of a plurality of protein reactions, for example, the outputs of such reactions. In embodiments, the method comprises the one or more of the following steps: providing a plurality of proteins, providing at least one interaction species, optionally providing at least one reaction component, using a multiplexer to combine said proteins, interaction species, and optional reaction components in a reaction chamber to create at least two distinct reactions, wherein each reaction comprises at least one protein from the plurality of proteins, allowing the at least two distinct reactions to occur, using the multiplexer to combine outputs from the at least two distinct reactions, analyzing the combined reaction outputs using a molecular analysis module, processing the analysis results using a demultiplexer, and providing the results and saving them in a database.

[0070] In embodiments, the method comprises the step of optimizing the combination of reaction outputs to maximize the number of distinct protein reactions that can be analyzed simultaneously while maintaining the ability to deconvolute individual reaction results. In embodiments, the multiplexer utilizes a dynamic pooling strategy, wherein the combination of reaction outputs is determined based on predicted compatibility of reaction products and the resolution capabilities of the molecular analysis module.

[0071] In embodiments, the method comprises a pre-analysis step wherein a small portion of each reaction output is individually analyzed to inform the optimal pooling strategy for the main analysis.

[0072] In embodiments, the molecular analysis module comprises a mass spectrometer, as described in more detail, herein. In embodiments, the method further comprises the step ofoptimizing mass spectrometry parameters to maximize the resolution between different reaction products in the combined output.

[0073] In embodiments, the molecular analysis module comprises a spectrophotometer. In embodiments, the method comprises the step of optimizing spectrophotometery parameters to maximize the resolution between different reaction products in the combined output.

[0074] In embodiments, the method comprises a machine learning component that continuously improves the pooling strategy based on historical data from previous runs, thereby increasing the efficiency and accuracy of the concurrent measurements over time.

[0075] In embodiments, the method comprises a quality control step after the analysis, wherein the results are compared against known standards and controls to ensure an accuracy of the concurrent measurements.

[0076] In embodiments, the method further comprises the step of selecting interaction species to minimize interference with the molecular analysis module. As used herein, “interference” generally refers to any phenomenon that hinders accurate detection, identification, or quantification of a molecular species in a pooled sample. Non-limiting examples of interferences include: (i) overlapping signals — e g., co-eluting chromatographic peaks, coincident absorption wavelengths, or isobaric mass-to-charge ratios; (ii) matrix effects that modify detector response via competitive ionization, signal suppression, or enhancement; (iii) chemical interactions among pooled species that generate complexes, degradation products, or other transformations during analysis; and (iv) instrumental limits such as inadequate dynamic range or resolution. Without wishing to be bound by theory, interference, in some cases, yields ambiguous or erroneous results and obstructs deconvolution of individual species. In embodiments, the method entails selecting species whose physicochemical properties produce mutually resolvable signatures under the chosen analytical conditions, to the degree necessary for statistically confident, quantitative measurements. This selection process may advantageously, in embodiments, consider factors such as molecular weight differences, spectral characteristics, chromatographic behavior, ionization properties, and / or chemical stability. Minimizing interference may include reducing or eliminating interference to a degree that permits many, most, or all observable results in a sample to be differentiated or distinguished. Differentiation between two signals may be defined to mean that two signals can be separately read with a confidence of at least 80%, at least 90%, at least 95%, at least 98%, and / or at least 99%. Differentiation of many, most, or allsignals within a sample or a reaction pool may be defined to mean that more than 80%, more than 90%, more than 95%, more than 98%, more than 99%, and / or 100% of all expected observable signals within the sample or reaction pool may be differentiated from other expected observable signals.

[0077] In embodiments, the method comprises the step of selecting an interaction species to increase or maximize the probability of interaction as determined by similarity to existing interaction species. In embodiments, the method further comprises a step of selecting the interaction species determined to be similar to another interaction species known to interact with at least one protein of the reaction. In embodiments, the reactions involving the interaction species within each pool are performed in discrete reaction chambers (or individual reaction vessels within a reaction chamber), with each interaction species reacted separately prior to pooling. In embodiments, reactions involving multiple interaction species within a single pool are performed concurrently within a common reaction vessel as a pooled reaction. In embodiments, pooled reactions may be executed in subsets or groups (blocks), wherein defined subsets of interaction species undergo reactions concurrently, but separate from other subsets within the same pool. Advantageously, in embodiments, such pooled reactions may be carried out simultaneously for all members of the pool, or may occur sequentially, with reactions for different interaction species within the same pool performed at distinct time points.

[0078] In embodiments, distinct reactions can occur concurrently or at different times. In embodiments, distinct reactions may have two or more two reaction conditions (e g., three or more, four or more, five or more, or six or more reaction conditions). Non-limiting examples of reaction conditions include the presence or absence of substrates, reagents, cofactors, or reaction products; physicochemical properties of the reaction environment such as temperature, pH, ionic strength, pressure; and the application or removal of external energy sources including irradiation with specific wavelengths of light (photochemical control), electrical fields (electrochemical control), and / or magnetic fields (magnetically induced control).

[0079] In embodiments, the interaction species are allocated according to a combinatorial pooling scheme, e.g., a pooling configuration as discussed in greater detail below, that systematically distributes one or more, or two or more interaction species among a plurality of reaction pools. In embodiments, pursuant to a predetermined combinatorial matrix, each interaction species is intentionally present in more than one distinct pool, thereby advantageouslyexpanding the set of unique interactions interrogated and increasing analytical throughput and diversity. In embodiments, the combinatorial pooling comprises matrix pooling (e.g., grid-based pooling), where interaction species are arranged into a conceptual grid with each species assigned to one row pool and one column pool. This creates overlapping pool compositions where each interaction species appears in exactly two distinct pools, enabling identification of active interaction species by analyzing the pattern of positive results across the different pooled samples.

[0080] In embodiments, the combinatorial pooling scheme may: (i) employ hierarchical (nested) pooling, sequentially subdividing interaction species into progressively finer sub-pools; (ii) use orthogonal arrays, assigning each species to a distinct set of pools that furnishes a unique combinatorial address; and / or (iii) implement probabilistic pooling, randomly distributing species among pools and resolving positive pools with decoding algorithms such as compressed sensing or group-testing.

[0081] In embodiments, combinatorial pooling incorporates balanced incomplete block design, where interaction species are systematically assigned to pools such that each species appears in a fixed number of pools, and each pair of species appears together in exactly one (or a predefined number of) pool(s).

[0082] In embodiments, the processor selects interaction species using structural relationships or scaffolds.

[0083] The systems and methods described herein may be useful for overcoming several limitations of conventional HTS methods. Unlike conventional HTS approaches that typically screen a plurality of compounds against one specific target, the present invention generally enables the simultaneous screening of multiple proteins against one or more interaction species. Advantageously, this approach generates a more balanced dataset with comprehensive information about both proteins and interaction species.

[0084] In embodiments, the present invention utilizes a molecular analysis module such as a mass spectrometer or spectrophotometer (e.g., which is capable of measuring a plurality of reaction components and / or interaction species), which does not require protein-specific assays for analyzing reaction outcomes, does not require that reaction components be labeled, and is capable of direct measurement of physicochemical properties. Advantageously, such a modulemay significantly reduce the time and resources required for assay development and enables the study of a wider range of proteins and interaction species.

[0085] Another example advantage of the present invention is its label-free nature. Unlike existing methods that require labeling of either proteins or interacting molecules, the systems and methods disclosed herein do not generally require any labeling steps (although labeling steps may be used, in embodiments, e.g., in conjugation with one or more additional assays). This label-free approach offers one or more advantages: it eliminates additional work steps, thereby increasing the efficiency of the process; it reduces the risk of altering the natural behavior of the molecules under study, which can occur with labeling; and / or it expands the range of proteins and compounds that can be studied, as some molecules are not compatible with labeling methods. For example, and without wishing to be bound by theory by enabling the direct analysis or measurement of native, unmodified proteins and molecules, the present invention provides a more accurate representation of biological interactions and broadens the chemical and biological space that can be explored.

[0086] The term “label-free” as used herein may refer to a molecule, such as a protein, compound, small molecule, substrate, ligand, nucleic acid, or other chemical entity, that does not include a bound chemical label, whether covalently or non-covalently attached. Examples of such chemical labels include, but are not limited to, biotin, nucleic acids (e.g., DNA), fluorescent dyes (e.g., FITC, rhodamine), radioactive isotopes, stable isotopes, reporter enzymes, mass tags, and enzyme conjugates. Label-free molecules may be analyzed in their native unmodified form and used in molecular analysis systems that rely on detection of intrinsic physicochemical properties.

[0087] In the context of this invention, the term "protein" refers to a large biomolecule or complex of biomolecules composed of one or more chains of amino acids, such as but not limited to natural, unnatural or modified amino acids, connected by at least one peptide bond. Proteins play crucial roles in biological processes and can have various functions within organisms. The term "protein" as used herein encompasses, but is not limited to, oligomers, peptides, enzymes, transcription factors, channels, transporters, antiporters, receptors, structural proteins, hormones, antibodies including but not limited to protein fragments, fusion or engineered proteins derived from or mimicking antibodies, including but not limited to singlechain variable fragments, Fab fragments, single domain antibodies (nanobodies), affibodies,affimers, alphabodies, avimers, anticalins, monobodies, DARPins, and affilins; other binding proteins including but not limited to variable lymphocyte receptors and de novo designed binding proteins;, chaperones, storage proteins, contractile proteins, motor proteins, stress proteins, antigen or other presenting proteins, carrier proteins, fluorescent proteins, proteins that bind nucleic acids, proteins that bind to or otherwise modulate the effect of other proteins, electrically conductive proteins such as bacterial nanowires, electron carrying proteins, light harvesting proteins, viral proteins such as tail or capsid proteins, ribosomal proteins, and proteins that bind to ions or molecules designed for purposes such as but not limited to sequestration, storage, accumulation, display, and stabilization or other chemical or quantum alteration to enable the bound molecule to be able to be transformed or otherwise perform in a reaction.

[0088] Those of ordinary skill in the art would understand, based upon the teachings of this specification that proteins may include other types of proteins not explicitly mentioned here. Furthermore, the terms "protein," "target," and "protein target" may be used interchangeably in this patent application to refer to the biological molecules (e.g., analytes) that are the subject of investigation or manipulation by the disclosed system and method.

[0089] In embodiments, the analyte (e g., a protein) comprises a binding moiety comprising biological or a chemical group capable of binding another biological or chemical molecule in a medium (e.g., aqueous phase). For example, the binding moiety may include a functional group, such as a thiol, aldehyde, ester, carboxylic acid, hydroxyl, and the like, wherein the functional group forms a bond with the analyte. In some cases, the binding moiety may be an electron-rich or electron-poor moiety wherein interaction between the analyte and the binding moiety comprises an electrostatic interaction. In some cases, the interaction between the analyte and the binding moiety includes binding to a metal or metal-containing moiety.

[0090] In embodiments, the binding moiety and an analyte interact via a binding event between pairs of biological molecules including proteins, nucleic acids, glycoproteins, carbohydrates, hormones, drugs, and the like. Specific examples include an antibody / peptide pair, an antib ody / antigen pair, an antibody fragment / antigen pair, an antibody / antigen fragment pair, an antibody fragment / antigen fragment pair, an antibody / hapten pair, an enzyme / substrate pair, an enzyme / inhibitor pair, an enzyme / cofactor pair, a protein / substrate pair, a nucleic acid / nucleic acid pair, a protein / nucleic acid pair, a peptide / peptide pair, a protein / protein pair, a small molecule / protein pair, a glutathione / GST pair, an anti-GFP / GFP fusion protein pair, a Myc / Maxpair, a maltose / maltose binding protein pair, a carbohydrate / protein pair, a carbohydrate derivative / protein pair, a metal binding tag / metal / chelate, a peptide tag / metal ion-metal chelate pair, a peptide / NTA pair, a lectin / carbohydrate pair, a receptor / hormone pair, a receptor / effector pair, a complementary nucleic acid / nucleic acid pair, a ligand / cell surface receptor pair, a virus / ligand pair, a Protein A / antibody pair, a Protein G / antibody pair, a Protein L / antibody pair, an Fc receptor / antibody pair, a biotin / avidin pair, a biotin / streptavidin pair, a drug / target pair, a zinc finger / nucleic acid pair, a small molecule / peptide pair, a small molecule / protein pair, a small molecule / target pair, a carbohydrate / protein pair such as maltose / MBP (maltose binding protein), a small molecule / target pair, or a metal ion / chelating agent pair. Specific non-limiting examples of binding moieties include peptides, proteins, DNA, RNA, PNA. Other binding moieties and binding pairs are also possible. Binding moieties can also be attached to polymers, organic nanoparticles, inorganic nanoparticles, or metal nanoparticles.

[0091] In embodiments, the binding moiety and the analyte interact via a binding event between pairs of biological molecules including proteins, nucleic acids, glycoproteins, carbohydrates, hormones, and the like. In an example embodiment, the analyte is a protein comprising a binding moiety. In embodiments, two or more binding moieties may be present.

[0092] In embodiments, the protein may be a naturally occurring protein. In embodiments, the protein may be a synthetic or engineered protein. In embodiments, the protein may be a fragment or domain of a larger protein. In embodiments, the protein may be a fusion protein comprising elements from two or more different proteins.

[0093] The proteins used in the present invention may be derived from various sources, including but not limited to, human proteins, animal proteins, plant proteins, microbial proteins such as bacterial proteins, fungal proteins, algal proteins, protist proteins protein or archaeal proteins, viral proteins, genomic, metagenomic, transcriptomic, or proteomic data, in silico designed, evolved or selected proteins, non-ribsomally synthesized proteins, chemically synthesized proteins. Other derivation sources are also possible.

[0094] In embodiments, the proteins may be wild-type proteins. In embodiments, the proteins are mutant or variant proteins. In embodiments, the proteins are post-translationally modified proteins. In embodiments, the proteins comprise one or more unnatural amino acids or amino acid analogs.

[0095] In embodiments the proteins are derived from and / or are present in (e.g., are naturally found and / or interact with) the cytoplasm of a cell. In embodiments proteins are derived from and / or are present (e.g., are naturally found and / or interact with) on the surface of a cell or viral particle. In embodiments proteins are displayed or bound to a natural or synthetic particle (e.g., a nanoparticle), or the surface of a substrate (e.g., a container). In embodiments, the proteins may be in a solution (e.g., an aqueous solution). In embodiments, the proteins may be present in a droplet, micelle, capsule, or the like.

[0096] As used herein, the term “Interaction Species” generally refers to any molecules, atoms, ions, or chemical entities that bind to, influence, or participate in biochemical reactions involving a target protein or enzyme. This includes, but is not limited to, substrates, products, inhibitors, activators, cofactors, coenzymes, and other binding species that form specific, detectable or observable complexes with the target under experimental conditions. As used herein, the term “Binding Species” generally refers to any molecule or chemical entity that forms a specific interaction with a protein or enzyme, typically, but not limited to, through the formation of a bond, such as an ionic bond, a covalent bond, a hydrogen bond, Van der Waals (e.g., electrostatic) interactions, and the like. The covalent bond may be, for example, carbon-carbon, carbon-oxygen, oxygen-silicon, sulfur- sulfur, phosphorus-nitrogen, carbon-nitrogen, metal- oxygen, or other covalent bonds. The hydrogen bond may be, for example, between hydroxyl, amine, carboxyl, thiol, and / or similar functional groups. The bond may also be, for example, between sulfonic acid and a positively charged functional group or phosphonic acid and a positively charged functional group (e.g., present on the surface of the location internal to the subject). Other bonds are also possible. Binding Species include, but not limited to, substrates, inhibitors, activators, cofactors, and ions that interact directly with the active site or allosteric sites of the protein or enzyme.

[0097] As used herein, the term “Reaction Components” generally refers to any substances that are required to facilitate or support the biochemical reaction, such as a substrate, product, inhibitors, activators, cofactors, and coenzymes. Reaction Components include, but are not limited to, solvents (e.g., water), buffers, acids, bases, salts, cofactors, coenzymes, coating proteins, electron transfer chemicals and proteins, and / or other auxiliary chemicals that maintain the appropriate reaction conditions.

[0098] Fig. 2 illustrates a schematic diagram of the system (200) for concurrent measurements of a plurality of protein reactions, according to one set of embodiments. The system comprises a protein reservoir (205) for storing one or more proteins; an interaction species reservoir (210) for storing one or more interaction species; a reaction components reservoir (215) for storing one or more reaction components; a multiplexer (220) including a processor (222), a database (224), and a sample handling system (226); a reaction chamber (230) where the proteins, interaction species, and reaction components are combined and allowed to react; a molecular analysis module (240); and a demultiplexer (250) including a processor (252) and a database (254). In embodiments, the functionality of the processor (222) and the processor (252), as described below, may be implemented by one or more processors in common, may be implemented by cloud computing solutions, or may be implemented by any suitable processor arrangement that is not limited to the two processors described below.

[0099] Referring to Fig. 2, in embodiments, the system (200) for concurrent measurements of a plurality of protein reactions comprises several interconnected components designed to work in concert to achieve high-throughput, label-free analysis of protein-interaction species interactions. In embodiments, system (200) comprises a protein reservoir (205), an interaction species reservoir (210), a reaction components reservoir (215), a multiplexer (220), a reaction chamber (230), a molecular analysis module (240), and a demultiplexer (250). In embodiments, one or more of protein reservoir (205), interaction species reservoir (210), reaction components reservoir (215), multiplexer (220), reaction chamber (230), molecular analysis module (240), and demultiplexer (250) are in fluidic communication with another component of the system. For example, protein reservoir (205), interaction species reservoir (210), and reaction components reservoir (215) may be in fluidic communication with one another. In embodiments, the components collectively and advantageously enable the system to efficiently combine proteins, interaction species, and reaction components, facilitate reactions, and analyze the resulting products in a high-throughput manner.

[0100] In embodiments, protein reservoir (205) is a component of the system (200), designed to store and maintain a diverse array of proteins for use in the high-throughput screening process. In embodiments, protein reservoir (205) may take different forms and incorporate various features to ensure the integrity and availability of the stored proteins. In embodiments, protein reservoir (205) is a temperature-controlled storage unit capable of maintaining proteins at temperaturesranging from -80°C to room temperature (typically around 20-25°C), depending on the specific requirements of the stored proteins. The ability to store proteins at room temperature can be particularly advantageous for proteins that are stable under these conditions, as it can simplify handling and reduce energy costs associated with refrigeration or freezing.

[0101] In embodiments, the reservoir may be equipped with multiple compartments, each capable of maintaining a different temperature, to accommodate proteins with varying storage requirements. In embodiments, the reservoir may be configured to each protein is stored separately from other proteins. In embodiments, this multi-temperature capability allows for optimal storage conditions for a wide range of proteins, from those requiring deep freezing to those stable at room temperature. In embodiments, the reservoir is configured to allow different conditions to accommodate protein storage requirements such as but not limited to light, buffer type, buffer conditions, concentration.

[0102] In embodiments, protein reservoir (205) comprises a liquid handling system that enables automated retrieval and dispensing of proteins. In embodiments, the system may comprise robotic arms, pipettes, pins, acoustic transfer devices or microfluidic channels, droplets or capsules that can accurately measure and transfer small volumes of protein solutions.

[0103] In embodiments, protein reservoir (205) is designed as a microfluidic chip with multiple wells or channels, each containing a different protein or protein mixture. Advantageously, this design may allow for miniaturization of the system and reduce the volume of protein required for each reaction.

[0104] In embodiments, the system (e.g., comprising protein reservoir (205)) may be associated with a database system that maintains detailed information about each stored protein, including its sequence, structure, known functions, optimal reaction conditions, known substrates, cofactors, and / or coenzymes, and any relevant metadata. In embodiments, the database can be integrated with the multiplexer (220) to inform the selection of proteins for each reaction set.

[0105] In embodiments, protein reservoir (205) may include an on-demand protein synthesis module. In embodiments, the on-demand protein synthesis module utilizes cell-free protein synthesis systems to produce proteins as needed, reducing the need for long-term storage and ensuring a supply of fresh, active proteins for each experiment.

[0106] In embodiments, e.g., to maintain protein stability and activity, the protein reservoir (205) may be equipped with a system for controlling the chemical environment of the stored proteins.Non-limiting examples of such control systems include mechanisms for maintaining specific pH levels, ionic strengths, and the presence of stabilizing agents such as glycerol or specific cofactors.

[0107] In embodiments, protein reservoir (205) incorporates a quality control system that periodically tests the activity and integrity of stored proteins. In embodiments, the quality control system uses small-scale assays or spectroscopic methods to ensure that the proteins remain active and properly folded over time.

[0108] In embodiments, protein reservoir (205) is designed to be compatible with a wide range of protein types, including but not limited to enzymes, receptors, structural proteins, and engineered proteins. Advantageously, protein reservoir (205) may accommodate, in embodiments, proteins derived from various sources, including human, animal, plant, microbial, and viral origins.

[0109] In embodiments, protein reservoir (205) includes a tagging system that allows for easy tracking and identification of proteins throughout the experimental process. For example such a tagging system comprises, in embodiments, the use of barcodes, RFID tags, or other identification methods that can be read by the multiplexer (220) and other system components.

[0110] Advantageously, the capacity of the protein reservoir (205) may be scaled to meet the needs of different experimental setups. For example, in large-scale implementations, the protein reservoir may be capable of storing thousands of unique proteins, while smaller-scale versions might accommodate dozens or hundreds of proteins. By providing a versatile, controlled, and automated storage solution for a diverse array of proteins, the protein reservoir (205) advantageously enables, in embodiments, the high-throughput, concurrent analysis of multiple protein reactions.[0U1] Protein reservoir (205) may be designed and adapted to contain a diverse array of proteins, encompassing a wide range of biological functions and structures. In embodiments, proteins inserted into and / or contained within protein reservoir (205) may be obtained from a variety of sources, reflecting the system's flexibility and broad applicability. One example source includes protein production systems, which may include cell-based expression systems using bacterial, yeast, insect, or mammalian cells. Such systems may be optimized for high-yield production of specific proteins or classes of proteins. Another example source includes cell-free protein synthesis systems, which offer rapid, on-demand production of proteins without the needfor cell culture. Such systems can be particularly useful for producing proteins that are difficult to express in cellular systems or for generating proteins with non-natural amino acids.

[0112] In embodiments, the protein reservoir contains proteins extracted from natural sources, such as tissue samples or microbial cultures, which can be e.g., particularly valuable for studying proteins in their native state or for exploring proteins from unculturable organisms. Commercial sources represent another possible protein supply, with many purified proteins and enzymes available for purchase from biochemical supply companies. Such pre-purified proteins can be directly added to the reservoir, advantageously saving time and resources in protein production. In embodiments, the system may incorporate proteins from cell lysates, which can e.g., provide a complex mixture of proteins representative of a particular cell type or organism. Such an approach can be especially useful for studying protein interactions in a more physiologically relevant context. In embodiments, the protein reservoir is designed to be compatible with one or more of these protein sources, allowing to populate it with proteins best suited to the investigation goals, whether focused on a particular protein class, organism, or biological process. Flexibility in protein sourcing supports the system's goal of maximizing the ability to obtain interaction data on a wide variety of different enzyme classes while minimizing resource usage.

[0113] In embodiments, the protein reservoir (205) may be implemented as a microplate storage system. In embodiments, the system comprises a plurality of microplates, wherein each microplate contains a plurality of wells. Each well may be configured to contain a distinct protein. The microplate storage system may further comprise an automated access mechanism for retrieving and dispensing proteins from said wells. In embodiments, the system comprises a multi -well plate (e.g., a multi -well cell culture plate) such as a 6-well, 12-well, 24-well, 48-well, 96-well, 384-well, or 1536 well plate. In embodiments, the system comprises an ANSI multiwell (e.g., microtiter) plate. For example, in some cases, the system may comprise a 96-well, 384-well, or 1536-well plate designed according the ANSI SLAS 4-2004 (R2012) standard. In embodiments, the system comprises a plurality of conical tubes (e.g., greater than or equal to 2 and less than or equal to 1536 conical tubes). In embodiments, the system comprises a plurality of dishes such as petri dishes (e.g., greater than or equal to 2 and less than or equal to 1536 petri dishes).

[0114] In embodiments, part or all of the protein reservoir (205) may function as the reaction chamber (230). For example, if the protein reservoir (205) is implemented by one or more microplates, petri dishes, conical tubes, or other media capable of conducting reactions, said media may function as the reaction chamber (230). In an example, the protein reservoir (205) may be implemented as a microplate storage system, wherein a plurality of microplates store individual proteins in the plate wells. During a reaction step, the required interaction species, reaction components, and other reactants may be added to the individual wells of the microplate, thereby turning each well into a reaction chamber (230). Accordingly, at least a portion of the protein reservoir may be configured to function as a reaction chamber (230).

[0115] Referring now to interaction species reservoir (210). In embodiments, interaction species reservoir (210) comprises a storage and dispensing system configured to contain and manage a plurality of chemical entities capable of interacting with proteins in biochemical reactions. Nonlimiting examples of such chemical entities include, for example, substrates, products, inhibitors, activators, cofactors, coenzymes, binding species, and ions. Interaction species reservoir (210) may be adapted, in some embodiments, to accommodate diverse chemical properties and storage requirements of said entities.

[0116] In embodiments, interaction species reservoir (210) may be implemented as a microplate storage system. In embodiments, the system comprises a plurality of microplates, wherein each microplate contains a plurality of wells. Each well may be configured to contain a distinct interaction species. The microplate storage system may further comprise an automated access mechanism for retrieving and dispensing compounds from said wells. In embodiments, the system comprises a multi-well plate (e.g., a multi-well cell culture plate) such as a 6-well, 12- well, 24-well, 48-well, 96-well, 384-well, or 1536 well plate. In embodiments, the system comprises an ANSI multi-well (e.g., microtiter) plate. For example, in some cases, the system may comprise a 96-well, 384-well, or 1536-well plate designed according the ANSI SLAS 4- 2004 (R2012) standard. In embodiments, the system comprises a plurality of conical tubes (e.g., greater than or equal to 2 and less than or equal to 1536 conical tubes). In embodiments, the system comprises a plurality of dishes such as petri dishes (e.g., greater than or equal to 2 and less than or equal to 1536 petri dishes).

[0117] In embodiments, interaction species reservoir (210) comprises as a vial storage system. In embodiments, interaction species reservoir (210) comprises a plurality of vials, wherein each vialis adapted to contain a distinct interaction species. In embodiments, the vials are arranged in one or more racks, with each rack designed to hold a predetermined number of vials. The vial storage system may further include a robotic arm or similar automated mechanism configured to retrieve and replace vials as needed for compound dispensing.

[0118] In embodiments, interaction species reservoir (210) comprises as a cassette-based storage system. For example, the system may comprise multiple cassettes, each cassette containing a predetermined number of sealed compartments. In embodiments, each compartment may be configured to hold a specific interaction species (e.g., the same or different interaction species). In embodiments, a cassette-based system may further include a mechanism for puncturing or otherwise accessing the sealed compartments to retrieve the contained compounds as needed.

[0119] In embodiments, interaction species reservoir (210) comprises a carousel storage system. For example, the system may comprise one or more carousels, each carousel containing a plurality of storage positions arranged in a circular or semi-circular configuration. Each storage position may be adapted to hold a container of a distinct interaction species. The carousel storage system may further include a rotational mechanism for aligning the desired storage position with a fixed access point, and an automated dispensing mechanism at said access point.

[0120] In embodiments, interaction species reservoir (210) comprises a matrix storage system. For example, the system may comprise a three-dimensional array of storage cells, wherein each cell is configured to contain a distinct interaction species. The matrix storage system may further include a coordinate-based retrieval mechanism capable of accessing any cell within the three- dimensional array for compound retrieval and dispensing.

[0121] In embodiments, interaction species reservoir (210) comprises a liquid handling robot with vial storage. For example, the robot may comprise a robotic arm capable of accessing and retrieving compounds stored in individual vials or tubes. The vials or tubes may be arranged in one or more temperature-controlled racks, wherein each rack may be maintained at a temperature based on the compounds contained therein.

[0122] In embodiments, interaction species reservoir (210) comprises a microfluidic chip. For example, the microfluidic chip may comprise a plurality of channels or wells, each containing a different interaction species. This configuration may advantageously allow for precise control over small volumes of compounds and may be integrated directly with other microfluidic components of system (200).

[0123] Interaction species reservoir (210) may, in embodiments, incorporate an automated synthesis module. For example, the automated synthesis module may comprise one or more reaction chambers configured for parallel synthesis of different compounds, thereby expanding the range of available interaction species in real-time.

[0124] For interaction species requiring cryogenic storage, in embodiments, interaction species reservoir (210) comprises a cryogenic storage system. For example, the cryogenic storage system may utilize liquid nitrogen or other cryogenic fluids to maintain extremely low temperatures necessary for the stability of certain compounds.

[0125] In embodiments where gaseous interaction species are used, interaction species reservoir (210) may comprise a gas delivery system. For example, the system may include a gas manifold capable of precisely delivering various gases to reaction chamber (230).

[0126] For solid compounds, interaction species reservoir (210) may be configured as a solid compound dispensing system. For example, the system may comprise mechanisms for accurately weighing and dispensing small amounts of powdered substances. In embodiments, interaction species reservoir (210) may further include a reconstitution module adapted to dissolve the solid compounds in an appropriate solvent. For example, the reconstitution module may comprise a plurality of solvent reservoirs, mixing chambers, and fluid transfer mechanisms. In embodiments, the reconstitution process may incorporate one or more reaction components stored in a separate compartment of interaction species reservoir (210). The system may be configured to combine these reaction components with the solvent during the reconstitution process, thereby preparing the interaction species in a form immediately suitable for use in subsequent reactions. The reconstituted compounds may then be transferred to a temporary storage area within interaction species reservoir (210) or directly to reaction chamber (230) as required by the experimental protocol.

[0127] Regardless of the specific embodiment, the interaction species reservoir (210) may incorporate various features to ensure optimal storage and handling of the contained compounds. These features may include, but are not limited to, temperature control mechanisms, humidity control systems, light protection measures, and atmosphere maintenance capabilities.

[0128] Interaction species reservoir (210), in embodiments, further comprises a compound tracking system, e.g., which may utilize barcode or RFID technology to uniquely identify and track each compound. In embodiments, the tracking system may be integrated with a databasecontaining information about each compound, including its chemical properties, storage requirements, and known interactions with proteins.

[0129] An automated dispensing mechanism may be incorporated into the interaction species reservoir (210). For example, the automated dispensing mechanism may be capable of delivering precise, small volumes of each compound as required for the reactions.

[0130] In embodiments, interaction species reservoir (210) comprises a quality control system configured to perform regular checks on the integrity and purity of the stored compounds. Advantageously, the design of the interaction species reservoir (210) may allow for scalability, enabling easy expansion to accommodate an increasing library of interaction species.

[0131] The interaction species contained within the reservoir (210) may be obtained from various sources. These may include, without limitation, commercial chemical libraries; natural product extracts from plants, marine organisms, and microbes; custom-synthesized compounds; combinatorial chemistry libraries; metabolomics-derived compounds; protein-derived peptides; computationally designed novel compounds; compounds identified in previous high-throughput screening campaigns; FDA-approved drug libraries; compounds from academic collaborations; and isolates from environmental samples.

[0132] In embodiments, part or all of the interaction species reservoir (210) may function as the reaction chamber (230). For example, if the interaction species reservoir (210) is implemented by one or more microplates, petri dishes, conical tubes, or other media capable of conducting reactions, said media may function as the reaction chamber (230). In an example, the interaction species reservoir (210) may be implemented as a microplate storage system, wherein a plurality of microplates store individual interaction species in the plate wells. During a reaction step, the required interaction species, reaction components, and other reactants may be added to the individual wells of the microplate, thereby turning each well into a reaction chamber (230). Accordingly, at least a portion of the interaction species reservoir (210) may be configured to function as a reaction chamber (230).

[0133] By accommodating interaction species from these diverse sources, the reservoir (210) advantageously enables the system (200), in embodiments, to explore a vast chemical space in its investigation of protein-interaction species interactions. This comprehensive approach aligns with the goal of maximizing the system's ability to obtain interaction data on a wide variety of different enzyme classes while minimizing resource usage.

[0134] In embodiments, the system comprises one or more reaction components reservoirs. Referring again to Fig. 2, in embodiments, reaction components reservoir (215) comprises a storage and dispensing system configured to contain and manage a plurality of reaction components. In embodiments, reaction components reservoir (215) may be implemented as a multi-chamber fluidic system. For example, in embodiments, the system comprises a plurality of chambers, wherein each chamber is configured to contain a distinct reaction component. The chambers may be fabricated from materials compatible with the stored components, such as glass, high-grade plastics, silicon, or corrosion-resistant metals.

[0135] In embodiments, reaction components reservoir (215) may be implemented as a multichamber fluidic system. In embodiments, the system may comprise a plurality of chambers, wherein each chamber is configured to contain a distinct reaction component. The plurality of chambers may be fabricated, for example, from materials compatible with the stored components, such as glass, high-grade plastics, silicon, or corrosion-resistant metals. The multichamber system may further include a network of microfluidic channels connected to each chamber, wherein said channels provide fluid communication between the chambers and / or one or more outlet ports. The network may be operatively coupled with pumps configured to draw reaction components from the individual chambers through the microfluidic channels, enabling precise dispensing of components from selected chambers to reaction chamber (230) via the multiplexer (220).

[0136] In embodiments, reaction components reservoir (215) in designed and adapted as a modular cartridge system. For example, in embodiments, the system may comprise interchangeable cartridges, each containing a specific reaction component or a pre-mixed combination of components. The cartridges may be designed with standardized interfaces for easy insertion and removal, allowing rapid reconfiguration of the reservoir for different experimental protocols.

[0137] In embodiments, reaction components reservoir (215) may be implemented as a gradient generation system. For example, in embodiments, the system may comprise a series of stock solutions and a mixing chamber capable of generating precise gradients or mixtures of reaction components. This configuration may advantageously allow, in some cases, for the exploration of a continuous range of reaction conditions within a single experiment.

[0138] Reaction components reservoir (215) may, in embodiments, incorporate an in-line dilution system. For example, in embodiments, the system may comprise concentrated stock solutions of reaction components and a precision dilution mechanism. This configuration may, in some cases, advantageously allow for the generation of a wide range of component concentrations from a minimal number of stock solutions, thereby increasing the system's flexibility and reducing storage requirements.

[0139] For volatile or gas-phase reaction components, reaction components reservoir (215) may be configured with a gas infusion system. For example, in embodiments, the system may comprise pressurized gas cylinders, flow controllers, and gas-permeable membranes for introducing gaseous components into liquid reaction mixtures.

[0140] In embodiments, reaction components reservoir (215) may also include a temperature control system. For example, in embodiments, the system may comprise Peltier elements, electric heating elements, circulating water baths, or other heating and cooling mechanisms to maintain optimal storage temperatures for each reaction component and to pre-equilibrate components to reaction temperatures when required.

[0141] In embodiments where synthesis or modification of reaction components may be desired immediately prior to use, reaction components reservoir (215) may incorporate an on-demand synthesis module. For example, the on-demand synthesis module may comprise miniaturized reaction vessels and necessary reagents for small-scale, automated synthesis of unstable or shortlived reaction components.

[0142] Reaction components reservoir (215) may further comprise a real-time monitoring system. For example, in embodiments, the system may include sensors for continuous measurement of critical parameters such as pH, ionic strength, and oxygen content of stored components. This monitoring system may be integrated with a feedback mechanism for automated adjustment of component properties as needed.

[0143] To ensure precise dispensing, in embodiments, reaction components reservoir (215) may incorporate a multi-modal dispensing system. For example, in embodiments, the system may comprise a combination of positive displacement pumps, piezoelectric dispensers, and pressure- driven flow controllers, allowing for accurate handling of components across a wide range of volumes and viscosities.

[0144] Reaction components reservoir (215) may, in embodiments, include a purification system for recycling and regenerating certain reaction components. For example, in embodiments, the system may comprise filtration units, ion exchange columns, or other purification mechanisms to extend the usable life of expensive or rare components.

[0145] In terms of sourcing, the reaction components contained within reaction components reservoir (215) may be obtained through a variety of means. These may include, without limitation, commercial suppliers of biochemical reagents; custom synthesis by specialized chemical manufacturers; in-house preparation using standardized protocols; isolation from biological sources such as cell extracts or tissue homogenates; and generation through enzymatic or chemical conversion processes. Those of ordinary skill in the art would be capable of selecting suitable reaction components and sources based upon the teachings of this specification. The system may be designed, in embodiments, to accommodate components from these diverse sources, allowing for flexibility in experimental design and optimization of reaction conditions.

[0146] Reaction components reservoir (215) is generally designed to work in concert with (e.g., via one or more fluidic components) the protein reservoir (205) and the interaction species reservoir (210), providing the necessary environmental conditions and supporting elements for a wide range of biochemical reactions. For example, this comprehensive approach enables the system to explore diverse reaction conditions and supports the investigation of a broad spectrum of protein classes, aligning with the goal of maximizing the system's ability to obtain interaction data on a wide variety of different enzyme classes while minimizing resource usage.

[0147] In embodiments, the system comprises a multiplexer. In embodiments, multiplexer (220) comprises an integrated system designed to orchestrate the combination of proteins, interaction species, and reaction components of at least two biochemical reactions. For example, in some embodiments, multiplexer (220) incorporates a processor (222), a database (224), and a sample handling system (226), to enable experimental design and execution.

[0148] In embodiments, the systems described herein comprise one or more (micro)controller(s) and / or (micro)processor(s). In embodiments, the controller is configured (e.g., programmed) to receive and transmit data commands to / from one or more components of the system and / or an interface component (or other control device such as a smartphone or other consumer electronic device). In embodiments, the data includes one or more signals from one or more sensors within the system. In embodiments, the process may be configured to adjust various parameters basedon external metrics e.g., in response to a signal from a sensor in electrical communication with the controller and / or in response to a signal from a user.

[0149] The embodiments described herein can be implemented in any of numerous ways. For example, the embodiments may be implemented by any suitable type of analog and / or digital circuitry. In embodiments, the embodiments may be implemented using hardware or a combination of hardware and software. When implemented using software, suitable software code can be executed on processing circuitry including any suitable processor (e.g., a microprocessor) or collection of processors, whether provided in a single computer or distributed among multiple computers (or other consumer electronic devices). It should be appreciated that any component or collection of components that perform the functions described above can be generically considered as one or more controllers that control the above-discussed functions. The one or more controllers can be implemented in numerous ways, such as with dedicated hardware or with one or more processors programmed using microcode or software to perform the functions recited above. The one or more embodiments can be implemented in numerous ways, such as with dedicated hardware, or with general purpose hardware (e.g., one or more processors) that is programmed using microcode or software to perform the functions recited above.

[0150] In embodiments, the systems described herein comprise wireless capabilities for enabling suitable communication with other devices / systems (e.g., for controlling aspects of the controller, controlling locomotion of the system, controlling a source of electromagnetic radiation, controlling a sensor or other component). Wireless devices are generally known in the art and may include, in some cases, LTE, WiFi and / or Bluetooth systems. In embodiments, the systems and / or devices described herein comprise such a wireless device (e.g., a short-range wireless component).

[0151] In embodiments, the embodiments described herein may be configured to adjust various parameters in response to an input from a user and / or a signal from a sensor and / or an externally located consumer electronic device (e.g., a CPU).

[0152] Any electronic component circuitry may be implemented by any suitable type of analog and / or digital circuitry. For example, the electronic component circuitry may be implemented using hardware or a combination of hardware and software. When implemented using software, suitable software code can be executed on any suitable processor (e.g., a microprocessor) orcollection of processors. The one or more electronic components can be implemented in numerous ways, such as with dedicated hardware, or with general purpose hardware (e.g., one or more processors) that is programmed using microcode or software to perform the functions recited above.

[0153] In this respect, it should be appreciated that one implementation of the embodiments described herein comprises at least one computer-readable storage medium (e.g., RAM, ROM, EEPROM, flash memory or other memory technology, or other tangible, non-transitory computer-readable storage medium) encoded with a computer program (i.e., a plurality of executable instructions) that, when executed on one or more processors, performs the abovediscussed functions of one or more embodiments. In addition, it should be appreciated that the reference to a computer program which, when executed, performs any of the above-discussed functions, is not limited to an application program running on a host computer. Rather, the terms computer program and software are used herein in a generic sense to reference any type of computer code (e.g., application software, firmware, microcode, or any other form of computer instruction) that can be employed to program one or more processors to implement aspects of the techniques discussed herein.

[0154] In embodiments, processor (222) serves as the central control unit of the multiplexer (220). In embodiments, processor (222) may be implemented as a high-performance computing system capable of real-time data processing and decision-making. In one embodiment, the processor (222) may utilize machine learning algorithms to optimize experimental design based on prior results and predictive models. Processor (222) may be configured to analyze the properties of proteins, interaction species, and reaction components to determine optimal combinations and reaction conditions. In embodiments, processor (222) may be adapted to dynamically adjust experimental parameters in response to interim results, enabling adaptive experimental protocols.

[0155] Database (224) generally functions as a comprehensive repository of information critical to the operation of the system. In embodiments, the database may contain detailed records of all proteins, interaction species, and reaction components available in the respective reservoirs (205, 210, 215). In embodiments, database (224) may include structural information, physicochemical properties, known interactions, and historical experimental data for each entity. Database (224) may be implemented using a scalable, high-performance database management system capableof rapid data retrieval and real-time updates. In embodiments, database (224) may incorporate a knowledge graph structure to represent complex relationships between different entities and facilitate advanced query capabilities.

[0156] Sample handling system (226), also referred to herein as a liquid handler, comprises a system designed to combine proteins, interaction species, and reaction components e.g., as directed by the processor (222). In embodiments, sample handling system (226) is in fluidic communication with one or more components of the system (e.g., via one or more fluidic and / or microfluidic channels, tubes, pipes, or the like).

[0157] In an example embodiment, the sample handling system (226) may be implemented as a simple gravity-fed dispensing system, wherein reservoirs containing the required components are positioned above the reaction vessels, and flow is controlled by electronically actuated valves. This configuration may be suitable for applications where precise volume control is less critical or where larger volumes are being manipulated. In embodiments, sample handling system (226) may utilize a peristaltic pump system, which may offer a balance between simplicity and precision, suitable for medium-throughput applications. Sample handling system (226) may alternatively be configured as a syringe-driven system, offering improved accuracy over the peristaltic pump system, particularly for smaller volumes. In embodiments, sample handling system (226) comprises a precision fluid manipulation system designed to accurately combine proteins, interaction species, and reaction components as directed by the processor (222). In an example embodiment, sample handling system (226) may utilize a combination of positive displacement pumps and microfluidic channels to achieve high-precision, low-volume liquid transfers. Sample handling system (226) may, in embodiments, incorporate multiple dispensing heads operating in parallel to increase throughput. In embodiments, sample handling system (226) may include acoustic liquid handling technology for contact-free, ultra-low volume dispensing. Sample handling system (226) may also be, in embodiments, equipped with inline dilution capabilities to generate concentration gradients or titration series of interaction species or reaction components. In embodiments, sample handling system (226) may incorporate a combination of these technologies, allowing for flexibility in handling a wide range of volumes and precision requirements. In embodiments, the system may be modular, allowing for the addition or replacement of different liquid handling technologies as needed for specific experimental protocols or as new technologies become available.

[0158] In embodiments, the sample handling system (226) my further include components that provide functionality for containerized transfer and transport of proteins, interaction species, reaction outputs, samples, reactants, and other system components. The sample handling system (226) may thus be configured to transfer and transport media such as microwell plates, vials, syringes, containers, tubes, flasks, etc., as necessary to implement the functionality of the system as described herein.

[0159] In embodiments, multiplexer (220) may be configured to employ a sample pooling configuration to optimize the exploration of protein-interaction species interactions. For example, the configuration may, in some cases, involve the combination of multiple proteins or interaction species in a single reaction vessel. For example, the combination may be performed in a manner that allows for subsequent deconvolution of individual interactions. Processor (222) may be programmed to access information stored in database (224) for the purpose of implementing pooling configurations and / or designing pooling strategies, in embodiments. Such pooling configurations and strategies may be designed to minimize potential interference between different molecular species and / or to maximize the information obtained from each experiment. For example, processor (222) may utilize algorithms to analyze the physicochemical properties of the proteins and interaction species, their known interaction profiles, and their potential for cross-reactivity. In embodiments, processor (222) may be configured to generate pooling configurations based on said analysis. In embodiments, processor (222) may be configured to access pooling configurations. In an example embodiment, the pooling configurations may comprise groupings of compatible proteins. In another example embodiment, the pooling configurations may comprise groupings of compatible interaction species. In yet another example embodiment, the pooling configurations may comprise groupings of both compatible proteins and compatible interaction species. The compatibility of proteins and / or interaction species for pooling may be determined based, for example, on their physicochemical properties, known interaction profiles, and / or potential for cross-reactivity as stored in the database (224). Sample handling system (226) may be operatively coupled to processor (222) and may be configured to prepare pooled samples according to the generated pooling configurations.

[0160] In embodiments, multiplexer (220) incorporates a quality control module. For example, the module may comprise spectrophotometric or other analytical instruments to verify thecomposition and concentration of reaction mixtures prepared by sample handling system (226). In embodiments, the quality control module may provide feedback to processor (222), allowing for real-time adjustments to liquid handling parameters to maintain precision and accuracy.

[0161] To enhance flexibility and throughput, multiplexer (220) may be designed with a modular architecture. This design may advantageously allow for the integration of additional liquid handling modules and / or the incorporation of specialized reaction preparation equipment as needed for specific experimental protocols. The modular design may also facilitate system upgrades and maintenance without disrupting ongoing experiments, in embodiments.

[0162] Multiplexer (220) may further comprise an environmental control system to maintain optimal conditions during the reaction preparation process. For example, in embodiments, the system may regulate temperature, humidity, and atmospheric composition to preserve the integrity of proteins and other sensitive components during transfer and mixing operations.

[0163] In embodiments, multiplexer (220) incorporates capabilities for in situ modification of proteins or interaction species. This may include an integrated enzymatic modification module for phosphorylation, glycosylation, or other post-translational modifications of proteins, or a chemical derivatization module for modifying interaction species immediately prior to experimental use, amongst others. Those of ordinary skill in the art would be capable of selecting suitable in situ modifications of proteins for use with the systems described herein based upon the teachings of this specification.

[0164] Multiplexer (220) may be designed to accommodate a wide range of experimental scales, from microliter-volume reactions for high-throughput screening to milliliter-volume preparations for detailed kinetic studies. This scalability may be achieved, for example, through the use of interchangeable liquid handling heads and software-controlled adjustment of dispensing parameters.

[0165] By integrating these various components and capabilities, multiplexer (220) may advantageously enable the efficient and precise preparation of diverse protein-interaction species interaction experiments. In embodiments, the system's ability to handle a wide range of proteins, as well as diverse interaction species and reaction components, generally aligns with the goal of generating comprehensive bioactivity data across a broad spectrum of protein classes and molecular interactions.

[0166] In embodiments, the system comprises reaction chamber (230). In embodiments, reaction chamber (230) comprises a vessel, or plurality of vessels, wherein individual biochemical reactions occur between proteins, interaction species, and / or reaction components. In embodiments, reaction chamber (230) may be configured to maintain optimal conditions for a diverse array of protein-interaction species reactions, including temperature control, pH regulation, and atmospheric composition management.

[0167] In embodiments, the reaction chamber (230) may include a single reaction vessel. For example, the reaction chamber (230) may be a beaker, test-tube, flask, vial, dish, ampoule, or any other suitable single compartment container. In such an example, the reaction vessel may be coextensive with the reaction chamber (230).

[0168] In an example embodiment, reaction chamber (230) may be implemented as a microplate format. For example, each microplate may be a reaction chamber comprising a plurality of wells, each well serving as an individual reaction vessel. The microplate may be fabricated from any suitable materials compatible with a wide range of biochemical reactions. Non-limiting examples include polypropylene, polystyrene, and glass. In embodiments, reaction chamber (230) may incorporate a temperature control system, which may include Peltier elements, circulating water baths, and / or other heating and cooling mechanisms to maintain precise reaction temperatures.

[0169] Reaction chamber (230) may be designed to accommodate various reaction scales and throughput requirements. In an example embodiment, reaction chamber (230) comprises a microplate with at least 6 wells. In another example embodiment, reaction chamber (230) may comprise a microplate with at least 24 wells. In another example embodiment, reaction chamber (230) may comprise a microplate with at least 96 wells. In another example embodiment, reaction chamber (230) may comprise a microplate with at least 384 wells. In another example embodiment, reaction chamber (230) may comprise a microplate with at least 1536 wells. The system may be adaptable to accommodate future microplate formats with higher well densities as they become available.

[0170] In embodiments, reaction chamber (230) comprises various formats such as microfluidic chips, capsules, droplets, capillary arrays, or a plurality of individual reaction tubes. In the case of microfluidic chips, reaction chamber (230) may comprise a network of channels and chambers etched or molded into a substrate material, allowing for precise control of reaction conditions and reduced reagent consumption. For example, capillary array embodiments may utilize abundle of capillary tubes, each serving as an individual reaction vessel, potentially allowing for continuous flow reactions. In embodiments, droplet-based formats may compartmentalize reagents into picoliter to nanoliter-sized droplets that are dispersed within an immiscible carrier phase. For example each droplet functions as an independent micro-reactor that can be merged, split, or sorted on demand, thereby enabling high-throughput screening, digital quantification, and rapid thermal cycling while minimizing cross-contamination. In embodiments, capsule based format may comprise a suspension or packed bed of individually addressable microcapsules. Non-limiting examples of suitable microcapsules include spherical shells about 5 pm to 500 pm in diameter fabricated from materials including but not limited to, glass, silica, alginate-poly-L- lysine, agarose, polyacrylamide, PLGA, or photocurable acrylates. For example, each microcapsule may enclose a discrete aliquot of reagents, thereby functioning as a self-contained micro-reactor with a high surface-to-volume ratio for rapid heat and mass transfer. In embodiments, the capsule shell may incorporate reversible pore-forming domains — thermoresponsive, pH-responsive, photo-cleavable, magnetically actuated, or otherwise stimuli- responsive — that allow controlled influx of substrates and efflux of products while retaining macromolecular constituents. Such controllable permeability may advantageously permit sequential reagent addition, synchronized reaction triggering, and straightforward pooling or downstream processing.

[0171] Multiplexer (220) may be operatively coupled to reaction chamber (230), e.g., to facilitate high-throughput analysis. In an example embodiment, multiplexer (220) is configured to combine the entire contents of at least two completed reactions from reaction chamber (230) into a single sample for analysis by molecular analysis module (240). Multiplexer (220) may comprise, in embodiments, a plurality of fluid transfer channels, each channel being connected to a distinct well or reaction vessel within reaction chamber (230). For example, the fluid transfer channels may converge into a common outlet leading to molecular analysis module (240). Multiplexer (220) may further comprise a series of electronically controlled valves, said valves being configured to selectively open and close to control the flow from each reaction vessel. For example, this configuration may enable the system to analyze reactions wherein all components are amenable to concurrent analysis,

[0172] In embodiments, multiplexer (220) may be configured to selectively extract and combine only the interaction species from at least two reactions in reaction chamber (230). For example,this selective combination may be achieved through the use of filtration, chromatography, or other separation techniques integrated into multiplexer (220).

[0173] Multiplexer (220) may also be designed and adapted, in embodiments, to perform preanalysis treatment of reaction products. In an example embodiment, multiplexer (220) may incorporate a protein denaturation module, wherein proteins from at least two reactions are denatured prior to combination and analysis. For example, the denaturation may be achieved through heat treatment, chemical denaturation, proteolytic degradation or other methods known in the art.

[0174] In embodiments, multiplexer (220) may comprise a protein filtration system. For example, in embodiments, the system may be configured to remove proteins from the reaction products of at least two reactions prior to combination and analysis. This approach may be particularly useful when the analysis focuses solely on small molecule products or unchanged interaction species.

[0175] In embodiments, multiplexer (220) may further be designed and adapted to perform reaction quenching, pH adjustment, or addition of internal standards to reaction products prior to combination and analysis. These capabilities generally allow for flexible handling of diverse reaction types and optimization of samples for subsequent analysis.

[0176] Reaction chamber (230) may also incorporate, in embodiments, in situ monitoring capabilities. In an example embodiment, reaction chamber (230) may include fiber optic probes for spectroscopic measurements of reaction progress. In embodiments, reaction chamber (230) may incorporate electrochemical sensors for real-time monitoring of reaction parameters such as pH, oxygen concentration, or specific ion activities. In embodiments, reaction chamber (230) may further comprise an integrated imaging system for visual monitoring of reactions. For example, the imaging system may include a high-resolution camera coupled with appropriate optics for magnification and focus adjustment. In embodiments, reaction chamber (230) may be equipped with a fluorescence imaging system, said system comprising an excitation light source, appropriate filters, and a sensitive detector for measuring fluorescence intensity or lifetime. Reaction chamber (230) may also incorporate Raman spectroscopy capabilities for label-free monitoring of molecular vibrations and structural changes during reactions. In embodiments, reaction chamber (230) may include surface plasmon resonance (SPR) sensors for real-time, label-free detection of biomolecular interactions. Reaction chamber (230) may also be equippedwith a miniaturized nuclear magnetic resonance (NMR) system for monitoring changes in molecular structure and dynamics during reactions. In embodiments, reaction chamber (230) may incorporate a quartz crystal microbalance (QCM) system for detecting mass changes associated with molecular interactions or enzymatic activities. These diverse monitoring capabilities may be employed individually or in combination, allowing for comprehensive, realtime analysis of reaction progress and outcomes across a wide range of protein-interaction species studies.

[0177] In embodiments, reaction chamber (230) and its interface with multiplexer (220) are configured to facilitate the concurrent execution and analysis of a plurality of diverse proteininteraction species reactions. In an example embodiment, reaction chamber (230) may be configured to process at least 2 (e.g., at least 3, at least 4, at least 5, at least 10, a least 20, at least 50, a least 100, at least 250, at least 500, at least 1000) unique protein-interaction species combinations concurrently. In embodiments, reaction chamber (230) may be configured to process at least 10 unique protein-interaction species combinations concurrently. In embodiments, reaction chamber (230) may be configured to process at least 100 unique proteininteraction species combinations concurrently. In embodiments, reaction chamber (230) may be configured to process at least 1,000 unique protein-interaction species combinations concurrently. In embodiments, reaction chamber (230) may be configured to process at least 10,000 unique protein-interaction species combinations concurrently. Other amounts and / or combinations of the above-referenced ranges of unique protein-interaction species combination are also possible (e.g., at least 1 and less than or equal to 100,000 unique protein-interaction species combinations).

[0178] Reaction chamber (230) may be configured to facilitate the interaction of each protein with multiple interaction species. In an example embodiment, reaction chamber (230) may be configured to facilitate the interaction of each protein with at least 2 distinct interaction species. In another embodiment, reaction chamber (230) may be configured to facilitate the interaction of each protein with at least 10 distinct interaction species. In embodiments, reaction chamber (230) may be configured to facilitate the interaction of each protein with at least 100 distinct interaction species. In embodiments, reaction chamber (230) may be configured to facilitate the interaction of each protein with at least 1,000 distinct interaction species. In embodiments, reaction chamber (230) may be configured to facilitate the interaction of each protein with atleast 10,000 distinct interaction species. In embodiments, reaction chamber (230) may be configured to facilitate the interaction of each protein with at least 100,000 distinct interaction species. In embodiments, reaction chamber (230) may be configured to facilitate the interaction of each protein with at least 1,000,000 distinct interaction species. In embodiments, reaction chamber (230) may be configured to facilitate the interaction of each protein with at least 10,000,000 distinct interaction species. In embodiments, reaction chamber (230) may be configured to facilitate the interaction of each protein with at least 100,000,000 distinct interaction species. In embodiments, reaction chamber (230) may be configured to facilitate the interaction of each protein with at least 1,000,000,000 distinct interaction species. Other amounts and / or combinations of the above-referenced ranges are also possible (e.g., interaction of each protein with at least 2 and less than or equal to 10,000,000,000 distinct protein interaction species).

[0179] In an example embodiment, reaction chamber (230) may be configured to process at least 2 unique proteins concurrently. In embodiments, reaction chamber (230) may be configured to process at least 10 unique proteins concurrently. In embodiments, reaction chamber (230) may be configured to process at least 100 unique proteins concurrently. In embodiments, reaction chamber (230) may be configured to process at least 1,000 unique proteins concurrently. In embodiments, reaction chamber (230) may be configured to process at least 10,000 unique proteins concurrently. In embodiments, reaction chamber (230) may be configured to process at least 100,000 unique proteins concurrently. In embodiments, reaction chamber (230) may be configured to process at least 1,000,000 unique proteins concurrently. Other amounts and / or combinations of the above-referenced ranges of processing are also possible (e.g., configured to process at least 2 and less than or equal to 10,000,000 unique proteins concurrently).

[0180] Reaction chamber (230) and multiplexer (220) may be adapted to minimize reagent consumption. In an example embodiment, the volume of each reaction in reaction chamber (230) may be at least 10 microliters. In embodiments, the volume of each reaction in reaction chamber (230) may be at least 5 microliters. In embodiments, the volume of each reaction in reaction chamber (230) may be at least 1 microliter. In embodiments, the volume of each reaction in reaction chamber (230) may be at least 500 nanoliters. In embodiments, the volume of each reaction in reaction chamber (230) may be at least 100 nanoliters. In embodiments, the volume of each reaction in reaction chamber (230) may be at least 10 nanoliters. In yet a furtherembodiment, the volume of each reaction in reaction chamber (230) may be at least 1 nanoliter. In still another embodiment, the volume of each reaction in reaction chamber (230) may be at least 100 picoliters. Other amounts and / or combinations of the above-referenced ranges of volumes are also possible (e.g., configured to process at least 100 picoliters and less than or equal to 100 microliters).

[0181] In embodiments, the system comprises a Molecular Analysis Module. Molecular analysis module (240) comprises an analytical system configured to measure and characterize the components of protein-interaction species reactions. In an example embodiment, molecular analysis module (240) may be adapted to analyze combined protein-interaction species reactions, wherein at least two such reactions are measured concurrently. In embodiments, molecular analysis module (240) may be adapted to analyze combined protein-interaction species reactions, wherein at least five such reactions are measured concurrently. In embodiments, molecular analysis module (240) may be adapted to analyze combined protein-interaction species reactions, wherein at least ten such reactions are measured concurrently. In embodiments, molecular analysis module (240) may be adapted to analyze combined protein-interaction species reactions, wherein at least a hundred such reactions are measured concurrently. In embodiments, molecular analysis module (240) may be adapted to analyze combined protein-interaction species reactions, wherein at least a thousand such reactions are measured concurrently. In embodiments, molecular analysis module (240) may be adapted to analyze combined protein-interaction species reactions, wherein at least ten thousand such reactions are measured concurrently. In embodiments, molecular analysis module (240) may be adapted to analyze combined proteininteraction species reactions, wherein at least a hundred thousand such reactions are measured concurrently. In embodiments, molecular analysis module (240) may be adapted to analyze combined protein-interaction species reactions, wherein at least a million such reactions are measured concurrently. Other amounts and / or combinations of the above-referenced ranges of analysis are also possible (e.g., adapted to analyze combined protein-interaction species reactions, wherein at least two and less than or equal to ten million such reactions are measured concurrently).

[0182] The module (240) may be further configured to measure only interaction species in embodiments, allowing for focused analysis of small molecules or other non-protein components. In embodiments, molecular analysis module (240) may be adapted to measuredenatured proteins along with interaction species, enabling comprehensive analysis of reaction outcomes.

[0183] In embodiments, molecular analysis module (240) may utilize mass spectrometry as its primary analytical technique. The mass spectrometry system employed may include, but is not limited to, Matrix-Assisted Laser Desorption / Ionization Time-of-Flight (MALDI-TOF), Electrospray Ionization Mass Spectrometry (ESI-MS), Liquid Chromatography -Mass Spectrometry (LC-MS), Gas Chromatography-Mass Spectrometry (GC-MS), Inductively Coupled Plasma Mass Spectrometry (ICP-MS), and Secondary Ion Mass Spectrometry (SIMS). These various forms of mass spectrometry may be employed individually or in combination to provide comprehensive analysis of reaction components. Advantageously, and without wishing to be bound by theory, analytical methods such as mass spectrometry (including but not limited to ESI-MS, LC-MS, GC-MS, ICP-MS, TOFMS including but not limited to MALDI-TOF and Q-TOF, DIMS, Ion Trap, and SIMS), spectrophotometry (including but not limited to UV- visible, IR, FTIR), raman spectroscopy and flame ionization detection are able to read compounds based on the physicochemical properties without the need to develop a proteinspecific assay.

[0184] In embodiments, molecular analysis module (240) may employ analytical techniques other than mass spectrometry. Non-limiting example of suitable analytical techniques include Nuclear Magnetic Resonance (NMR) spectroscopy, High-Performance Liquid Chromatography (HPLC), Gas Chromatography (GC), Capillary Electrophoresis (CE), Fourier Transform Infrared Spectroscopy (FTIR), Raman Spectroscopy, Fluorescence Spectroscopy, Circular Dichroism (CD) Spectroscopy, and Surface Plasmon Resonance (SPR). In embodiments, molecular analysis module (240) employs a combination of mass spectrometry and other analytical techniques.

[0185] In embodiments, molecular analysis module (240) is configured to analyze a wide range of molecular entities, including but not limited to; organic molecules; inorganic molecules; biomolecules such as proteins, nucleic acids, and lipids; ions; metal complexes; and quantum particles. In an example set of embodiments, molecular analysis module (240) is capable of detecting and quantifying changes in the oxidation state of metal ions, such as those involved in the catalytic cycle of iron-oxidizing enzymes.

[0186] Molecular analysis module (240) may be configured to handle a wide range of sample volumes. In an example embodiment, the module may be adapted to analyze sample volumes ofat least 1 milliliter. In embodiments, the module may be configured to analyze sample volumes of at least 100 microliters. In embodiments, the module may be capable of analyzing sample volumes of at least 10 microliters. In embodiments, the module may be adapted to analyze sample volumes of at least 1 microliter. In embodiments, the module may be configured to analyze sample volumes of at least 100 nanoliters. In embodiments, the module may be capable of analyzing sample volumes of at least 10 nanoliters. In still another embodiment, the module may be adapted to analyze sample volumes of at least 1 nanoliter. Other amounts and / or combinations of the above-referenced ranges of volumes are also possible (e.g., adapted to analyze sample volumes of at least 1 nanoliter and less than or equal to 10 milliliters).

[0187] In embodiments, the molecular analysis module may incorporate one or more automated sample preparation capabilities, including but not limited to, dilution, desalting, and chromatographic separation.

[0188] In embodiments utilizing mass spectrometry, molecular analysis module (240) may be equipped with high-resolution mass analyzers capable of distinguishing between closely related molecular species. For example, the high-resolution capabilities may enable the module to differentiate between proteins with high sequence homology, as well as between interaction species with similar molecular weights.

[0189] Molecular analysis module (240) may further comprise data processing capabilities configured to interpret the analytical results obtained from mass spectrometry measurements. For example, the data processing capabilities may include one or more processors operatively coupled to non-transitory computer-readable memory, said memory containing instructions that, when executed by the one or more processors, cause molecular analysis module (240) to perform data analysis operations.

[0190] In an example embodiment, molecular analysis module (240) may incorporate spectral deconvolution algorithms configured to resolve overlapping mass spectral peaks, thereby enabling the identification and quantification of individual components in complex mixtures. For example, the spectral deconvolution algorithms may employ techniques including, but not limited to, Fourier transform methods, wavelet transform methods, and maximum entropy approaches.

[0191] In embodiments, the molecular analysis module may utilize pattern recognition algorithms configured to identify specific proteins or interaction species based on their massspectral signatures. For example, the pattern recognition algorithms may comprise techniques such as principal component analysis (PCA), linear discriminant analysis (LDA), or artificial neural networks (ANNs) trained on reference spectral libraries.

[0192] Molecular analysis module (240) may, in embodiments, employ machine learning algorithms configured to predict protein-interaction species binding affinities based on the mass spectrometry data. For example, the machine learning algorithms may include, but are not limited to, support vector machines (SVMs), random forests, or deep learning neural networks trained on datasets correlating mass spectrometric features with known binding affinities.

[0193] In embodiments, the molecular analysis module may incorporate isotope pattern analysis algorithms configured to determine the elemental composition of detected ions based on the relative abundances of isotopic peaks. For example, the isotope pattern analysis may enable the differentiation between compounds with the same nominal mass but different elemental compositions.

[0194] Molecular analysis module (240) may, in embodiments, utilize fragmentation pattern analysis algorithms configured to elucidate the structural information of proteins and interaction species. For example, the fragmentation pattern analysis may employ techniques such as de novo sequencing for proteins or in silico fragmentation prediction for small molecules.

[0195] In embodiments, the module may incorporate quantitative analysis algorithms configured to determine absolute or relative abundances of proteins and interaction species. For example, the quantitative analysis algorithms may employ techniques including, but not limited to, isotope dilution methods, label-free quantification, or isobaric tagging approaches.

[0196] The data processing capabilities of molecular analysis module (240) may also include, in embodiments, data visualization tools configured to represent complex mass spectrometry data in interpretable formats. For example, the data visualization tools may generate two-dimensional or three-dimensional plots, heat maps, or interactive molecular structure viewers based on the processed mass spectrometry data.

[0197] In embodiments, the system comprises a demultiplexer. Demultiplexer (250) of the present invention comprises an integrated system designed to process and deconvolute the analytical data generated by molecular analysis module (240). For example, in embodiments, demultiplexer (250) incorporates a processor (252) and a database (254), working in concert to enable efficient and precise interpretation of complex, multiplexed reaction data. Demultiplexer(250) is configured, in embodiments, to receive and process data from molecular analysis module (240), which may include mass spectrometry data or other analytical data types, resulting from the analysis of at least two concurrent protein-interaction species reactions.

[0198] In an example embodiment, demultiplexer (250) may be adapted to process data from at least 2 concurrent reactions. In embodiments, demultiplexer (250) may be configured to handle data from at least 10 concurrent reactions. In embodiments, demultiplexer (250) may be configured to handle data from at least 100 concurrent reactions. In embodiments, demultiplexer (250) may be configured to handle data from at least 1,000 concurrent reactions. In embodiments, demultiplexer (250) may be configured to handle data from at least 10,000 concurrent reactions. In embodiments, demultiplexer (250) may be configured to handle data from at least 100,000 concurrent reactions. In embodiments, demultiplexer (250) may be capable of processing data from at least 1,000,000 concurrent reactions. The scalability of demultiplexer (250) allows for the system to accommodate increasing throughput requirements while maintaining data integrity and accuracy. Other amounts and / or combinations of the abovereferenced ranges of concurrent reactions are also possible (e.g., configured to handle data from at least 2 and less than or equal to 10,000,000 concurrent reactions).

[0199] In embodiments, processor (252) of demultiplexer (250) serves as the computational core, executing algorithms designed to separate and interpret the multiplexed data streams. For example, the processor may be implemented as a high-performance computing system capable of real-time data processing and analysis. Processor (252) may utilize advanced signal processing techniques, statistical methods, and machine learning algorithms to accurately demultiplex the complex data generated by molecular analysis module (240).

[0200] In embodiments, processor (252) is configured to receive output data from molecular analysis module (240), said output data comprising reads of a plurality of interaction species combined from at least two concurrent reactions into a single analyzed sample. In an example embodiment, processor (252) may be adapted to process data from at least 10 concurrent reactions combined into a single sample. In embodiments, processor (252) may be configured to handle data from at least 100 concurrent reactions combined into a single sample. In embodiments, processor (252) may be capable of processing data from at least 1,000 concurrent reactions combined into a single sample. Other amounts and / or combinations of the abovereferenced ranges of data are also possible (e g., capable of processing data from at least 2concurrent reactions and less than or equal to 10,000 concurrent reactions combined into a single sample).

[0201] In embodiments, processor (252) is further configured to execute demultiplexing algorithms designed to separate the combined reads based on the pooling configuration previously employed by multiplexer (220). For example, the demultiplexing algorithms may utilize advanced signal processing techniques, statistical methods, and machine learning approaches to accurately assign each read to its corresponding original reaction.

[0202] In embodiments, following the demultiplexing process, processor (252) is adapted to store the demultiplexed reads of interaction species in database (254). Database (254) is structured such that for each individual protein from an individual reaction, the data from the interaction species specific to that reaction is distinctly recorded and readily accessible. This organization advantageously enables the system to maintain discrete, interpretable results for each individual protein-interaction species reaction, despite the initial multiplexing of samples.

[0203] In embodiments, processor (252) in demultiplexer (250) may be configured to execute a plurality of demultiplexing algorithms for separating data received from molecular analysis module (240) based on various pooling configurations. In an example embodiment, processor (252) may employ a spectral deconvolution algorithm configured to resolve overlapping mass spectrometry peaks corresponding to different reaction products from pooled samples. For example, the algorithm may utilize known mass-to-charge ratios of expected products to assign signals to their respective reactions. In embodiments, processor (252) may implement a chromatographic peak separation algorithm adapted to demultiplex data from pooled samples analyzed by liquid chromatography-mass spectrometry (LC-MS). For example, the algorithm may be configured to utilize retention time information in conjunction with mass spectrometry data to distinguish between reaction products. In embodiments, processor (252) may employ a machine learning-based demultiplexing algorithm trained on reference datasets of known pooled reactions. For example, the algorithm may be adapted to recognize complex patterns in the pooled data and assign signals to their corresponding individual reactions. Processor (252) may be further configured to demultiplex various types of measurements from the pooled data and store them in database (254). These measurements may include, but are not limited to, absolute quantities of reaction products, relative abundances of interaction species, signal intensities of mass spectrometry peaks, chromatographic peak areas, isotopic distributions, fragmentationpatterns, and derived measurements such as binding affinities or reaction rates. Tn an example embodiment, processor (252) may be adapted to demultiplex and store quantitative data for at least TOO distinct interaction species from a single pooled sample. In embodiments, processor (252) may be configured to demultiplex and record signal intensity data for at least 1,000 mass spectrometry peaks from a pooled sample comprising at least 10 concurrent reactions. Other amounts and / or combinations of the above-referenced ranges of demultiplexing and recording are also possible (e.g., adapted to demultiplex and store quantitative data for at least 2 and less than or equal to 10,000 measurements (e.g., mass spectrometry peaks) from a pooled sample (e.g., comprising at least 10 concurrent reactions)).

[0204] In embodiments, database (254) functions as a comprehensive repository of information critical to the demultiplexing process. For example, the database may contain detailed records of experimental parameters, molecular signatures, and reference data necessary for accurate data interpretation. Database (254) may be implemented using a scalable, high-performance database management system capable of rapid data retrieval and real-time updates.

[0205] In embodiments, database (254) of the present invention comprises a data storage and management system configured to store, organize, and facilitate retrieval of demultiplexed data from protein-interaction species reactions. For example, database (254) may be operatively coupled to processor (252) and may be adapted to receive and store data processed by said processor.

[0206] In an example embodiment, database (254) may be implemented as a relational database management system. For example, the system may be configured to organize data into tables, wherein each table may correspond to a specific protein or interaction species. Database (254) may further comprise a schema designed to efficiently represent the relationships between proteins, interaction species, and reaction conditions.

[0207] In embodiments, database (254) may be implemented as a non-relational, distributed database system. For example, the system may be adapted to handle large volumes of unstructured or semi-structured data, enabling flexible storage and rapid retrieval of diverse data types generated by the protein-interaction species reactions.

[0208] In embodiments, database (254) may be configured to store multiple data types associated with each protein-interaction species reaction. As used herein, the term “proteininteraction species reaction” may encompass positive and negative results. A “protein-interaction species reaction” may refer to a reaction that has occurred between the protein and the interaction species. The term may also refer to a null result or a lack of reaction when suitable reaction conditions for the protein and the interaction species are provided. For example, the data types may include, but are not limited to, raw spectral data, processed peak information, quantitative measurements of interaction species, calculated binding affinities, and reaction kinetics parameters.

[0209] In an example embodiment, database (254) may be adapted to store data from at least 10,000 individual protein-interaction species reactions. In embodiments, database (254) may be configured to accommodate data from at least 100,000 individual protein-interaction species reactions. In embodiments, database (254) may be configured to accommodate data from at least 1,000,000 individual protein-interaction species reactions. In embodiments, database (254) may be configured to accommodate data from at least 10,00,000 individual protein-interaction species reactions. In embodiments, database (254) may be configured to accommodate data from at least 100,000,000 individual protein-interaction species reactions. In embodiments, database (254) may be configured to accommodate data from at least 1,000,000,000 individual proteininteraction species reactions. In embodiments, database (254) may be capable of storing data from at least 10,000,000,000 individual protein-interaction species reactions. Other amounts and / or combinations of the above-referenced ranges are also possible (e.g., configured to accommodate data from at least 10,00,000 and less than or equal to 100,000,000,000 individual protein-interaction species reactions).

[0210] In embodiments, database (254) may further comprise an indexing system configured to facilitate rapid data retrieval. For example, the indexing system may be adapted to create and maintain indices based on various parameters, including but not limited to protein identity, interaction species identity, reaction conditions, and data acquisition time.

[0211] In an example embodiment, database (254) may incorporate a versioning system. For example, the versioning system may be configured to maintain a history of data modifications, enabling tracking of changes over time and facilitating data auditing processes.

[0212] In embodiments, database (254) may be further configured with data compression capabilities. In an example embodiment, database (254) may employ lossless compression algorithms to reduce storage requirements while maintaining complete data fidelity. Inembodiments, database (254) may utilize lossy compression techniques for certain data types, such as raw spectral data, where some degree of data reduction is acceptable.

[0213] In embodiments, database (254) may also comprise a query optimization engine. For example, the engine may be configured to analyze incoming queries, develop efficient query execution plans, and utilize appropriate indexing strategies to minimize query response times.

[0214] In an example embodiment, database (254) may be implemented with distributed storage capabilities. For example, the capabilities may enable the database to be scaled across multiple physical or virtual servers, thereby increasing storage capacity and improving data access performance.

[0215] In embodiments, database (254) may further incorporate data backup and recovery mechanisms. For example, the mechanisms may be configured to create regular backups of the stored data and provide rapid recovery capabilities in the event of system failures.

[0216] In embodiments, database (254) may include data encryption features. For example, the features may be adapted to encrypt sensitive data at rest and in transit, ensuring data security and compliance with relevant data protection regulations.

[0217] In embodiments, database (254) may also be configured with an application programming interface (API). For example, the API may enable external systems or downstream analysis tools to access and retrieve stored data in a controlled and efficient manner.

[0218] In embodiments, the system may further comprise a user interface module. For example, the user interface module may be operatively coupled to one or more components of the system and may be configured to enable user interaction with, for example, the system. The user interface module may comprise a graphical user interface (GUI) accessible via a computing device in data communication with the system.

[0219] In an example embodiment, the user interface module may be adapted to receive user input related to experimental design parameters. For example, the parameters may include, but are not limited to, protein identifiers, interaction species identifiers, reaction condition specifications, and pooling configuration definitions. The user interface module may, in embodiments, further comprise a visual programming interface. For example, the visual programming interface may be configured to enable user definition of multi-step experimental protocols.

[0220] In embodiments, the user interface module may incorporate a data visualization component. For example, the data visualization component may be configured to render analytical data in a plurality of formats. These formats may include, without limitation, chromatographic representations, mass spectral displays, heat map visualizations, and three- dimensional molecular interaction models.

[0221] In embodiments, the user interface module may be further adapted to generate user- customizable reports. For example, the reports may be configured to summarize experimental results in a user-defined format.

[0222] In embodiments, the user interface module may comprise a machine learning-based recommendation engine. For example, the recommendation engine may be configured to propose experimental parameters based on analysis of historical experimental data and user-specified objectives.

[0223] The user interface module may, in embodiments, further comprise a remote access functionality. For example, the functionality may be configured to enable off-site monitoring of experimental progress and remote viewing of experimental results.

[0224] The present invention further provides methods for concurrent measurements of a plurality of protein reactions. In embodiments, the method comprises a series of steps that enable high-throughput analysis of protein-molecule interactions. The following description generally details each step of the method, beginning with the provision of a plurality of proteins, although other steps may also be possible.

[0225] Referring now to Fig. 1, some embodiments are generally directed to methods. The methods may be implemented, for example, on the systems and components described herein. In embodiments, the method comprises the following steps: providing a plurality of proteins (110); providing at least one interaction species (112); optionally providing at least one reaction component (114); combining inputs in reaction chamber(s) (120); allowing reactions to occur (130); combining reaction outputs (140); performing molecular analysis on combined outputs (150); processing and analyzing results using a demultiplexer (160); and providing and saving results in a database (170). The method described with respect to FIG. 1 is not limited to the exact description provided. Additional steps may be performed, steps may be removed or substituted or repeated, and steps may be performed in a different order as may be necessary or beneficial.

[0226] Embodiments, as shown in step 110, are directed to providing a plurality of proteins. In embodiments, the method comprises providing a plurality of proteins for concurrent analysis. For example, the proteins may be selected from an array of protein types maintained under controlled storage conditions, e.g., from a protein reservoir. The storage conditions may include temperature control ranging from cryogenic temperatures to room temperature, depending on the specific requirements of each protein.

[0227] In an example embodiment, the step of providing proteins may involve automated retrieval and dispensing of proteins from a storage unit. In embodiments, this step may utilize a microfluidic system for protein provision.

[0228] The proteins provided may encompass a wide range of types, as described above and herein, including but not limited to enzymes, transcription factors, channels, transporters, receptors, structural proteins, hormones, antibodies, chaperones, storage proteins, and contractile proteins. For example, the proteins may be naturally occurring, synthetic, engineered, or fragments thereof.

[0229] The method may accommodate proteins derived from various sources, as described above and herein, including but not limited to human, animal, plant, microbial (such as bacterial, fungal, or archaeal), and viral origins. The provided proteins may be wild-type, mutant, variant, or post-translationally modified. In embodiments, the proteins may be obtained through various means, including cell-based expression systems, cell-free protein synthesis, extraction from natural sources, commercial purchases, or isolation from cell lysates.

[0230] The method may be adapted to provide varying numbers of unique proteins concurrently. In an example embodiment, at least 2 unique proteins may be provided concurrently. In embodiments, the number of unique proteins provided concurrently may be at least 10, at least 100, at least 1,000, at least 10,000, at least 100,000, or at least 1,000,000.

[0231] The step of providing a plurality of proteins may further comprise, in embodiments, a quality control process to verify the integrity and activity of the provided proteins before proceeding to subsequent steps of the method.

[0232] Some embodiments, as shown in step 112, are generally directed to providing at least one interaction species. In embodiments, the method further comprises providing at least one interaction species for analysis with the proteins. The interaction species provided may include, but are not limited to, substrates, products, inhibitors, activators, cofactors, coenzymes, and otherbinding species that interact directly with proteins. These may encompass small molecules, peptides, nucleic acids, lipids, or other biochemical entities.

[0233] In an example embodiment, the method may involve providing a single interaction species. In embodiments, the method may provide multiple interaction species concurrently. The number of interaction species provided may range from at least 2 to at least 1,000,000 or more, depending on the scale and scope of the analysis.

[0234] The interaction species may be provided in various forms, as described above and herein, including but not limited to solutions, suspensions, or solid compounds. In embodiments, solid interaction species may be reconstituted into solution form as part of the providing step.

[0235] The method may accommodate interaction species from diverse sources, as described above and herein. These may include, but are not limited to, commercially available compound libraries, natural product extracts from plants, marine organisms, or microbes, synthetic compounds, combinatorial chemistry libraries, metabolomics-derived compounds, protein- derived peptides, computationally designed novel compounds, or isolates from environmental samples.

[0236] In embodiments, the step of providing interaction species may involve automated retrieval and dispensing from a storage unit. In embodiments, this step may utilize microfluidic systems or other advanced liquid handling technologies for precise delivery of interaction species.

[0237] In embodiments, the method may further comprise steps to ensure the quality and integrity of the provided interaction species. This may include verifying compound identity, purity, and stability prior to use in subsequent steps of the method.

[0238] In embodiments, the method may allow for the provision of interaction species in various concentrations or in concentration gradients. This feature may enable the method to assess dosedependent interactions between proteins and interaction species.

[0239] The step of providing at least one interaction species may be adapted to accommodate specific experimental designs, such as screening a single protein against many interaction species, or testing multiple proteins against a defined set of interaction species.

[0240] Some embodiments, as shown in step 114, are generally directed to optionally providing at least one reaction component. In embodiments, the method may further comprise the optional step of providing at least one reaction component to facilitate or support the biochemicalreactions between proteins and interaction species. Suitable reaction components may include, but are not limited to, solvents such as water, buffers, acids, bases, salts, cofactors, coenzymes, and other auxiliary chemicals that contribute to the reaction environment. As would be understood by those of ordinary skill in the art based upon the teachings of this specification, the specific reaction components provided may depend on the requirements of the particular proteins and interaction species involved in the analysis.

[0241] In an example embodiment, the method may involve providing a single reaction component. In embodiments, multiple reaction components may be provided concurrently. The number and type of reaction components may be tailored to the specific requirements of each experimental protocol.

[0242] The reaction components may be provided in various forms, including but not limited to aqueous solutions, organic solvents, or in some cases, gaseous components. In embodiments, the method may include steps for preparing reaction component mixtures or gradients to explore a range of reaction conditions.

[0243] The method may accommodate reaction components from various sources, including commercially available reagents, custom-synthesized components, or components isolated from biological sources. In embodiments, the method may include steps for on-demand synthesis or modification of reaction components immediately prior to their use.

[0244] The step of providing reaction components may involve automated dispensing systems for precise delivery of components. In embodiments, the method may utilize microfluidic systems or other advanced liquid handling technologies for accurate and reproducible provision of reaction components.

[0245] In embodiments, the method may further comprise quality control steps to ensure the purity, concentration, and stability of the provided reaction components. This may include pH measurements, conductivity tests, or spectroscopic analysis of component solutions.

[0246] In embodiments, the method may allow for the provision of reaction components in various concentrations or in gradients. This feature may enable the exploration of optimal reaction conditions for diverse protein-interaction species combinations.

[0247] The optional nature of step 114 generally allows the method to be advantageously adaptable to various experimental designs. In embodiments, the reaction components may bepre-mixed with the proteins or interaction species in previous steps. In embodiments, they may be added separately to fine-tune reaction conditions.

[0248] Step 114 of the method may also include provisions for special reaction conditions, such as the introduction of specific gas mixtures for oxygen-sensitive reactions, or the addition of stabilizing agents for particularly labile proteins or interaction species.

[0249] Some embodiments, as shown in step 120, are generally directed to using a multiplexer to combine said proteins, interaction species, and optional reaction components in a reaction chamber to create at least two distinct reactions, wherein each reaction comprises at least one protein from the plurality of proteins. In embodiments, step 120 comprises the precise and controlled combination of the provided components to initiate multiple concurrent biochemical reactions.

[0250] In an example embodiment, the multiplexer may employ a sample pooling configuration to optimize the exploration of protein-interaction species interactions. For example, the configuration may involve the combination of multiple proteins or interaction species in a single reaction vessel. The combination may be performed in a manner that allows for subsequent deconvolution of individual interactions.

[0251] In embodiments, the multiplexer may utilize a microfluidic system for precise control over the combination of reaction components. For example, the microfluidic system may comprise a network of channels and chambers etched or molded into a substrate material, allowing for precise control of reaction conditions and reduced reagent consumption.

[0252] The method may accommodate various scales of reaction volumes, as described above. In an example embodiment, the volume of each reaction may be at least 10 microliters. In embodiments, the reaction volume may be at least 5 microliters, at least 1 microliter, at least 500 nanoliters, at least 100 nanoliters, at least 10 nanoliters, at least 1 nanoliter, or at least 100 picoliters.

[0253] In embodiments, the method may involve the combination of each protein with multiple interaction species, as described above. For example, the number of distinct interaction species combined with each protein may range from at least 2 to at least 100,000,000 or more, depending on the scale and scope of the analysis.

[0254] The method may be adapted to create varying numbers of distinct reactions concurrently, as described above. In an example embodiment, at least 2 distinct reactions may be created. Inembodiments, the number of distinct reactions created concurrently may be at least 10, at least 100, at least 1,000, at least 10,000, at least 100,000, or at least 1,000,000.

[0255] In embodiments, the method may include steps for creating concentration gradients of interaction species or reaction components across multiple reactions. This feature may enable, for example, the exploration of dose-dependent interactions or optimal reaction conditions.

[0256] In embodiments, the method may further comprise steps for maintaining specific environmental conditions during the combination process. These may include temperature control, pH regulation, and atmospheric composition management to ensure optimal conditions for diverse protein-interaction species combinations.

[0257] In embodiments, the method may incorporate real-time monitoring capabilities during the combination process. This may include spectroscopic measurements, electrochemical sensing, or imaging techniques to verify successful combination and initiation of reactions.

[0258] The combination step may also include provisions for special reaction conditions, such as the introduction of specific gas mixtures for oxygen-sensitive reactions, or the addition of stabilizing agents for particularly labile proteins or interaction species.

[0259] n some embodiments, the method may include steps for creating replicate reactions to ensure reproducibility and statistical validity of results. The number of replicates may be determined based on the specific requirements of each experimental protocol.

[0260] In embodiments, the method further comprises quality control steps to verify the accuracy and precision of the combination process. This may include volume verification, mixture homogeneity assessment, or rapid analytical techniques to confirm the presence and concentration of key components in each reaction.

[0261] Some embodiments, as shown in step 130, are generally directed to allowing the at least two distinct reactions to occur. In embodiments, the step comprises maintaining appropriate conditions for the biochemical reactions between proteins and interaction species to proceed, while ensuring the integrity and stability of the reaction components.

[0262] In an example embodiment, the method may involve incubating the reactions for a predetermined period. For example, the period may range from seconds to hours or even days, depending on the nature of the specific protein-interaction species combinations and the kinetics of their interactions. In embodiments, the incubation time may be at least 1 second, at least 1 minute, at least 10 minutes, at least 1 hour, at least 6 hours, at least 12 hours, at least 24 hours, atleast 48 hours, or at least 72 hours. Other amounts and / or combinations of the above referenced- ranges are also possible (e.g., at least 1 second and less than or equal to 30 days).

[0263] The method may incorporate temperature control during the reaction period, as described above. In an example embodiment, the reactions may be maintained at a constant temperature throughout the incubation period. In embodiments, the method may employ temperature gradients or cycling protocols to optimize reaction conditions or to study temperature-dependent effects on protein-interaction species interactions.

[0264] In embodiments, the method may include steps for maintaining specific atmospheric conditions during the reaction period, as described above and herein. This may involve controlling the composition of gases in the reaction environment, which may be particularly important for oxygen-sensitive reactions or for studying the effects of gaseous interaction species.

[0265] In embodiments, the method may further comprise steps for agitation or mixing of the reaction mixtures during the incubation period. In an example embodiment, the reactions may be subjected to continuous gentle mixing to ensure homogeneity. In embodiments, the method may employ intermittent mixing protocols or static incubation, depending on the specific requirements of the reactions. In embodiments, the system comprises one or more mixing components (e.g., a mechanical agitator such a ultrasonic agitation, propeller mixing, shaker, or the like).

[0266] In embodiments, the method may include steps for maintaining or adjusting pH levels during the reaction period. This may involve the use of buffer systems or automated pH control mechanisms to ensure optimal conditions for diverse protein-interaction species combinations. Those of ordinary skill in the art would be capable of selecting suitable buffers based upon the teachings of this specification.

[0267] The method may incorporate real-time monitoring capabilities during the reaction period. In an example embodiment, this may include spectroscopic measurements to track the progress of reactions. In embodiments, the method may employ electrochemical sensing, imaging techniques, or other analytical methods to monitor reaction kinetics or detect the formation of products.

[0268] n some embodiments, the method may allow for the addition of components or adjustment of conditions during the reaction period. This may enable the study of timedependent effects or the investigation of sequential or coupled reactions.

[0269] In embodiments, the method may further comprise steps for preventing evaporation or contamination of reaction mixtures during the incubation period. In an example embodiment, this may involve the use of sealed reaction vessels or microfluidic systems. In embodiments, the method may employ oil overlays or other barrier techniques to maintain the integrity of reaction volumes.

[0270] In embodiments, the method may include steps for creating time-resolved reaction profdes. This may involve periodically sampling or analyzing the reactions at predetermined time points throughout the incubation period.

[0271] In embodiments the method may include steps for separately incubating reactions in different conditions such as temperature, reaction time, or atmosphere.

[0272] In embodiments, the method comprises steps that create a gaseous atmosphere for the reaction.

[0273] In embodiments, the gaseous atmosphere comprises carbon dioxide (CO2). In embodiments, CO2 serves as a direct reactant or carbon source in the reaction, participating chemically within the reaction pathway. In embodiments, CO2 functions primarily as a buffering or control agent to maintain a defined pH or acid-base equilibrium within the reaction environment. In embodiments the CO2 functions both as a reactant and buffering agent

[0274] While much of the description generally relates to the use of CO2 as the gaseous atmosphere, other gases are also possible. For example, in embodiments, the gaseous atmosphere comprises inert gases such as nitrogen (N2), argon (Ar), helium (He), neon (Ne), and all combinations thereof. In embodiments, the inert gas atmosphere is used to create anaerobic or oxygen-free reaction conditions

[0275] . In embodiments, oxygen (O2) is included in the gaseous atmosphere. In embodiments, oxygen serves directly as a reactant, oxidant, or electron acceptor. In embodiments, the oxygen concentration is controlled to modulate reaction kinetics, product distribution, or yield optimization.

[0276] In embodiments, hydrogen (Hs) is incorporated into the gaseous atmosphere. In embodiments, hydrogen gas functions as a reducing agent. In yet other of these embodiments hydrogen serves as a reactant

[0277] In embodiments, the gaseous atmospheres comprises halogen gases such as fluorine (F2), chlorine (CI2), bromine (B ), iodine (L), their gaseous derivatives (e.g., hydrogen chloride (HC1), hydrogen bromide (HBr)), halocarbons or halogenated compounds as direct reactants, catalysts, halogenating agents, or to modulate reaction conditions.

[0278] In embodiments, gaseous atmosphere comprises gases such as ammonia (NH3), sulfur dioxide (SO2), nitrogen oxides (NOX), carbon monoxide (CO), methane (CH4), ethane (C2H6), acetylene (C2H2), or other reactive gases are utilized as reactants, catalysts, or agents e.g., to control reaction pathways or kinetics.

[0279] In embodiments, the system comprises one or more sources of a gas (e.g., comprising the one or more gases described above and herein).

[0280] In embodiments, gaseous atmospheres incorporating water vapor (humidity control) are employed. In embodiments, humidity levels within the reaction atmosphere are controlled to modulate reaction rates or enzyme activity. In embodiments, humidity levels are used to control solvent properties, or to prevent evaporative concentration changes. In some such embodiments, the system may comprise one or more humidity control components (e.g., a source of moisture, a humidifier, a dehumidifier, a vaporizer, and combinations thereof).

[0281] In embodiments, gaseous atmospheres comprising gas mixtures (e.g., CO2 / N2, I / Ar, O2 / N2, H2 / N2, O2 / CO2, NH3 / H2, halogen / N2, and reactive / inert gas combinations) are employed.

[0282] In embodiments, the reaction atmosphere is maintained under vacuum conditions, either partial or complete, to remove or minimize the presence of specific gases, to prevent oxidation, moisture contamination, or other atmospheric interference, or to facilitate reaction processes sensitive to pressure. In some such embodiments, the system comprises one or more sources of pressure (e.g., a vacuum pump).

[0283] The method may also incorporate steps for terminating reactions at specific time points. In an example embodiment, this may involve rapid cooling or the addition of quenching agents to stop the reactions. In embodiments, the method may employ physical separation techniques to isolate reaction products from the active enzyme environment. In embodiments, quenchingagents are chemical denaturants. In embodiments, quenching agents are proteases. In embodiments, quenching agents are protein binders, aptamers or other protein binding agents. In embodiments, quenching agents are further reactants that react with the one or more components of the reaction . In embodiments, quenching agents are encapsulating, nanoparticle, membrane forming, or micelle forming agents that serve to separate reaction components .

[0284] In embodiments, the method may allow for parallel processing of reactions under different conditions. This may advantageously enable the simultaneous study of multiple reaction parameters or the comparison of reaction outcomes under varying environmental factors.

[0285] In embodiments, the method may further comprise quality control steps to ensure the stability and consistency of reaction conditions throughout the incubation period. This may include, in embodiments, periodic verification of temperature, pH, or other critical parameters to maintain the validity and reproducibility of the experimental results (e g., by a quality control component associated with the system).

[0286] In embodiments, the method comprises using the multiplexer to combine outputs from the at least two distinct reactions. For example, in embodiments, the method comprises the controlled aggregation of reaction products and remaining components from multiple individual reactions into a combined sample for subsequent analysis.

[0287] In an example embodiment, the method may involve the complete combination of all reaction products and remaining components from at least two distinct reactions. This approach may be suitable for reactions where all components are amenable to concurrent analysis. In embodiments, the method may employ selective combination strategies, focusing on specific subsets of reaction products or interaction species.

[0288] The method may incorporate various combination strategies to optimize downstream analysis. In an example embodiment, e.g., as shown in step 140 of Fig. 1, the multiplexer may combine reactions based on predefined pooling configurations designed to minimize potential interference between different molecular species. In embodiments, the method may employ adaptive combination strategies, where the pooling configuration is determined in real-time based on the observed progress or outcomes of individual reactions.

[0289] In embodiments, the method may include steps for preprocessing reaction outputs prior to combination. This may involve filtration, centrifugation, or other separation techniques to remove unwanted components or to concentrate specific reaction products. In an exampleembodiment, the method may employ protein denaturation steps prior to combination, which may be particularly useful when the analysis focuses on small molecule products or unchanged interaction species.

[0290] The method may accommodate various scales of combination, as described above and herein. In an example embodiment, the multiplexer may combine outputs from at least 2 distinct reactions. In embodiments, the number of reactions combined may be at least 10, at least 100, at least 1,000, at least 10,000, at least 100,000, or at least 1,000,000, depending on the scale and throughput of the experimental setup.

[0291] In embodiments, the method may involve the addition of internal standards or calibrants during the combination process. This may enable more accurate quantification and normalization of reaction products in subsequent analysis steps. The internal standards may be isotopically labeled analogs of expected reaction products or other compounds with similar chemical properties.

[0292] The method may incorporate steps for controlling the ratios of combined reaction outputs. In an example embodiment, this may involve equal volume combination of all reactions. In embodiments, the method may employ weighted combination strategies, where the volume or proportion of each reaction in the final mixture is adjusted based on predefined criteria or realtime analytical feedback.

[0293] In embodiments, the method may include steps for temporal resolution in the combination process. This may involve combining reaction outputs at different time points or creating time-resolved pools to capture the kinetics of reactions across multiple experiments.

[0294] In embodiments, the method may further comprise steps for maintaining the chemical integrity of reaction products during the combination process. This may include temperature control, pH adjustment, or the addition of stabilizing agents to prevent degradation or unwanted side reactions in the combined sample.

[0295] In embodiments, the method may incorporate inline analytical techniques during the combination process. This may involve spectroscopic, chromatographic, or other rapid analytical methods to verify the composition of the combined sample and to ensure successful integration of individual reaction outputs.

[0296] The method may also include steps for creating replicate combined samples. This may enable multiple analyses of the same set of reactions or provide backup samples for verification and quality control purposes.

[0297] In embodiments, the method may allow for the creation of multiple combined samples from the same set of reactions, each optimized for different downstream analytical techniques. For example, one combined sample may be prepared for mass spectrometry analysis, while another may be optimized for chromatographic separation.

[0298] In embodiments, the method may further comprise steps for documenting and tracking the combination process. This may include recording the identity and proportion of each reaction in the combined sample, as well as any processing steps or additions made during the combination. Such documentation is crucial for subsequent deconvolution and interpretation of analytical results.

[0299] Some embodiments, as shown in step 150 of Fig. 1, are generally directed to analyzing the combined reaction outputs using a molecular analysis module. In embodiments, the step comprises the comprehensive characterization and quantification of reaction products and remaining components from the multiplexed reactions.

[0300] In an example embodiment, the method may employ mass spectrometry as the primary analytical technique, as described above and herein. The mass spectrometry analysis may utilize various ionization methods and mass analyzer configurations to accommodate a wide range of molecular species. In embodiments, the method may employ Matrix-Assisted Laser Desorption / Ionization Time-of-Flight (MALDI-TOF) mass spectrometry for the analysis of large biomolecules such as proteins or peptides. In embodiments, the method may utilize Electrospray Ionization Mass Spectrometry (ESI-MS) for the analysis of both small molecules and larger biomolecules in solution.

[0301] In embodiments, the method may incorporate chromatographic separation techniques prior to mass spectrometry analysis. In an example embodiment, the method may employ Liquid Chromatography-Mass Spectrometry (LC-MS) to separate and analyze complex mixtures of reaction products. In embodiments, the method may utilize Gas Chromatography-Mass Spectrometry (GC-MS) for the analysis of volatile or derivatized reaction products.

[0302] In embodiments, the method may employ high-resolution mass spectrometry techniques. This may include the use of Fourier Transform Ion Cyclotron Resonance (FT-ICR) or Orbitrapmass analyzers to achieve ultra-high mass resolution and accuracy, enabling the differentiation of molecules with very similar masses.

[0303] In embodiments, the method may accommodate various sample volumes for analysis, as described above and herein. In an example embodiment, the molecular analysis module may be capable of analyzing sample volumes of at least 1 milliliter. In embodiments, the module may be configured to analyze sample volumes of at least 100 microliters, at least 10 microliters, at least 1 microliter, at least 100 nanoliters, at least 10 nanoliters, or at least 1 nanoliter.

[0304] In embodiments, the method may incorporate tandem mass spectrometry (MS / MS) techniques, as described above and herein. This may involve the fragmentation of selected ions to obtain structural information or to increase specificity in the detection of target molecules. The method may employ various fragmentation techniques, including collision-induced dissociation (CID), electron transfer dissociation (ETD), or photodissociation.

[0305] In embodiments, the method may further comprise steps for quantitative analysis of reaction products. In an example embodiment, this may involve the use of isotope dilution methods, where isotopically labeled standards are added to the sample for absolute quantification. In embodiments, the method may employ label-free quantification techniques based on ion intensity or spectral counting.

[0306] In embodiments, the method may incorporate alternative or complementary analytical techniques, as described above and herein. These may include, but are not limited to, Nuclear Magnetic Resonance (NMR) spectroscopy for structural elucidation, High-Performance Liquid Chromatography (HPLC) for high-resolution separation, or Capillary Electrophoresis (CE) for the analysis of charged species.

[0307] In other embodiments the method may incorporate spectrophotometery to measure the absorbance or emission properties of reaction products.

[0308] In embodiments, the method may incorporate Raman spectroscopy for molecular fingerprinting, enabling structural characterization, identification, and monitoring of reaction intermediates or products based on vibrational modes.

[0309] In embodiments, the method may incorporate a Flame Ionization Detector (FID) for sensitive and selective detection and quantification of organic reaction products, by measuring ions generated during combustion.

[0310] The method may include steps for automated sample preparation prior to analysis. This may involve inline desalting, concentration, or derivatization of samples to optimize them for the chosen analytical technique.

[0311] In embodiments, the method may employ multiplexed or parallel analysis techniques to increase throughput. This may involve the use of multiple molecular analysis modules operating in parallel or the implementation of ion mobility spectrometry for additional separation of complex mixtures.

[0312] In embodiments, the method may further comprise steps for real-time data analysis during the analytical process, as described in more detail above. This may include automated peak picking, spectral deconvolution, or preliminary identification of known reaction products to guide subsequent analysis steps (e.g., as described above in the context of the molecular analysis module).

[0313] In embodiments, the method may incorporate ion mobility spectrometry in conjunction with mass spectrometry. This technique may provide an additional dimension of separation based on the size and shape of ions, enhancing the resolution of complex mixtures and providing structural information.

[0314] The method may also include steps for analyzing intact protein-ligand complexes. In an example embodiment, this may involve native mass spectrometry techniques to preserve non- covalent interactions during the analysis process.

[0315] In embodiments, the method may employ imaging mass spectrometry techniques. This may be particularly useful for spatially resolved analysis of reaction products in heterogeneous samples or for monitoring the distribution of interaction species in complex biological matrices.

[0316] In embodiments, the method may further comprise quality control steps throughout the analysis process. This may include the regular analysis of blank samples, quality control standards, and replicate analyses to ensure the reliability and reproducibility of the analytical results.

[0317] In embodiments, as shown in step 160 of Fig. 1, the method comprises processing the analysis results using a demultiplexer. In embodiments, the step comprises the deconvolution and interpretation of the complex data generated from the analysis of combined reaction outputs, enabling the attribution of results to specific protein-interaction species combinations.

[0318] In an example embodiment, the method may employ spectral deconvolution algorithms to resolve overlapping mass spectrometry peaks corresponding to different reaction products from pooled samples. These algorithms may utilize known mass-to-charge ratios of expected products to assign signals to their respective reactions. In embodiments, the method may implement chromatographic peak separation algorithms adapted to demultiplex data from pooled samples analyzed by liquid chromatography -mass spectrometry (LC-MS), utilizing retention time information in conjunction with mass spectrometry data to distinguish between reaction products. In embodiments, the method may implement chemometric algorithms adapted to demultiplex complex spectroscopic datasets, such as those obtained from NMR or UV-visible spectroscopy, to resolve overlapping resonance signals and assign structural features to distinct reaction products. In embodiments, the method may utilize spectral baseline correction and curve-fitting algorithms in spectrophotometry to accurately quantify analyte concentrations, accounting for spectral interferences and overlapping absorbance or emission bands. In embodiments, Raman spectroscopy data may be processed using multivariate statistical analyses, to differentiate closely related reaction products based on variations in vibrational spectra. Still some embodiments employing Flame Ionization Detection (FID) may integrate peak-integration algorithms and calibration curve methods to quantify and resolve signals arising from co-eluting volatile organic compounds. Furthermore, embodiments incorporating Capillary Electrophoresis (CE) or High-Performance Liquid Chromatography (HPLC) may leverage retention or migration-time alignment algorithms, coupled with peak shape analysis, to improve resolution and facilitate accurate identification and quantification of reaction products in pooled sample datasets.

[0319] The method may incorporate machine learning-based demultiplexing algorithms trained on reference datasets of known pooled reactions. In an example embodiment, these algorithms may be adapted to recognize complex patterns in the pooled data and assign signals to their corresponding individual reactions. In embodiments, the method may employ neural network models capable of learning and adapting to novel spectral patterns, enhancing the system's ability to demultiplex increasingly complex reaction mixtures.

[0320] In embodiments, the method may include steps for quantitative analysis of demultiplexed data. This may involve the determination of absolute quantities of reaction products, relative abundances of interaction species, or derived measurements such as binding affinities or reactionrates. The method may employ various quantification strategies, including isotope dilution methods, label-free quantification, or isobaric tagging approaches.

[0321] The method may accommodate the processing of data from various numbers of pooled reactions, as described in more detail above and herein. In an example embodiment, the demultiplexer may be adapted to process data from at least 10 concurrent reactions combined into a single sample. In embodiments, the demultiplexer may be configured to handle data from at least 100, at least 1,000, at least 10,000, at least 100,000, or at least 1,000,000 concurrent reactions combined into a single sample.

[0322] In embodiments, the method may incorporate isotope pattern analysis algorithms to determine the elemental composition of detected ions based on the relative abundances of isotopic peaks. This may enable the differentiation between compounds with the same nominal mass but different elemental compositions, enhancing the accuracy of demultiplexing for complex reaction mixtures.

[0323] In embodiments, the method may further comprise steps for fragmentation pattern analysis to elucidate structural information of proteins and interaction species. In an example embodiment, this may involve de novo sequencing algorithms for proteins. In embodiments, the method may employ in silico fragmentation prediction for small molecules to aid in the identification and demultiplexing of reaction products.

[0324] In embodiments, the method may include steps for correlating demultiplexed data with the original pooling configuration employed by the multiplexer. This may involve accessing stored information about the experimental design and using it to guide the demultiplexing process and validate the results.

[0325] The method may incorporate error correction and noise reduction algorithms to improve the quality of demultiplexed data. In an example embodiment, this may involve the use of statistical methods to distinguish true signals from background noise. In embodiments, the method may employ machine learning techniques to identify and correct systematic errors in the demultiplexing process.

[0326] In embodiments, the method may include steps for integrating data from multiple analytical techniques. This may involve the correlation of mass spectrometry data with results from complementary techniques such as NMR or chromatography to enhance the accuracy and comprehensiveness of the demultiplexing process.

[0327] In embodiments, the method may further comprise steps for kinetic analysis of reaction data. In an example embodiment, this may involve the demultiplexing of time-resolved data to reconstruct reaction profdes for individual protein-interaction species combinations. In embodiments, the method may employ mathematical modeling techniques to extract kinetic parameters from the demultiplexed data.

[0328] In embodiments, the method may incorporate steps for automated identification and characterization of unexpected reaction products. This may involve the use of database searching algorithms, in silico fragmentation prediction, or machine learning-based classification techniques to identify novel compounds or reaction pathways.

[0329] The method may also include steps for assessing and reporting the confidence levels of demultiplexed results. In an example embodiment, this may involve the calculation of statistical measures such as false discovery rates or confidence intervals for quantitative measurements. In embodiments, the method may employ probabilistic models to assign confidence scores to the attribution of signals to specific reactions.

[0330] In embodiments, the method may incorporate steps for iterative refinement of the demultiplexing process. This may involve using the results of initial demultiplexing to inform and improve subsequent rounds of analysis, potentially incorporating feedback from downstream data interpretation or experimental validation.

[0331] In embodiments, as shown in step 170 of Fig. 1, the method comprises storing the generated output from the demultiplexing process. In embodiments, this step comprises the systematic organization, preservation, and management of the processed data, ensuring its accessibility for further analysis, interpretation, and long-term archival.

[0332] In an example embodiment, the method may employ a relational database management system for data storage. For example, the system may be configured to organize data into tables, wherein each table may correspond to a specific protein, interaction species, or reaction condition. The database schema may be designed to efficiently represent the relationships between proteins, interaction species, and reaction outcomes, facilitating complex queries and data retrieval.

[0333] In embodiments, the method may utilize a non-relational, distributed database system for data storage. This approach may be particularly suitable for handling large volumes of unstructured or semi-structured data generated from high-throughput experiments. The systemmay be adapted to store diverse data types, including raw spectral data, processed peak information, quantitative measurements, and derived parameters such as binding affinities or kinetic constants.

[0334] The method may incorporate data compression techniques to optimize storage efficiency. In an example embodiment, the method may employ lossless compression algorithms to reduce storage requirements while maintaining complete data fidelity. In embodiments, the method may utilize lossy compression techniques for certain data types, such as raw spectral data, where some degree of data reduction is acceptable without compromising the overall integrity of the results.

[0335] In embodiments, the method may include steps for data indexing to facilitate rapid retrieval of stored information. The indexing system may be adapted to create and maintain indices based on various parameters, including but not limited to protein identity, interaction species identity, reaction conditions, and data acquisition time. This approach may significantly enhance the efficiency of data retrieval for subsequent analysis or reporting.

[0336] The method may accommodate the storage of data from varying numbers of individual protein-interaction species reactions, as described in more detail above and herein. In an example embodiment, the storage system may be adapted to store data from at least 10,000 individual reactions. In embodiments, the system may be configured to accommodate data from at least 100,000, at least 1,000,000, at least 10,000,000, at least 100,000,000, at least 1,000,000,000, or at least 10,000,000,000 individual reactions.

[0337] In embodiments, the method may incorporate a versioning system for stored data. This system may be configured to maintain a history of data modifications, enabling tracking of changes over time and facilitating data auditing processes. The versioning system may be particularly useful for long-term studies or for projects involving multiple rounds of data analysis and interpretation.

[0338] In embodiments, the method may further comprise steps for metadata management. In an example embodiment, this may involve the storage of detailed information about experimental conditions, instrument parameters, and data processing steps associated with each dataset. In embodiments, the method may employ a standardized metadata format to ensure interoperability with other data management systems and to facilitate data sharing across different research platforms.

[0339] In embodiments, the method may include steps for data backup and recovery. This may involve the implementation of regular backup routines, potentially utilizing both local and cloudbased storage solutions to ensure data redundancy and protection against loss. The method may also incorporate disaster recovery protocols to enable rapid restoration of data in the event of system failures or other unforeseen circumstances.

[0340] The method may incorporate data encryption features to ensure the security of stored information. In an example embodiment, this may involve the encryption of sensitive data both at rest and in transit. In embodiments, the method may employ multi-factor authentication systems to control access to stored data, ensuring that only authorized personnel can retrieve or modify the information.

[0341] In embodiments, the method may include steps for data integration with external resources. This may involve the implementation of application programming interfaces (APIs) to enable seamless data exchange with other research databases, analysis tools, or collaborative platforms. The integration capabilities may enhance the value of the stored data by facilitating cross-referencing with external datasets or enabling more comprehensive meta-analyses.

[0342] In embodiments, the method may further comprise steps for automated data quality assessment and curation. In an example embodiment, this may involve the implementation of algorithms to detect anomalies or inconsistencies in stored data. In embodiments, the method may employ machine learning techniques to identify patterns or trends in the data that may indicate systematic errors or biases in the experimental process.

[0343] In embodiments, the method may include steps for generating data summaries or reports. This may involve the creation of standardized data views or visualizations that provide at-a- glance insights into the stored information. The summaries may be customizable to meet the specific needs of different user groups or analysis objectives.

[0344] The method may also incorporate steps for managing data retention and archival. In an example embodiment, this may involve the implementation of data lifecycle management policies, defining how long different types of data should be retained and under what conditions they may be archived or deleted. In embodiments, the method may employ hierarchical storage management techniques to optimize the balance between data accessibility and storage costs.

[0345] Fig. 3 illustrates a method for measuring a plurality of interacting molecules concurrently. The method may be performed on a system, such as an automated or roboticsystem, such as system 200, described above, that includes a protein reservoir, an interaction species reservoir, and optionally a reaction components reservoir. The system may further include at least one processor configured to carry out software instructions as well as a the necessary electrical, electronic, and computer components required to implement the described functionality. The system may further include a sample handling system (also referred to as a liquid handler), a reaction chamber (which may comprise one or more reaction vessels), and a molecular analysis module. In embodiments, the at least one processor may cooperate with the sample handling system to carry out the functionality of a multiplexer, as described herein. In embodiments, the at least one processor may carry out the functionality of a demultiplexer, as described herein. The multiplexing and demultiplexing operations may be carried out by a same processor or a different processor as may be appropriate. Examples of such components are discussed in greater detail above. In embodiments, the operations of method 3000 may be entirely or partially automated. The automated system described herein may carry out any or all of the operational steps described below. In embodiments, at least a portion of the operations of method 3000 may be carried out by manual user intervention.

[0346] The method 3000 may further include variations, including additions, subtractions, and substitutions of various operations and other aspects. It is not required that the steps or operations of method 3000 be carried out in the order described below and it is not required that each and every step or operation be performed. Further, the method 3000 is not limited to the description below and with respect to FIG. 3 but my further encompass and incorporate as an addition or in combination, any additional aspects, details, or embodiments discussed herein (e.g., with respect to FIGS. 1 and 2) without limitation unless otherwise stated.

[0347] In embodiments, the reaction chamber may be included as an aspect (e.g., as part or all) of either the protein reservoir or the interaction species reservoir. For example, the protein reservoir may include one or more multi-well plates containing proteins of the protein reservoir. In an embodiment, the multi-well plate or plates that contain the proteins of the protein reservoir may be employed as reaction chambers. For example, the wells of the plates may store proteins and the interaction species may be added directly to the protein storing wells to facilitate the reactions. In further embodiments, the reaction chamber may be included as an aspect (e.g., as part or all) of the interaction species reservoir in a similar manner.

[0348] The sample handling system, also referred to as a liquid handler, may be configured to provide operative coupling between any combination of the protein reservoir, the interaction species reservoir, the optional reaction components reservoir, the reaction chamber, and / or the molecular analysis module. The sample handling system may be configured to facilitate liquid transfer, e.g., via robotic pipetting, between the various system components. The sample handling system may further be configured to provide transfer of entire multi-well plates or other similar consumable products between system aspects. Operative coupling may refer to the capability of the sample handling system to transfer proteins, interaction species, reaction components, and / or reaction output samples between various aspects of the system, for example, via direct liquid transfer and / or by transferring containers or chambers that may include these. The sample handling system may further be configured to combine reaction output samples into a combined vessel for the molecular analysis module. In embodiments, some materials transfer operations may be performed manually - e.g., a reaction vessel may be transported manually to the molecular analysis module. The specific configuration and function of the sample handling system may vary according to the specific needs of the system.

[0349] In an operation 3002, the method 3000 may include a step of selecting from the protein reservoir a plurality of proteins to be reacted. The step of selecting the plurality of proteins to be reacted may include selection of specific proteins, from the protein reservoir, to be reacted with interaction species. Selecting may be performed by the at least one processor according to a pooling configuration, as discussed below. Other considerations for the selection of proteins from the protein reservoir may be understood with reference to Examples 1-8, as discussed below.

[0350] In an operation 3004, the method 3000 may include a step of selecting from the interaction species reservoir at least one interaction species to be reacted. The step of selecting the at least one interaction species to be reacted may include selection of one or more specific interaction species, from the interaction species reservoir, to be reacted with selected proteins. In embodiments, the at least one interaction species may include a plurality of interaction species. Selecting may be performed by the at least one processor according to a pooling configuration, as discussed below. Other considerations for the selection of interaction species from the interaction species reservoir may be understood with reference to Examples 1-8, as discussed below.

[0351] FIG. 4 illustrates a pooling configuration 4000. The pooling configuration includes a plurality of proteins 4001 and at least one interaction species 4002. The pooling configuration further includes at least one reaction pool and, in embodiments, a plurality of reaction pools 4010a, 4010b . . . 401 On. The at least one interaction species 4002 and the plurality of proteins 4001 may be determined according to at least one reaction pool 4010a-n of the pooling configuration 4000.

[0352] Each reaction pool 4010 may include at least two selected proteins from the plurality of proteins 4001 and one or more selected interaction species from the at least one interaction species 4002. Thus, each reaction pool 4010 may include components of at least two reactions. Each reaction pool 4010 may be considered to include at least two protein / interaction species pairs, where each pair represents components of potential reaction. Collectively, the reaction pools 4010a-n of the pooling configuration 4000 may include all of the at least one interaction species 4001 and the all of plurality of proteins 4002. In embodiments, each of the plurality of proteins 4002 and each of the at least one interaction species 4001 may be represented in the reaction pools 4010a-n one or more times. In embodiments, a pooling configuration may include all potential pairs of proteins and interaction species from among the plurality of proteins and the at least one interaction species - e.g. each protein is paired with each of the interaction species in at least one reaction pool 4010 of the pooling configuration 4000. The pooling configuration 4000 represents a combinatorial pooling of the plurality of proteins 4001 and the at least one interaction species 4002.

[0353] As discussed above, the most significant bottleneck in screening a large number of proteins against a large number of interaction species is the physical analysis step, e.g., analysis by a molecular analysis module to determine whether a selected protein has interacted with a selected interaction species. The pooling configurations 4000 of embodiments herein are selected such that the reaction outputs of the plurality of proteins and the at least one interaction species may be combined to undergo molecular analysis concurrently, thereby accelerating the process.

[0354] As discussed herein, a “pooling configuration” represents a conceptual arrangement of a plurality of proteins and at least one interaction species into “pools.” The physical protein samples and the physical interaction species may be combined (i.e., multiplexed) according to the pools and the pooling configuration. All combined physical samples corresponding to orassociated with a specific pool may be concurrently measured or analyzed by the molecular analysis module to obtain combined results from all reactions that associated with the specific pool. The combined results may then be separated, (i.e., demultiplexed), to identify results specific to individual protein / interaction species reactions. Thus, rather than conducting measurements of each potential reaction individually, a large number of reactions (e.g., at least 10, at least 100, at least 1000, at least 10,000, at least 100,000, at least 1,000,000) may be measured concurrently, thereby significantly reducing total measurement time and significantly increasing throughput.

[0355] The pooling configuration 4000 may be selected or determined according to one or more criteria. One potential criterion by which the proteins and interaction species may be grouped into pools may include ensuring that, between all of the selected reaction pools 4010, there exist pairings between all of the proteins and all of the interaction species - e.g., each protein is paired with each interaction species - in at least one of the reaction pools 4010.

[0356] Another potential criterion may be based on expected observable results of reactions between proteins and interaction species. The reaction pools may be determined such that the observable results of the reaction outputs in a given pool be differentiable by the molecular analysis module. As discussed above, methods described herein may be performed using proteins and / or interaction species that have not been labeled and are therefore, “label free.” Accordingly, determining whether or not a reaction between a protein and an interaction species has occurred may be performed based on direct measurement of physical or chemical characteristics of a reaction output sample. As used herein, “reaction output sample” refers to a physical sample of the reaction outputs between a protein and interaction species. The reaction output sample may include products or by-products of a reaction between the protein and the interaction species. The reaction output sample may also include the original protein and interaction species, for example, if no reaction occurred. As used herein, “direct” measurement refers to measurement of a specific physical, chemical, or other property of a reaction output sample. If no reaction has occurred, the expected observable results may be associated with the protein and the interaction species only. If a reaction has occurred, the expected observable results will differ and will include measurements associated with products or by-products of the reaction between the protein and the interaction species. Such measurements may differ depending on a type of molecular analysis module employed.

[0357] As used herein, a “fluid” is given its ordinary meaning, i.e., a liquid or a gas. A fluid cannot maintain a defined shape and will flow during an observable time frame to fill the container in which it is put. Thus, the fluid may have any suitable viscosity that permits flow. If two or more fluids are present, each fluid may be independently selected among essentially any fluids (liquids, gases, and the like) by those of ordinary skill in the art.

[0358] In embodiments, a potential criterion may be based on physicochemical properties of the selected proteins and interaction species. In such embodiments, such properties may be used for the prediction and / or estimation of expected observable results.

[0359] In an example, if a mass spectrometer is used as the molecular analysis module, the product of the reaction between the protein and the interaction species may have an expected molecular weight. In such an example, a reaction pool may be determined so as not to include proteins and interaction species that are expected to combine in a manner that produces different output products of similar molecular weights. Products of similar molecular weight, e.g., within a threshold of less than 5%, within less than 3%, within less than 1% of each other, may be difficult to differentiate via mass spectrometry. Thus, proteins and interaction species pairs expected to have similar molecular weights may be organized into different reaction pools 4010 to maintain differentiability among the observable results.

[0360] Some examples of observable results that may be differentiable via various analysis modules may include, molecular weights spectral characteristics, chromatographic behavior, ionization properties, chemical stability, chemical reactivity, and hydrophilicity and / or hydrophobicity. These examples are provided by way of example only and any observable, differentiable characteristic of a reaction product may be selected.

[0361] In embodiments, the pooling configuration 4000 may be obtained by the at least one processor (e.g., processor 222 of the multiplexer 220). Obtaining the pooling configuration 4000 may include retrieving the pooling configuration 4000 from a data storage unit, e.g., a computer memory, where it has been stored. In embodiments, obtaining the pooling configuration 4000 may further include generating the pooling configuration 4000 according to the criteria discussed above and throughout this disclosure.

[0362] In In an operation 3006, the method 3000 may include conducting individual reactions between the plurality of proteins and the at least one interaction species to generate a plurality of reaction output samples in the reaction chamber. The reaction chamber is configured forconducting individual reactions between the plurality of proteins and the at least one interaction species to generate a plurality of reaction output samples. In embodiments, the reaction chamber may include individual reaction vessels configured for conducting the individual reactions. In embodiments, the protein reservoir or the interaction species reservoir includes the reaction chamber. The reaction chamber may be included as part or all of the protein or interaction species reservoir. Conducting the individual reactions may be performed in separate individual reaction vessels and / or in combined reaction vessels. In embodiments, as discussed above, the reaction chamber may include a single individual reaction vessel.

[0363] In an embodiment, the method 3000 may include conducting, in individual reaction vessels of the reaction chamber, one of the individual reactions to generate the plurality of reaction output samples. A reaction chamber may include, for example, a multi-well plate configured to permit many different individual reactions to occur simultaneously. In an embodiment, each individual protein / interaction species pair of the pooling configuration may be reacted with one another in a separate individual reaction vessel of the reaction chamber (or reaction chambers, as need be). Each individual reaction produces a reaction output sample and the plurality of individual reactions produces a plurality of reaction output samples. Subsequent to the individual reactions, the operation 3006 may further include combining the plurality of reaction output samples into a plurality of combined reaction output samples according to the plurality of reaction pools. After the individual reactions are conducted, the reaction outputs from all of the individual reactions associated with a specific reaction pool may be combined into a single combined reaction output sample. This may be performed for each reaction pool according to the pooling configuration, thus resulting in a plurality of combined reaction output samples, where each of the combined reaction output samples corresponds to one of the reaction pools. Thus, each combined reaction output sample will contain the reactant products from all of the protein / interaction species pairs in the associated reaction pools. Not every protein / interaction species pair will produce reactant product - many combinations will produce no reaction. Each of the combined reaction output samples may then be measured, as discussed below.

[0364] In embodiments, the operation 3006 may include combining the plurality of proteins with the at least one interaction species in individual reaction vessels of the one or more reaction vessels according to the pooling configuration. In such an embodiment, individual reactionvessels (or, for example, the single reaction vessel of a non-compartmentalized reaction chamber) of a reaction chamber or chambers may each include more than one protein / interaction species pair. In embodiments, all protein / interaction species pairs of a given reaction pool 4010 may be combined and reacted in a single reaction vessel. In other embodiments, a portion of the protein / interaction species pairs of a given reaction pool 4010 may be combined and reacted in a single reaction vessel. If all protein / interaction species pairs of a given reaction pool 4010 are interacted in a single reaction vessel, the single reaction vessel may include the entire combined reaction output sample subsequent to the reaction. If only a portion of the protein / interaction species pairs of a given reaction pool 4010 are included in single reaction vessels, then, subsequent to the reaction, the reaction output samples may be combined into combined reaction output samples according to the pooling configuration 4000.

[0365] In embodiments, the operation 3006 may include steps for physically handling the protein and interaction species samples. Thus, the operation 3006 may include, providing, by the at least one processor to a sample handling system, control instructions to provide operative coupling between any combination of the protein reservoir, the interaction species reservoir, the reaction chamber, and the molecular analysis module. Operative coupling may include transfer of proteins, transfer of interaction species, transfer of reaction output samples, or any combination of these. The sample handling system, also described herein as a sample handling system 226, may provide automated or robotic sample handling to facilitate transfer of proteins and interaction species between their respective reservoirs and the reaction chamber or chambers. The sample handling system may be configured to combine the plurality of reaction output samples into a plurality of combined reaction output samples according to the plurality of reaction pools. The sample handling system may provide automated or robotic sample handling to facilitate combination of proteins and interaction species in the reaction chamber or chambers and / or to facilitate combination of the reaction output samples according to the pooling configuration 4000. The sampling handling system may further provide automated or robotic sample handling to facilitate transfer of the combined reaction output samples to the molecular analysis module 240. The sampling handling system may provide transfer via liquid handling and / or transfer via container handling.

[0366] In additional embodiments, operation 3006 may further include steps or processes related to adjusting reaction conditions in the reaction chamber by use of reaction components stored ina reaction components reservoir. As discussed above and throughout, a reaction components reservoir (e.g., reaction components reservoir 215) may be provided to supply reaction components as needed. Reaction components may be selected and provided to the reaction chamber to adjust reaction conditions as may be necessary for reacting the proteins and interaction species of a reaction pool 4000. Transfer and delivery of the reaction components may be facilitated, e.g., by the sample handling system.

[0367] In an operation 3008, the method 3000 may include measuring the plurality of reaction output samples. The molecular analysis module is configured to measure the plurality of reaction output samples, wherein measuring includes concurrent measurement of at least two reaction output samples of a reaction pool selected according to the pooling configuration. This may be achieved by operating the molecular analysis module on a combined reaction output sample.

[0368] The molecular analysis module may include concurrent measurement of any number of reaction output samples associated with a given reaction pool between a minimum of two and a maximum representing all of the reaction output samples in a combined reaction output sample associated with a reaction pool selected according to the pooling configuration. Measuring the plurality of reaction output samples may be performed concurrently, reaction pool by reaction pool, until each of the plurality of combined reaction output samples has been measured. In embodiments, this measurement of each reaction pool may be sequential, where one after another reaction pool is measured. In embodiments, where a molecular analysis module is capable of conducting more than one measurement at a time or the molecular analysis module includes more than one measurement device, all or some of the reaction pools may be measured concurrently with other reaction pools. In each measurement, all of the combined reaction output samples for a specific reaction pool may be measured. In embodiments, as discussed above, measurement may include direct measurement of at least one physicochemical property of the reaction outputs associated with the plurality of reaction output samples.

[0369] In embodiments, the molecular analysis module includes, by way of example, a mass spectrometer employing one or more techniques selected from the group consisting of: Matrix- Assisted Laser Desorption / Ionization Time-of-Flight (MALDLTOF), Electrospray Ionization Mass Spectrometry (ESLMS), Liquid Chromatography-Mass Spectrometry (LC-MS), Gas Chromatography-Mass Spectrometry (GC-MS), Inductively Coupled Plasma Mass Spectrometry(ICP-MS), Direct Injection Mass Spectrometry (DIMS), Ion Trap Mass Spectrometry and Secondary Ion Mass Spectrometry (SIMS).

[0370] In embodiments, in place of or in addition to a mass spectrometer, the molecular analysis module may include at least one device selected from the group including a spectrophotometer; a chromatography system; a Nuclear Magnetic Resonance (NMR) spectrometer; a fluorescence spectrometer; a Raman spectrometer; and a capillary electrophoresis system. Other suitable molecular analysis modules are discussed above and throughout.

[0371] In an operation 3010, the method 3000 may include demultiplexing the concurrent measurement to differentiate measurement results associated with each reaction output sample within the combined reaction output samples. As discussed above, concurrent measurements may be made of two or more reaction output samples associated with a specific reaction pool 4010. The reaction output samples of a given reaction pool 4010 may be measured concurrently, with separate concurrent measurements being made of each set of combined reaction samples associated with the different reaction pools 4010. The result of such measurements may require demultiplexing to separate out or obtain individual measurements that can be associated with the outputs of individual reactions between individual protein / interaction species pairs.

[0372] The individual measurements may include positive indications of reactions between the individual protein / interaction species pairs. A positive indication of reaction may include a measurement that corresponds with an expected observable result of a reaction between an individual protein and an individual interaction species. The individual measurements may include negative indications of reactions between the individual protein / interaction species pairs. A negative indication of reaction may include a measurement that lacks an expected observable result of a reaction between an individual protein and an individual interaction species.

[0373] Demultiplexing the concurrent measurement may include employing the at least one processor to identify both the positive and negative indications of reactions between the proteins and interaction species of a reaction pool 4010. Using the pooling configuration as a guide and comparing the concurrent measurement associated with a reaction pool 4010 to the expected observable results of the reaction pool 4010, the at least one processor may identify which proteins and which interaction species have reacted and which have not.

[0374] In an operation 3012, the method 3000 may include storing the individual measurements as demultiplexed pool measurement data in a protein reactions database. The individualmeasurement may include the positive and negative indications of reactions in each reaction pool 4010.EXAMPLES

[0375] The following examples are intended to illustrate certain embodiments described herein, including certain aspects of the present invention, but do not exemplify the full scope of the invention. The following specific and non-limiting examples may be representative of the systems, e.g., system 200, and methods, e.g., method 100 and method 3000, as described above. The following Examples are illustrative and do not limit the scope of the invention.Example 1. High-Throughput Profiling of Compounds against Enzymes Using Multiplexed Electrospray Ionization Mass Spectrometry (ESI-MS)

[0376] In this Example, a system, e.g., system 200, is provided for high-throughput screening of a diverse selection of enzymes against a vast library of potential inhibitor compounds. A protein reservoir includes, for example, 3,000 enzymes representing maximal diversity across Enzyme Commission (EC) classes. An interaction species reservoir includes a library of small molecules (“compound library”). A system according to embodiments herein selects, from the protein reservoir, a plurality of enzymes to be interacted with at least one compound, e.g., a plurality of compounds, from the compound library. The selected enzymes and compounds are combined in reaction pools, which are determined according to a pooling configuration for analysis by ESIMS as described herein.Selection of Enzymes for Protein ReservoirDiversity and Substrate Suitability

[0377] The system uses the UniProt database containing 269,008 reviewed entries to apply selection criteria. First, the system selects enzymes with EC class annotations. Next, the enzymes are filtered to retain only those with experimentally validated catalytic activity and known substrates documented in the BRENDA enzymes database (brenda-enzymes.org). Substrate suitability is assessed by targeting substrates with molecular weights between 100 to 1,500 Daltons (Da), commercial availability at less than about $20 / gram, stability in aqueous solution at about pH 6-8 for at least about 4 hours, and / or substrate-product mass differences of at least about 2 Da.Producibility and Reactivity

[0378] Next, the system applies producibility criteria to the enzymes to ensure successful expression in an automated protein production system using E. coli as expression host. Exclusion criteria include enzymes that are known or predicted to: be 100 kDa or larger in size, contain transmembrane domains (e.g., based on crystal structure and / or as predicted by a transmembrane prediction model), require post-translational modifications for activity such as glycosylation or lipidation, originate from anaerobic organisms, and / or contain more than 10 cysteine residues and / or other secondary structures that may complicate folding in the expression host. Further exclusion criteria removes enzymes that are known or predicted to: require non-readily available cofactors for expression and / or activity, require at least one additional protein (e.g., a further subunit of a multi-subunit protein complex) for expression and / or activity, and / or have known toxicity to the expression host.

[0379] Inclusion criteria within the protein reservoir provides preferential selection of enzymes that are known or predicted to have high reaction rates and / or originate from mesophilic organisms, particularly those from bacterial sources and / or previously demonstrated to express functionally in E. coli.Selection and Validation of Enzymes for Reaction Pool

[0380] Following the selection of enzymes for the protein reservoir, the system is configured to select a plurality of proteins from the protein reservoir to be interacted, e.g., to be included within reaction pools of the pooling configuration. This selection may include enzyme validation, as described below. The system performs clustering of the enzymes based on sequence similarity using Cluster Database at High Identity with Tolerance (CD-HIT) with an identity threshold of about 40%, ensuring selection of diverse representative enzymes. Within each EC class, representative enzymes are chosen from different clusters to advantageously maximize functional diversity while maintaining the ability to produce and assay all selected enzymes.

[0381] In one exemplary cluster, the enzymes include oxidoreductases, prioritizing those utilizing common cofactors such as NAD+ / NADH and FAD / FADH2; transferases, including kinases, aminotransferases, and glycosyltransferases; hydrolases, including proteases and phosphatases; lyases, including decarboxylases and aldolases; ligases; and combinations thereof.

[0382] Following the clustering, the system selects a plurality of enzymes for a validation pool by determining which enzymes may be combined for concurrent analysis while maintaining theability to demultiplex individual enzyme activities. As used herein, a “validation pool” may be selected according to a validation pooling configuration similar to that described above with respect to reaction pooling configurations. Validation pools may include a plurality of proteins and their corresponding known substrates. The system achieves this by first constructing a compatibility matrix for scoring enzyme pairs based on mass spectrometry compatibility, chromatographic separation potential, and / or chemical compatibility. Then, integer linear programming is employed to maximize the sum of compatibility scores while constraining the reaction pool to contain about 95 to about 105 enzymes. Optimization is performed with simulated annealing to escape local optima. Ultimately, up to 30 validation pools each containing enzymes with high compatibility are generated. Validation pool compositions are validated by simulating mass spectra to confirm that greater than 95% of substrate / product pairs could be uniquely identified.

[0383] The enzymes of each validation pool are produced using a protein production system including a fully automated platform integrating liquid handling robotics and microbioreactor. The enzymes may be produced in an expression host such as E. coll or in a cell-free transcription / translation system as described in the below examples. Gene fragments encoding each enzyme are cloned into expression vectors that optionally include purification tags such as N-terminal or C-terminal His6 or His8 tags. Following transformation into E. colt cells (for example, strain BL21(DE3)), cultures are grown at about 37°C to mid-log phase, then induced with 1 mM IPTG at about 18°C for about 16 hours. Automated purification, e g., of enzymes with His6 or His8 tags, utilizes Ni-NTA affinity chromatography in 96-well format. All liquid handling steps may be performed robotically with user intervention as appropriate. Protein concentration and / or purity are assessed using gel electrophoresis. Proteins are stored at 10 pM concentration in a storage buffer, e.g., 20 mM HEPES pH 7.5, 150 mM NaCl, 1 mM DTT, and 20% glycerol, then flash frozen.

[0384] The enzymes of each validation pool are tested individually without inhibitors to confirm activity under screening conditions. Reactions are assembled in 384-well plates with each enzyme at 500 nM final concentration, its corresponding substrate at 100 pM, and appropriate cofactors and buffers.

[0385] Reactions are allowed to proceed at about 37°C for about 60 minutes before being quenched and pooled for analysis. Enzymes with confirmed activity are considered validated enzymes to be included in reaction pools of the pooling configuration.Compound Library

[0386] A small molecule library (e.g., interaction species reservoir), e.g., of 25,000 compounds, is obtained with each compound as a 10 mM stock in DMSO. The library is advantageously designed to maximize chemical diversity while maintaining molecular weights ranging from 200-600 Da and drug-like physicochemical properties. Working plates are prepared, e.g., by transferring compounds to 384-well plates using acoustic dispensing technology and stored at about -20°C under nitrogen atmosphere.

[0387] The system selects at least one interaction species, e.g., a plurality of interaction species, from the interaction species reservoir to be interacted. The system selects appropriate compounds / species to be included in the reaction pools of the pooling configuration. The selection criteria may be based, e.g., on compatibility of the compounds with the enzymes selected from the validation pools. In some cases, each enzyme in the reaction pool reacts with all compounds of the small molecule library in the pooling configuration.Screening / Reaction WorkflowScreening Stage

[0388] Individual reactions between the plurality of sei ected / vali dated enzymes and the plurality of selected interaction species are conducted. Validated enzymes from each validation pool are allowed to proceed to compound screening, in which each enzyme is tested individually against each compound at a concentration of 10 pM in individual reaction vessels. The enzymes and compounds may be pre-incubated for an appropriate time, e.g., about 15 minutes, prior to substrate addition and reaction initiation.Reaction Pooling

[0389] The individual reactions are strategically combined into a reaction pool according to a pooling configuration in order to allow multiplexed measurements of each reaction pool and decrease the number of required individual measurements for the reaction products (i.e., reaction output samples). The combining may be conducted prior to initiating the individual reactions, during the reactions, or after termination of the reactions. The combining is based on one or more of the following observable criteria of the expected reactant products in each reaction pool: (i)molecular weight; (ii) spectral characteristics; (iii) chromatographic behavior; (iv) ionization properties; (iv) chemical stability; (v) chemical reactivity; and (vi) hydrophilicity and / or hydrophobicity, thereby ensuring that the reaction substrates and products from all constituent enzyme reactions in each reaction pool are distinguishable For analysis by electrospray ionization mass spectrometry (ESI-MS), the multiplexing criteria include mass (ionization property) and chromatographic retention time of the expected reaction products.

[0390] Based on the above multiplexing scheme, approximately 100 individual enzyme reactions may be combined into a reaction pool for analysis and / or measurement of their reaction products by a molecular analysis module. The reactions are combined, for example, using an automated sample handling system that transfers specific volumes from individual reaction vessels into the reaction pool.

[0391] The reactions of each reaction pool are quenched, e.g., with cold acetonitrile containing 0.1% formic acid, and analyzed by LC-MS. Chromatographic separation is performed with, for example, a C18 column with a rapid 2-minute gradient from 5% to 95% acetonitrile. Measuring the plurality of reaction output samples of all of the reaction output samples of a reaction pool selected according to the pooling configuration is conducted. An electrospray ionization mass spectrometer is operated in polarity switching mode to collect full scan data from m / z 100-2000. This analytical approach advantageously enables detection and quantification of substrates and products from all enzymes within each reaction pool in a single analysis.Data Demultiplexing and Analysis

[0392] The mass spectrometry data from the reaction pool is then processed for demultiplexing. The system first performs peak detection across all acquired chromatograms, identifying features based on accurate mass (e.g., within 5 ppm), retention time, and / or signal intensity thresholds. For each detected feature, the demultiplexer generates extracted ion chromatograms and / or integrated peak areas using Gaussian peak fitting.

[0393] The system then assigns each detected mass to its corresponding enzyme reaction using a lookup table to match expected substrate and product m / z values to detected features within defined retention time windows. When multiple potential assignments exist for a single feature, the system uses a probabilistic scoring system considering factors including, but not limited to, predicted ionization efficiency based on molecular structure, historical retention time data frompure compound standards, expected reaction conversion rates from validation experiments, ion suppression effects calculated from co-eluting species, or combinations thereof.

[0394] Quality metrics, including mass accuracy, retention time deviation from predicted values, peak shape correlation coefficients, or combinations thereof, are calculated for each assignment. Assignments with quality scores below threshold values are flagged for manual review and / or excluded from further analysis. Background noise is subtracted from the data by using multiplexed control samples lacking enzymes, accounting for non-enzymatic substrate degradation and chemical noise.Inhibitor Identification

[0395] The system then determines, based on the demultiplexed mass spectrometry data, which compounds are inhibitors for which enzymes in each reaction pool. A compound is considered an inhibitor if it shows greater than 50% inhibition of enzyme activity. Inhibitors are confirmed, e.g., by retesting in a separate single enzyme activity assay.Example 2. High-Throughout Quantitative Substrate Profiling of Enzymes with Predictable Mass Changes Using Multiplexed Mass Spectrometry Analysis

[0396] In this Example, a system, e.g., system 200, is provided for assessing enzymes against a wide variety of potential substrates in a high-throughput manner while maintaining quantitative accuracy for determining kinetic parameters of the enzymes. A protein reservoir includes enzymes that catalyze reactions producing predictable mass changes in their substrates. An interaction species reservoir includes a library of substrates. A system according to embodiments herein selects, from the protein reservoir, a plurality of enzymes to be interacted with at least one substrate from the substrate library. The selected enzymes and substrates are combined in reaction pools, which are determined according to a pooling configuration for analysis by mass spectrometry, e.g., Q-TOF mass spectrometry as described herein.Selection of EnzymesSelection and Production of Enzymes for Protein Reservoir

[0397] Enzymes of the protein reservoir are known or predicted to catalyze reactions producing predictable mass changes in their substrates and include, but are not limited to, hydrolases such as nitrilases (converting R-CN to R-COOH, +19 Da); esterases (cleaving esters to acids and alcohols with a corresponding mass decrease); phosphatases (removing phosphate groups, -80 Da); peptidases (cleaving peptide bonds with predictable fragmentation patterns);oxidoreductases including oxidases (adding oxygen, +16 Da per oxygen); dehydrogenases (removing or adding H2, ±2 Da); halogenases and dehalogenases (adding or removing halogens, ±35 Da for Cl, ±80 Da for Br); methyltransferases (adding methyl groups, +14 Da); and acetyltransferases (adding acetyl groups, +42 Da).

[0398] The enzymes are identified via sequences from metagenomic databases, structural genomics databases, and / or curated enzyme databases. The selection criteria for inclusion of enzymes in the protein reservoir include one or more of the following known and / or predicted features: sequence diversity to ensure broad substrate specificity coverage (which may be selected by clustering algorithms to select representative enzymes from different subfamilies, ensuring coverage of enzymes across a wide range of substrate classes); sequence homology to known enzymes of interest; stability based on structural features; absence of transmembrane domains and / or post-translational modifications; molecular weight between 25-80 kDa; and activity on at least one substrate. Additional selection criteria for inclusion in the protein reservoir include known and / or predicted and properties, such as enzyme stability at room temperature for at least 2 hours, activity in aqueous buffers between pH 6-9, lack of requirement for complex or expensive cofactors, and / or suitability for expression in a protein production system.

[0399] Enzymes are produced using a cell-free transcription / translation system, or using an expression host such as E. coli as described in the above example. In a cell-free system, the enzymes produced may be purified or used directly for activity screening without purification, advantageously reducing processing time and cost. Gene fragments encoding each enzyme are synthesized with appropriate regulatory elements including a promoter (e.g., T7 promoter), ribosome binding site, and / or affinity and purification tags (e.g. N-terminal or C-terminal His6 or His8 tags). These gene fragments are added directly to commercial or custom cell-free expression systems according to manufacturer’s instructions (for example, at 5-50 nM concentration). The cell-free expression system contains the required mixture of components for protein production, for example, E. coli S30 extract, T7 RNA polymerase, amino acids, nucleotides, energy regeneration components such as phosphoenol pyruvate and pyruvate kinase, and / or appropriate salts and buffers. Expression reactions are conducted in 96-well or 384-well formats at 30°C for 4-16 hours with gentle shaking. The enzyme expression products are purified or used directly in the screening / reaction workflow as described below.Selection and Validation of Enzymes for Reaction Pool

[0400] The system selects a plurality of enzymes from the protein reservoir to be interacted. The system selects appropriate enzymes to be included in the reaction pools of the pooling configuration.

[0401] Each selected enzyme is tested with a small set of known substrates to confirm activity. Reactions are assembled in 384-well or 1536-well plates with enzyme concentrations ranging from 10 nM to 10 pM, substrate concentrations from 10 pM to 1 mM, and appropriate buffers and cofactors.Selection of Substrates for Interaction Species Reservoir

[0402] Interaction species reservoirs, i.e., libraries of diverse compounds representing potential substrates (“substrate library”) for each enzyme class, are compiled by the system. For nitrilases, the substrate library includes various nitriles ranging from 100-800 Da, such as aliphatic (e.g., C2 to C20) nitriles, aromatic nitriles (e.g., benzonitriles and derivatives thereof with various substitution patterns), and heterocyclic nitriles (e.g., pyridine and thiophene derivatives), and a- aminonitriles. For esterases, the substrate library contains diverse ester substrates including methyl and ethyl esters of various carboxylic acids, acetate esters, benzoate esters, phosphate esters, lactones of different ring sizes, and thioesters. For phosphatases, the substrate library includes phosphorylated amino acids, nucleotides, and synthetic phosphate-containing compounds. Compounds are provided as 10-100 mM stocks in DMSO or aqueous buffers as appropriate for their solubility properties.

[0403] The system selects at least one interaction species, e.g., a plurality of interaction species, from the interaction species reservoir to be interacted with the selected enzymes. The system selects appropriate compound species to be included in the reaction pools of the pooling configuration.Screening / Reaction Workflow Screenins Stage

[0404] Individual reactions between the plurality of sei ected / vali dated enzymes and the plurality of selected interaction species (substrates) are conducted. Each validated enzyme is tested individually against each selected substrate. The system strategically combines reactions into reaction pools for multiplexing of reactions and reaction product analysis according to a pooling configuration. The system advantageously selects substrate sets in which each substrate-productpair within a reaction pool can be uniquely identified by mass spectrometry. In an example, such selection is based on mass difference, e.g., a greater than 2 Da mass difference, between substrate and product. In another example, such selection is based substrate and product having distinct chromatographic and / or ionization properties. Reactions are conducted at temperatures ranging from 25°C to 45°C for time periods from 5 minutes to 24 hours. The appropriate reaction conditions may be selected according to known or predicted enzyme kinetics.

[0405] The screening workflow may be performed in 1536-well plates to maximize throughput. Each reaction vessel contains 5 pL total reaction volume including 1 pL of the cell-free expression product (enzyme), substrate at 200 pM final concentration, reaction buffer (e.g., 50 mM HEPES pH 7.5, 100 mM NaCl, and optionally 1 mM DTT). The plate layout is designed such that each enzyme is tested against each substrate across the full plate set, with no-enzyme and no-substrate control wells distributed throughout the plate.

[0406] Reactions are terminated by adding a broad-specificity protease, e.g., proteinase K, pronase, or thermolysin at final concentrations of about 0.1-1 mg / mL. The protease addition rapidly degrades all enzymes in the reaction mixture, immediately stopping catalytic activity while leaving small molecule substrates and products intact. This termination method advantageously avoids the use of organic solvents or extreme pH conditions that may affect ionization efficiency or cause degradation of sensitive compounds. The protease treatment is performed at about 37°C for about 10 to 30 minutes.Reaction Pooling

[0407] The individual reactions are strategically combined into reaction pools according to a pooling configuration to allow a multiplexed measurement of the reaction products (i.e., reaction output samples) in each reaction pool. The combining may be conducted prior to initiating the individual reactions, during the reactions, or after termination of the reactions. The combining is based on whether the expected reaction products in each reaction pool are distinguishable, e.g., by mass difference, distinct chromatographic properties, and / or ionization properties of the substrates and reaction products as describe above. The reaction products are combined, for example, using an automated sample handling system. Each reaction pool may include, for example, the reaction products from about 50 to about 1000, or about 75 to about 900, or about 100 to about 750, or about 150 to about 600, or about 200 to about 500, or about 300 to about 400 individual enzyme reactions.

[0408] The reaction products of each reaction pool are measured by a molecular analysis module, e.g., Quadrupole Time-of-Flight (Q-TOF) mass spectrometry coupled with liquid chromatography. The high mass resolution capability of Q-TOF configuration advantageously enables discrimination between products with similar masses that may be present in the reaction pools. In an example, when analyzing pools containing about 200 to about 500 enzyme reactions, the system employing Q-TOF is capable of readily distinguishing products differing by as little as 0.05 Da. Such a resolution may not be achievable with lower-resolution instruments. Further, the accuracy of Q-TOF in identifying molecular formulas and distinguishing between potential isobaric species is advantageous for analyzing diverse enzyme classes where unexpected side reactions or partial substrate conversions may occur. The wide dynamic range of Q-TOF may further accommodate the simultaneous detection of high-abundance unreacted substrates and low-abundance products from enzymes with poor catalytic efficiency.

[0409] The molecular analysis module may further include chromatographic separation. Chromatographic separation may employ reverse-phase Cl 8 or C8 columns with gradients optimized for the specific substrate / product classes. For example, analysis of nitrile / carboxylic acid pairs may use a gradient from 2% to 95% acetonitrile with 0.1% formic acid over 5-10 minutes, with the Q-TOF operating in full scan mode from m / z 50-2000, with data acquisition rates of 10-20 spectra per second to ensure adequate sampling across chromatographic peaks. When structural confirmation is required, the quadrupole may be used to isolate specific m / z values for collision-induced dissociation in the collision cell, with the resulting fragments analyzed by the TOF analyzer. This MS / MS capability is useful for distinguishing positional isomers or confirming unexpected reaction products.Data Demultiplexins and Analysis

[0410] The high-resolution Q-TOF mass data from each reaction pool is processed to improve demultiplexing accuracy. First, the system performs peak detection and integration across all chromatograms, using narrow mass extraction windows (±2-3 ppm) enabled by the Q-TOF’s resolution. For each detected feature, the demultiplexer calculates the exact mass and compares to theoretical masses of all possible substrates and products in the reaction pool.

[0411] Enzyme activity is quantified by calculating substrate depletion and / or product formation. The system advantageously further calculates specific activity values for each enzyme-substrate combination, generating a comprehensive quantitative substrate specificity profile. Enzymesshowing activity with multiple substrates are flagged as promiscuous, while those with narrow substrate ranges are identified as highly specific. This comprehensive profiling data is stored in a database for downstream applications (e.g. enzyme engineering, biocatalyst selection for synthetic chemistry, metabolic pathway characterization, and / or drug metabolism prediction).

[0412] Quality control measures include, but are not limited to: running control pools including samples of known enzyme-substrate pairs to validate deconvolution accuracy; incorporating isotopically labeled standards to confirm mass assignments; and / or performing replicate measurements to assess reproducibility.Example 3. High-Throughput Discovery of Protein Modulators Using Multiplexed Mass Spectrometry Analysis

[0413] In this Example, a system, e.g., system 200, is provided for high-throughput screening of protein modulators. A protein reservoir includes, for example, enzymes are known or predicted to exhibit low basal activity but may be activated through protein-protein interactions with modulators. An interaction species reservoir includes, for example, a library of potential protein modulators (“modulator library”). A system according to embodiments herein selects, from the protein reservoir, a plurality of enzymes to be interacted with at least one protein modulator, e.g., a plurality of protein modulators, from the modulator library. The interaction, i.e., reaction, is conducted in a reaction chamber such as a microcapsule system. The selected enzymes and protein modulators are combined in reaction pools, which are determined according to a pooling configuration for analysis by mass spectrometry as described herein.Selection of Enzymes for Protein Reservoir

[0414] The system selects enzymes that are known or predicted to exhibit low basal activity but may be activated through protein-protein interactions with modulators. These enzymes include, but are not limited to, kinases requiring regulatory subunits, dehydrogenases activated by allosteric binding partners, synthases regulated by protein cofactors, proteases requiring activation by removal of inhibitory domains, and / or metabolic enzymes subject to protein-based regulation. The system may preferentially select, for inclusion into the protein reservoir, enzymes where activation results in easily detectable mass changes, such as phosphorylation (+80 Da), methylation (+14 Da), acetylation (+42 Da), dehydrogenation (±2 Da), and / or hydrolysis or cleavage reactions with predictable mass shifts.Modulator Library

[0415] A modulator library (e.g., interaction species reservoir) includes potential protein modulators that activate the enzymes of the protein reservoir. The protein modulators include, for example, known or putative proteins or peptides from databases (e.g., containing known regulatory domains) and / or metagenomic sequencing, computationally designed proteins and variants thereof, fragments of known protein interaction partners, synthetic coiled-coil motifs, antibodies, antibody fragments and / or nanobodies, and / or random, mutagenized and / or evolved peptide and / or protein libraries.

[0416] The system selects at least one protein modulator, e.g., a plurality of modulators, to interact with selected enzymes in a reaction pool determined according to a pooling configuration described herein.Production of Enzymes and Protein Modulators

[0417] The system selects, from the protein reservoir, enzymes to be interacted with selected protein modulators from the modulator library (interaction species reservoir). Each modulator of the modulator library may be encoded on the same vector or plasmid as the enzyme with which it may interact (“target enzyme”). The enzyme and modulator pair on the vector may be separated or flanked by appropriate genetic elements for properties such as independent expression and / or cell export.

[0418] A library of vectors encoding the selected enzyme and modulator pairs is constructed, e.g., by assembling barcoded expression vectors, wherein each vector contains a unique DNA barcode sequence (e.g. a 20-30 nucleotide sequence), a constitutive or inducible promoter driving expression of one target enzyme, a second promoter driving expression of one potential protein modulator, antibiotic resistance markers for selection, and / or origin of replication compatible with the chosen host organism. The library may be constructed using combinatorial cloning methods to generate tens to trillions of unique enzyme-modulator combinations.

[0419] The vectors are configured for protein production in a microcapsule system, which employs polymer-based capsules with controllable permeability. The microcapsules may be, e.g., alginate-poly-L-lysine-alginate microcapsules, agarose microspheres with thermoreversible gelation properties, polyacrylamide capsules with defined pore sizes, and / or synthetic polymer capsules with pH-responsive permeability. The microcapsules have diameters ranging from 50-500 pm, which advantageous provide sufficient internal volume for protein expression while maintaining structural integrity during manipulation.

[0420] The permeability of the microcapsules are controlled by a permeabilization control system utilizing reversible pore-forming mechanisms. For example, the microcapsules may incorporate temperature-sensitive polymers that undergo phase transitions at specific temperatures, allowing controlled entry of molecules below certain size thresholds. For example, at 4°C, the microcapsules may be impermeable to proteins but permeable to small molecules under 1 kDa, while at 37°C they may allow passage of molecules up to 10 kDa. This permeabilization may be reversed by returning to the original temperature.

[0421] The encapsulation process is performed manually using standard pipetting equipment or by using automated liquid handling systems. Single bacterial or archaeal cells (e.g. E. coif) and / or eukaryotic cells (such as S. cerevisiae, H. sapiens, or other mammalian cells and / or insect cells), are transformed with the vector library and encapsulated at limiting dilution to achieve, primarily, single cells per capsule. The encapsulation may be performed using, for example, a flow-focusing microfluidic device operated manually, emulsification using controlled stirring speeds, and / or electrostatic droplet generation.

[0422] For expression of the enzymes and protein modulators, the encapsulated cells, are cultured under conditions promoting protein expression. For bacterial systems, this may include growth at 25°C followed by induction at 18°C for 6 hours. For yeast systems, this may include growth at 30°C with appropriate induction conditions. The microcapsules may maintain cell confinement while allowing nutrient and oxygen exchange.

[0423] Following expression, a permeabilization step may introduce cell lysis reagents. The microcapsules are transferred to a lysis buffer that may include, for example, a lysis agent including lysozyme at 1 mg / mL, DNase I at 10 pg / mL, protease inhibitors, and / or mild detergents compatible with enzyme activity. The permeabilization conditions may allow these components to enter while retaining expressed proteins (including both the target enzyme and protein modulator) within the microcapsules. Lysis may proceed for 30-60 minutes at room temperature with gentle agitation.Screening / Reaction Workflow

[0424] The system measures the activity of the enzyme within the microcapsule to assess the ability of the protein modulator to activate the enzyme (i .e., the interaction between the targetenzyme and protein modulator). The microcapsule therefore serves as both the protein production system and the reaction chamber.

[0425] To measure enzyme activity, the enzyme substrate is introduced to the microcapsule, e.g., by a second permeabilization step. The microcapsules are washed and transferred to a reaction buffer containing appropriate substrates for the enzymes at, for example, 100-1000 pM concentration, cofactors such as ATP, NAD+, or metal ions, pH buffering components, and / or stabilizing agents. The permeabilization may be controlled such that substrates enter freely while the proteins (including both the target enzyme and protein modulator) remain compartmentalized. Reactions may proceed at optimal temperatures for 1-24 hours depending on enzyme kinetics to produce a reaction product (i.e., reaction output sample) for each microcapsule.Reaction Pooling

[0426] The system strategically combines microcapsules containing unique pairs of enzymeprotein modulator into reaction pools for multiplexing of reactions and / or reaction product analysis. The system advantageously selects microcapsules in which the reaction products within a reaction pool can be uniquely identified by mass spectrometry. For example, reaction vessels containing enzymes producing products with m / z values of 300, 500, 700, and 900 may be pooled together as these products can be easily distinguished by mass spectrometry. Each reaction pool may contain microcapsules from 10-100 different wells, with each well containing approximately 10,000-100,000 microcapsules representing 5-10 different enzymes and 1,000 different activators per enzyme.

[0427] Following the combination into reaction pools, the microcapsules are disrupted to release their contents. The disruption may be, e.g., mechanical disruption using bead beating or sonication, chemical dissolution using capsule-specific solvents, and / or enzymatic degradation of capsule polymers. The released contents may be clarified by centrifugation and / or filtration before analysis.Data Demultiplexing and Analysis

[0428] A molecular analysis module measures the reaction products (i.e., reaction output samples) from each reaction pool. The reaction products may be rapidly screened by MALDI- TOF mass spectrometry. MALDI-TOF may be advantageous due to its high throughput capabilities, tolerance of complex biological matrices, ability to detect a wide mass rangesimultaneously, and / or minimal sample preparation requirements. Matrices optimized for small molecule detection, such as a-cyano-4-hydroxycinnamic acid or 2,5-dihydroxybenzoic acid, may be used. Each pool of reaction products may be spotted in replicate on MALDI target plates and analyzed in positive and / or negative ion modes.

[0429] Mass spectra is collected focusing on the expected product masses. The presence of specific product ions indicates successful enzyme activation within the reaction pool. For example, detection of a phosphorylated peptide at m / z 580 may indicate activation of a kinase that phosphorylates a peptide substrate with mass 500 Da. The intensity of product peaks relative to substrate peaks provides semi -quantitative information regarding activation efficiency of the protein modulator for the enzyme.

[0430] Following demultiplexing and analysis, the reaction pools may be identified by barcode sequencing of the vector that produced the enzyme-modulator pairs. The barcode sequencing may involve, for example, individually sorting the microcapsules from the identified reaction pools using flow cytometry, micromanipulation, and / or dilution plating; extracting DNA from the sorted microcapsules, and amplifying the barcode regions by PCR using universal primers flanking the barcode sequence. High-throughput sequencing identifies the specific enzymemodulator pairs responsible for the observed activity. Amplified sequences may be recloned and / or modified (e.g. via directed evolution) for confirmatory testing and / or optimization.

[0431] The system may be further used for assessing cell-based signaling. For example, the system may encapsulate pairs of sender and receiver cells. Sender cells may express different signaling molecules such as cytokines, growth factors, or synthetic signaling proteins. Receiver cells may express corresponding receptors linked to reporter enzymes that produce detectable mass changes upon activation. The compartmentalization in microcapsules may advantageously prevent cross-talk between different sender-receiver pairs while allowing quantitative measurement of signaling efficiency through MS detection of reporter products.

[0432] Quality control measures may include, but are not limited to, running control capsules with known enzyme-activator pairs to validate the system, incorporating “dead” capsules lacking cells to assess background, using capsules with constitutively active enzyme variants as positive controls, and / or performing replicate experiments to assess reproducibility.Example 4. High-Throughput Multiplexed Cell-Based Screening of Cell Signaling Pathway Modulators Using Enzyme-Coupled Mass Spectrometry

[0433] In this Example, a system, e.g., system 200, is provided for high-throughput screening of cell signaling pathway modulators using enzyme-coupled detection. A protein reservoir includes, for example, known or predicted proteins involved in diverse cell signaling pathways (“signaling proteins”). An interaction species reservoir includes, for example, a library of potential modulator compounds (“compound library”). A system according to embodiments herein selects, from the protein reservoir, a plurality of signaling proteins to be interacted with at least one modulator, e.g., a plurality of modulators, from the compound library. The signaling proteins may be linked reporter enzymes, such that inhibition or activation of a signaling pathway leads to reporter activation. The selected signaling proteins and modulators are combined in reaction pools, which are determined according to a pooling configuration for analysis by mass spectrometry as described herein.Selection, Production, and Validation of Signaling Proteins for Protein Reservoir

[0434] The system selects signaling proteins involved in, for example, G-protein coupled receptor (GPCR) pathways, receptor tyrosine kinase (RTK) pathways, nuclear receptor signaling, cytokine receptor pathways, and / or synthetic orthogonal signaling systems. For each pathway, cell lines are engineered in which pathway activation leads to expression of a specific reporter enzyme. The coupling between the signaling protein and reporter enzyme may be achieved through, for example, response element-driven promoters (e.g., CRE, SRE, NFAT-RE), CRISPR- based transcriptional activation systems, synthetic transcription factors activated by signaling cascades, and / or degron-based systems where signaling controls enzyme stability.

[0435] The system selects reporter enzymes that produce unique, easily detectable mass changes from a common substrate library. Such enzymes include, but are not limited to, methyltransferases specific for different positions on aromatic rings, halogenases introducing different halogens, glycosyltransferases adding different sugar moieties, acyltransferases with different acyl-CoA specificities, and / or oxidases creating different oxidation products.

[0436] The signaling proteins are expressed in engineered stable cell lines, with each cell line expressing a unique signaling protein linked to a specific reporter enzyme. In one example, various HEK293 cell lines are generated: a first cell line expressing GPCR-A (signaling protein) linked to methyltransferase- 1 (reporter enzyme), a second cell line expressing RTK-B (signalingprotein) linked to chlorinase-2 (reporter enzyme), a third cell line expressing GPCR-C (signaling protein) linked to glycosyltransferase-3 (reporter enzyme), and a fourth cell line expressing endogenous receptor-D (signaling protein) linked to bromoperoxidase-4 (reporter enzyme).

[0437] The reporter enzyme is configured to be expressed in the cytoplasm and / or extracellularly. The reporter enzyme is linked to the signaling pathway such that inhibition or activation of the pathway leads to reporter activation. Each cell line may be validated for appropriate receptor expression levels, minimal basal enzyme expression, and / or robust enzyme induction upon pathway activation.

[0438] A library of substrates for the reporter enzymes (“substrate library”) includes compounds capable of being modified by all reporter enzymes while producing distinguishable products. For example, the substrate library may include polyhydroxylated aromatic compounds amenable to methylation, halogenation, and glycosylation, peptides with multiple modification sites, synthetic scaffolds with reactive handles, and / or natural product-like structures. Substrates may be selected such that each reporter enzyme depletes a reactant and / or produces a product with a unique m / z value and / or retention time combination. The substrate library may contain two or more different substrates at, for example 50-500 pM each, dissolved in cell culture medium or a buffer.

[0439] A generic reporter system is optionally incorporated into the engineered cell lines for real-time monitoring. The generic reporter system is responsive to general signaling activation. This may include, for example, a pan-pathway fluorescent, luminescent, and / or chemogenic reporter. The generic reporter may be, for example, a luciferase activated by common secondary messengers (cAMP, Ca2+, MAPK), or a pathway driven expression cassette containing an alkaline phosphatase. This dual-reporter system advantageously allows rapid identification of active wells by the generic reporter system, while the reporter enzyme system provides pathway specificity.

[0440] The selected cell lines may be cultured in a multiplexed manner. For example, multiple cell lines may be seeded in each well of 384-well or 1536-well plates. Each well may contain about 2,000 to about 5,000 cells each of the selected cell lines, e.g., two or more different cell lines. The cell lines to be included in each well are selected to have similar growth rates and minimal or no cross-interference. The cell lines may be cultured for 24-48 hours to allow proper attachment and expression of the signaling proteins.Modulator Library

[0441] A modulator library (e.g., interaction species reservoir) includes potential modulator compounds that activate the signaling proteins of the protein reservoir. The modulator compounds may include protein and / or peptide-based compounds and small molecules. The system selects at least one modulator, e.g., a plurality of modulators, to interact with selected signaling proteins in a reaction pool determined according to a pooling configuration described herein.Screening / Reaction Workflow

[0442] The system selects cell lines expressing signaling proteins of the protein reservoir to be interacted with selected modulators from the modulator library (interaction species reservoir). The selected modulators are added, e.g., at concentrations of about 1 nM to about 100 pM, to reaction vessels containing each cell culture, e.g., the multiplexed cell culture plates as described above. The plates may be incubated at 37°C with 5% CO2 for 2-24 hours depending on the kinetics of enzyme induction. For real-time monitoring, luminescence or fluorescence measurements may be taken at regular intervals (e.g., every 30 minutes) using an automated plate reader. Wells showing activity above threshold may be flagged for differential processing.

[0443] Following the signaling period, the substrate library is added to all reaction vessels. Substrate addition may occur after the lysis and / or removal of cells and / or after removal of cellular debris via filtration and / or centrifugation. After the addition of substrate, reactions of the reporter enzymes may proceed for about 1-12 hours at about 37°C. For compounds showing selective activation in the real-time assay, parallel wells may be set up with individual substrates to confirm specificity.Reaction Pooling

[0444] Based on the real-time monitoring results, the system strategically combines the reactions (e.g., supernatants of the cultured cell lines) in the reaction vessels (e.g., wells) into reaction pools for multiplexing. For example, highly active wells may be pooled separately from moderately active wells to optimize dynamic range in mass spectrometry (MS) detection. In another example, wells may be pooled based on the expected enzyme products to maximize MS resolution. The system selects the reaction pools ensuring that all potential reaction products (reaction output samples) in a reaction pool can be distinguished. Each reaction pool may contain samples from one or more wells.Data Demultiplexing and Analysis

[0445] The reaction products from each reaction pool are prepared for analysis, which may involve, for example, removing cellular debris by centrifugation or filtration, adding internal standards for quantification, and / or protein precipitation with, for example, acetonitrile. The reaction products from each reaction pool are analyzed by a molecular analysis module, e.g., LC- MS or spectrophotometric methods, using suitable methods for the specific substrate / product combinations.

[0446] The system demultiplexes the reaction products from each reaction pool, e.g., by first identifying which enzyme products are present in each pool, then correlating product presence with specific signaling pathways based on the enzyme-pathway coupling, then quantifying relative pathway activation by product abundance. The system may calculate selectivity indices for each compound by comparing activation across different pathways.

[0447] The system may also employ active learning approaches. The system may use initial screening data to create models predicting compound selectivity based on chemical structure. The models may suggest structural modifications likely to enhance selectivity for specific pathways. Modified compounds may be synthesized and tested, with results fed back to refine the models. This iterative process may advantageously converge on highly selective agonists or antagonists for individual signaling pathways.

[0448] Quality control measures may include, for example, testing known selective agonists / antagonists to validate the system, using pathway-dead cell lines as negative controls, confirming results with traditional single-pathway assays, and / or performing dose-response curves.Example 5. High-Throughput Profiling of Compounds against Enzymes Using Microfluidic Droplet Compartmentalization with Full-Spectrum UV-Visible Spectrophotometric Analysis

[0449] In this Example, a system, e.g., system 200, is provided for high-throughput screening of a diverse selection of enzymes against a vast library of potential inhibitor compounds. A protein reservoir includes, for example, enzymes that are known or predicted to produce chromogenic and / or UV-active products. An interaction species reservoir includes, for example, a library of small molecules (“compound library”). A system according to embodiments herein selects, from the protein reservoir, a plurality of enzymes to be interacted with at least one compound, e.g., aplurality of compounds, from the compound library. The selected enzymes and compounds are combined in reaction pools, which are determined according to a pooling configuration for UV- visible spectrophotometric analysis as described herein. The system is capable of identifying specific enzyme inhibition profiles by the inhibitors of the compound library.Selection of EnzymesSelection of Enzymes for Protein Reservoir

[0450] The system selects enzymes that are known or predicted to act on substrates to produce chromogenic and / or UV-active products, i.e., compounds with distinct spectral signatures across the UV-visible spectrum (about 200-800 nm). The enzymes include, but are not limited to, peroxidases that oxidize different chromogenic substrates, laccases that produce colored quinones from phenolic compounds, cytochrome P450s that generate UV-absorbing metabolites, nitrilases that produce UV-active aromatic acids, esterases that release chromophoric leaving groups, dehydrogenases coupled to colorimetric redox indicators, phosphatases that release chromogenic products, dehydrogenases utilizing NAD+ / NADH (340 nm absorption change), oxidases producing hydrogen peroxide detectable via coupled reactions, kinases using ATP with coupled detection systems, proteases cleaving peptides with chromogenic leaving groups, transaminases with UV-active substrates and products, and / or glycosidases releasing chromophoric aglycones.Selection of Enzymes for Reaction Pool

[0451] Following selection of the selection of enzymes for the protein reservoir, the system is configured to select a plurality of enzymes from the protein reservoir to be interacted, e.g., to be included within reaction pools of the pooling configuration. The system advantageously selects enzymes for the reaction pool that produce products with distinct spectral characteristics detectable by UV-visible spectrophotometric analysis, including, for example: peak maxima wavelength; distinctive spectral shapes; characteristic shoulder patterns; specific absorbance ratios at multiple wavelengths; and / or unique spectral fine structure.

[0452] The system may also select enzymes for the reaction pool based on a distinct spectral output from the combination of their expected products, such that the reaction pool contains a unique multi-dimensional spectral fingerprint. In one example, a reaction pool contains peroxidases (generating products absorbing at 450 nm with characteristic shoulders), alkalinephosphatases (generating products with broad absorbance centered at 405 nm), and laccases (generating products with complex spectra from 300-600 nm).

[0453] For analysis by a microfluidic molecular analysis module, the selected enzymes for each reaction pool are encapsulated into a microfluidic droplet (“enzyme droplets”). The enzyme droplets may be generated, e.g., from flow-focusing devices to create monodisperse water-in-oil droplets at rates exceeding 1,000 droplets per second, and the generated droplets may be about 20-200 pm diameter. Each droplet contains the selected enzymes at about 0.1-10 pM per enzyme, substrates for each of the selected enzymes at concentrations of about 10-1000 pM, appropriate buffers and cofactors, and / or stabilizing agents, e.g., BSA or polymer additives. The oil phase of the droplets may contain surfactants to stabilize droplets and prevent coalescence during incubation and analysis.Compound Library

[0454] A small molecule library (e.g., interaction species reservoir) includes potential enzyme inhibitors. Each compound of the library may be uniquely tagged with a DNA barcode. The DNA barcode system may include double-stranded DNA tags, e.g., of about 20 to about 40 bases in length. The DNA tags may be attached to the inhibitor compounds, e.g., via biocompatible linkers such as polyethylene glycol chains, photo-cleavable linkers, enzyme-cleavable peptide linkers, and / or click chemistry handles. The DNA barcodes may be designed with errorcorrecting codes, unique molecular identifiers (UMIs) for PCR bias correction, and / or primer binding sites for amplification.

[0455] The system selects at least one interaction species, e.g., a plurality of interaction species, from the interaction species reservoir to be interacted. The system selects appropriate compounds / species to be included in each reaction pool of the pooling configuration. The selected DNA-barcoded compounds are also encapsulated into microfluidic droplets (“inhibitor droplets”). A separate inhibitor droplet is generated for each selected compound, which may be present at a concentration of about 0.1-100 pM in the droplet.Screening / Reaction Workflow

[0456] The system is configured to conduct reactions between the selected enzymes and selected interaction species, e.g., by combining the enzyme droplets and inhibitor droplets. The droplets may be merged or combined, e.g., using electric field-induced coalescence, channel geometrybased passive merging, acoustic wave-driven fusion, and / or optically triggered merging. Themerged droplets may be incubated in delay lines or collection chambers for 1 minute to 2 hours at controlled temperatures. In each merged droplet, the selected enzymes react with the DNA- barcoded compound of the inhibitor droplet to produce a plurality of reaction output samples, wherein each reaction output sample contains spectrally distinct products from the enzyme reactions as discussed above.

[0457] The reaction products are analyzed by a molecular analysis module. The molecular analysis module advantageously employs full-spectrum detection. In some instances, the molecular analysis module may employ single-wavelength or peak-based measurements. The molecular analysis module may further utilize a high-resolution spectrophotometer capable of collecting complete spectra from 200-800 nm with 0.5-2 nm resolution. For droplet analysis, the molecular analysis module may incorporate fiber optic probes for in-flow measurements, microfluidic cuvettes with defined path lengths, and / or imaging spectroscopy for parallel droplet analysis.

[0458] A full-spectrum detection molecular analysis module is capable of analyzing the entire spectral shape of a reaction output sample as a multi-dimensional fingerprint as discussed above. Such a system may employ sophisticated spectral analysis algorithms, which are advantageous over simple measurement of absorbance at predetermined wavelengths. The spectral analysis algorithms include, for example, multivariate curve resolution to separate overlapping spectra, principal component analysis to identify spectral patterns, machine learning models trained on known enzyme combinations, spectral derivative analysis to enhance fine features, and / or two- dimensional correlation spectroscopy techniques.

[0459] The multi-dimensional fingerprint advantageously enables identification of specific enzyme inhibition patterns within each droplet. When an inhibitor selectively blocks one enzyme in the mixture, the resulting spectrum shows characteristic changes such as loss of specific peaks, altered peak ratios, disappearance of spectral shoulders, and / or shifts in isosbestic points. A reference database of spectral patterns, corresponding to inhibition of each enzyme individually and in combinations, may be generated.

[0460] Following the spectroscopic analysis, the droplets may be further grouped based on spectral similarity to produce a reaction pool. The system is configured to employ clustering algorithms to identify droplets with similar inhibition patterns based on the spectroscopy results. For example, droplets showing complete inhibition of enzyme Abut not enzymes B or C may begrouped in one reaction pool, while droplets showing inhibition of both A and B may form a separate reaction pool. The pooling is achieved, for example, by fluorescence-activated droplet sorting based on spectral features, dielectrophoretic sorting using spectral data to control sorting parameters, passive sorting through channel networks triggered by optical detection, and / or collection into multi-well plates based on spectral classification.

[0461] Each reaction pool contains droplets with similar spectral patterns, representing potentially different inhibitors causing the same enzyme inhibition profile. The droplets in each reaction pool may be broken by addition of demulsification agents, electrical disruption, and / or chemical dissolution of surfactants. The aqueous phases may be combined and prepared for DNA barcode sequencing.

[0462] The DNA barcodes of inhibitor compounds in each reaction pool are analyzed, e.g., by amplification and sequencing, which are conducted through extraction of nucleic acids from the reaction pool, PCR amplification using universal primers flanking the barcode region, and / or addition of pool-specific index sequences for multiplexed sequencing. High-throughput sequencing may identify all DNA barcodes present in each spectrally defined reaction pool. Since each pool represents a specific inhibition pattern, the system is capable of directly associating inhibitor structures (via their barcodes) with their functional effects on the enzyme panel.

[0463] The system further correlates spectral patterns (corresponding to enzyme inhibition) with the identified DNA barcode sequences to create a comprehensive inhibitor profile. For each identified inhibitor, the system determines which enzymes are inhibited based on spectral changes, the degree of inhibition from spectral intensity changes, potential selectivity by comparing effects across enzyme combinations, and / or kinetic parameters, e.g., based on time- resolved spectral data.

[0464] Machine learning optimization may be incorporated by the system for spectral interpretation. For example, initial training sets may use known inhibitors to establish spectral- inhibition relationships. As screening progresses, the models may be refined using newly discovered inhibitor patterns. The system may advantageously predict inhibition profiles for untested compounds based on structural similarity to characterized inhibitors.

[0465] Quality control measures include, but are not limited to: control droplets with known inhibitors to validate spectral deconvolution, enzyme-only droplets to establish baseline spectra,solvent-only droplets to assess background, and / or droplets with non-inhibitory compounds to confirm specificity. Further, the system may employ derivative spectroscopy and / or two- dimensional correlation analysis for enhanced resolution. For example, first and second derivatives of spectra may reveal hidden peaks and shoulders obscured in the original spectra, and two-dimensional correlation may identify subtle spectral changes occurring at different rates or in response to different inhibitor concentrations.Example 6. High-Throughput Determination of Enzyme Kinetic Parameters Using Time- Resolved Spectrophotometric Analysis

[0466] In this Example, a system, e.g., system 200, is provided for high-throughput determination of enzyme kinetic parameters using time-resolved spectrophotometric analysis. A protein reservoir includes, for example, enzymes known or predicted to act on substrates and / or produce chromogenic and / or UV-active products. An interaction species reservoir includes, for example, substrates of the enzymes (“substrate library”). A system according to embodiments herein selects, from the protein reservoir, a plurality of enzymes to be interacted with at least one substrate, e.g., a plurality of substrates, from the substrate library.Selection of EnzymesSelection of Enzymes for Protein Reservoir

[0467] The system selects enzymes that are known or predicted to act on substrates to produce chromogenic and / or UV-active products, i.e., compounds with distinct spectral signatures across the UV-visible spectrum (about 200-800 nm). The enzymes include, but are not limited to, peroxidases that oxidize different chromogenic substrates, laccases that produce colored quinones from phenolic compounds, cytochrome P450s that generate UV-absorbing metabolites, nitrilases that produce UV-active aromatic acids, esterases that release chromophoric leaving groups, dehydrogenases coupled to colorimetric redox indicators, phosphatases that release chromogenic products, dehydrogenases utilizing NAD+ / NADH (340 nm absorption change), oxidases producing hydrogen peroxide detectable via coupled reactions, kinases using ATP with coupled detection systems, proteases cleaving peptides with chromogenic leaving groups, transaminases with UV-active substrates and products, and / or glycosidases releasing chromophoric aglycones.

[0468] Inclusion criteria within the protein reservoir provides preferential selection of enzymes with known or predicted substrate-product pairs that exhibit non-overlapping spectral regions,isosbestic points for reaction progress monitoring, linear Beer-Lambert law relationships across relevant concentration ranges, and / or minimal interference from cofactors or buffer components. Selection of Enzymes for Reaction Pool

[0469] Following selection of the selection of enzymes for the protein reservoir, the system is configured to select a plurality of enzymes from the protein reservoir to be interacted, e.g., to be included within reaction pools of the pooling configuration. The system advantageously selects enzymes with activity that be quantified independently within a reaction pool. For example, within a selected reaction pool, enzyme A may be monitored at 280 nm and 320 nm, enzyme B at 340 nm and 380 nm, and enzyme C at 420 nm and 460 nm, with mathematical deconvolution enabling simultaneous quantification despite partial spectral overlap.

[0470] The system may further identify the optimal detection for each enzyme using multivariate analysis of the full UV-visible spectrum for the enzyme’s substrates and products at multiple concentrations, thereby generating a unique “spectral fingerprint” that may be used in the pooling configuration. The spectral fingerprints allows analysis of multiple spectral features simultaneously, e.g., peak maxima wavelength, distinctive spectral shapes, characteristic shoulder patterns, specific absorbance ratios at multiple wavelengths, and / or unique spectral fine structure. For example, molecules with similarmaxvalues (e.g., two substrates both absorbing maximally at 260±5 nm) may be distinguished by analysis of spectral shape parameters. These parameters may include, e.g., the full width at half maximum, asymmetry factors calculated as the ratio of half-widths on the long- versus short-wavelength sides of the peak, and / or the presence and position of spectral shoulders arising from vibronic transitions or conformational heterogeneity. Derivative spectroscopy (first through fourth derivatives) may be employed to enhance resolution of overlapping bands and reveal hidden spectral features. Absorption ratios at strategically selected wavelengths may further serve as unique identifiers for the pooling configuration.

[0471] The system may further identify distinct detection characteristics for each enzyme based on its reaction spectra under multiple reaction conditions, e.g., pH, solvent conditions, temperature, reaction time, and the like. For example, spectra for each enzyme may be collected at three to five different pH conditions (e.g., pH 5.0, 6.5, 7.4, 8.0, and 9.0). Solvent-dependent spectral variations for each enzyme may be determined by adding controlled amounts of organic modifiers. For example, addition of 10-20% methanol or acetonitrile may cause wavelengthshifts of 5-15 nm for many aromatic compounds, alter extinction coefficients by 10-50%, and / or reveal fine structure obscured in purely aqueous solutions. Additionally, spectra for each enzyme may be collected at multiple temperatures (e.g., 15°C, 25°C, 35°C, and 45°C). Temperature variations may cause hyperchromic or hypochromic effects (±5-20% absorption changes), slight wavelength shifts due to solvent reorganization, and / or changes in spectral fine structure from altered vibrational states. Enzymes from thermophilic organisms may advantageously allow measurements at elevated temperatures where spectral differences are magnified.

[0472] The multiple reaction conditions may be tested in a multi-well plate, a multi-channel flow system, and / or segmented wells. A three-dimensional data matrix, including, e.g., wavelength, pH, and time data, may be constructed for each enzyme. Such data matrices enhance the spectral fingerprint of each enzyme and may be used to determine the pooling configuration.

[0473] The system selects enzymes for a reaction pool based on spectral orthogonality (e.g., according to the distinct spectral characteristics such as spectral fingerprints) and kinetic compatibility. For example, enzymes are suitable for inclusion in the same reaction pool if they have non-overlapping spectral windows of at least 20 nm between major peaks, similar optimal pH ranges (e.g. within 1 pH unit), compatible temperature requirements, comparable reaction timescales (all reaching measurable conversion within 1-60 minutes), and / or absence of crossreactivity between enzymes and non-cognate substrates. Each reaction pool may contain 2 or more enzymes, optimized to maximize throughput while maintaining quantitative accuracy.Substrate Library

[0474] An interaction species reservoir includes a substrate library, which contains the substrates for each enzymes in the protein reservoir. The system selects at least one substrate, e.g., a plurality of substrates, to interact with selected enzymes in a reaction pool determined according to a pooling configuration described herein.Screening / Reaction Workflow

[0475] The system is configured to conduct reactions between the selected enzymes and their substrates in a reaction pool. A matrix approach may be employed for comprehensive kinetic characterization. For Michaelis-Menten parameter determination, the system may prepare substrate concentration series spanning 0.1-10 times the expected Km for each enzyme. For example, if enzyme A has an expected Km of 100 pM, substrate concentrations may include 10,20, 50, 100, 200, 500, and 1000 pM. These concentrations may be prepared in a 384-well or 1536-well format using automated liquid handling systems.

[0476] The reaction pools containing the selected enzymes and substrates may be in temperature-controlled microplates. The enzymes in each pool may be present, e.g., at defined concentrations (e.g., 1-100 nM per enzyme), all corresponding substrates at one concentration point from the matrix, optimized buffer systems maintaining stable pH throughout the reaction, and / or necessary cofactors at saturating concentrations. The total reaction volume may range from 20-200 pL, optimized for the spectrophotometer’s microplate reader capabilities.

[0477] The system includes a molecular analysis module for time-resolved spectrophotometric monitoring, e.g., a high-speed plate reader capable of collecting full spectra (200-800 nm) from all wells. The molecular analysis module may advantageously collect complete spectral data rather than single- wavelength measurements, enabling post-acquisition optimization of analysis wavelengths. Data collection parameters may include spectral acquisition every 5-60 seconds for 5-120 minutes, temperature control maintaining ±0.3°C stability, orbital shaking between measurements to ensure mixing, and / or automatic gain adjustment to optimize signal-to-noise across the dynamic range.Data Demultiplexing and Analysis

[0478] The system demultiplexes the reaction products, i.e., reaction output samples in each reaction pool, by first performing spectral decomposition using algorithms (e.g. multivariate curve resolution-alternating least squares). This approach may advantageously separate overlapping spectra into individual component contributions without requiring pure component spectra. The system may extract time-dependent concentration profiles for each substrate-product pair, apply baseline corrections for drift or evaporation effects, and / or account for inner filter effects at high chromophore concentrations.

[0479] The system may identify unique spectral fingerprints from the reaction products in each reaction pool using a mathematical framework, including multivariate pattern recognition techniques such as Principal Component Analysis (PCA) to reduce the high-dimensional spectral data (e.g., 300 wavelength points x 5 pH values x 4 temperatures = 6,000 dimensions per spectrum) to a smaller set of orthogonal components capturing >99% of spectral variance. The system could then, for example, apply Linear Discriminant Analysis (LDA), Support VectorMachines (SVM), or neural network, to classify spectra and quantify individual components in mixtures.

[0480] Advantageously, the spectral fingerprints enable quantification even when complete spectral separation is not achieved. For example, two products with 80% spectral overlap may still be quantified with <5% error by utilizing their distinct features at specific wavelength / condition combinations. The system may automatically identify these optimal measurement conditions through, for example, exhaustive searching or genetic algorithms that maximize the condition number of the spectral deconvolution matrix.

[0481] Quality metrics for the fingerprinting analysis may include the spectral residuals after fitting, correlation between replicate measurements, and / or orthogonality scores between different molecular fingerprints in the pool. The system may flag cases where deconvolution uncertainty exceeds acceptable thresholds and suggest alternative multiplexing strategies or measurement conditions to improve discrimination.

[0482] For kinetic parameter extraction, the system may fit progress curves to integrated rate equations. For simple Michaelis-Menten kinetics, the system may use: d[P] / dt = (Vmax x [S]) / (Km + [S]), where [P] is product concentration, [S] is substrate concentration, Vmax is maximum velocity, and Km is the Michaelis constant. The fitting may employ non-linear regression with appropriate weighting schemes, considering measurement uncertainty at different spectral regions.

[0483] For inhibitor characterization, the system may incorporate compounds at multiple concentrations across the substrate matrix. The expanded experimental design may include a series of inhibitor concentrations (e.g. 0, 0.1, 0.3, 1, 3, 10, 30, 100 x expected Ki), full substrate concentration series at each inhibitor level, and / or time-resolved measurements enabling distinction between competitive, non-competitive, and uncompetitive inhibition. The system may simultaneously determine inhibition constants (Ki), inhibition mechanisms, and / or Hill coefficients for cooperative effects.

[0484] The system may employ global fitting using mathematical deconvolution approaches where all progress curves for a given enzyme across different conditions are fit simultaneously. This approach may advantageously constrain kinetic parameters to be consistent across the dataset, improving accuracy and precision. The system may utilize weighted least-squares fittingwith weights based on spectrophotometric noise characteristics, bootstrap resampling to estimate parameter confidence intervals, and / or F-tests to discriminate between different kinetic models.

[0485] The system may advantageously enable determination of multiple kinetic parameters from a single multiplexed experiment, including Km and kcat for each enzyme- substrate pair, Ki and inhibition mechanism for tested compounds, pH and temperature dependence of kinetic parameters, substrate specificity profiles across related compounds, and / or cooperative binding parameters (Hill coefficients, K0.5).

[0486] For complex reaction mechanisms, the system may extend the analysis to include multisubstrate reactions by varying two substrates in a matrix format, product inhibition effects by monitoring reverse reaction rates, allosteric regulation by including effector molecules, and / or enzyme stability by analyzing time-dependent activity loss. The spectrophotometric approach may be particularly advantageous for enzymes producing colored intermediates, enabling detection of pre-steady-state kinetics and reaction mechanism elucidation.

[0487] The system may provide comprehensive kinetic parameter tables for each enzymesubstrate-inhibitor combination, confidence intervals and quality metrics for all determined parameters, mechanistic classifications (e.g., ordered vs. random substrate binding), structureactivity relationships for substrate or inhibitor series, and / or predictive models for untested conditions based on the collected data.

[0488] Quality control measures may include internal standards with known extinction coefficients to verify spectrophotometer calibration, enzyme-free controls to assess non- enzymatic substrate degradation, replicate measurements at key concentration points, and / or positive controls with enzymes of known kinetic parameters. The system may flag data points where spectral decomposition residuals exceed predetermined thresholds or where fitted parameters fall outside physiologically reasonable ranges.Example 7. High-Throughput Screening of Protein-Protein Interaction Inhibitors Using Extended-Range Ion Trap Mass Spectrometry

[0489] In this Example, a system, e.g., system 200, is provided for high-throughput screening of protein-protein interaction inhibitors using extended-range ion trap mass spectrometry. A protein reservoir includes, for example, proteins that form complexes. An interaction species reservoir includes, for example, a library of potential inhibitor compounds (“compound library”). A system according to embodiments herein selects, from the protein reservoir, a plurality of proteincomplexes to be interacted with at least one compound, e.g., a plurality of compounds, from the interaction species reservoir.Selection of Proteins / Protein Complexes

[0490] The system selects, for inclusion into the protein reservoir, proteins that are known or predicted to form stable complexes detectable by native mass spectrometry. Exemplary target complexes include therapeutic targets spanning 30-300 kDa total complex mass. The protein complexes may be formed from two proteins, i.e., a protein pair, or more than two proteins in a multi-protein complex.

[0491] The system determines a pooling configuration for inclusion of protein complexes into a reaction pool. The system selects protein complexes that maintain at least 100 Th spacing between complex envelopes in their expected charge state ranges (e.g., +10 to +20 for a 50 kDa complex. This spacing ensures that charge state distributions do not overlap and allows the complex to be distinguished from other complexes by mass spectrometry.

[0492] Each reaction pool may include about 10-20 protein pairs for routine mass spectrometry analysis. Reaction pools with 30-50 protein pairs may be used with additional validation using ion mobility spectrometry (IMS) and / or MSn fragmentation to confirm complex assignments. The expected m / z values for all protein pairs in the reaction pool, based on their masses and typical charge state distributions under native conditions, have a minimum 100 Th separation.

[0493] The proteins may be maintained in ammonium acetate solutions in the range of 10-200 mM at pH 7.0+0.5. Buffer concentrations may be below 200 mM, e g., to prevent spray current reduction and salt adduction that can broaden peaks and compromise resolution. Online buffer exchange systems may be incorporated immediately prior to mass spectrometry analysis, e.g., electrospray ionization, to ensure optimal ionization conditions while maintaining native protein conformations during sample handling.Compound Library

[0494] A compound library (e.g., interaction species reservoir) includes potential inhibitors of the protein-protein interactions that form the complexes in the protein reservoir. The system selects at least one compound, e.g., a plurality of compounds, from the compound library to interact with selected protein complexes in a reaction pool determined according to a pooling configuration described herein.

[0495] The compounds may be provided as concentrated stocks (e.g., 10-100 mM in DMSO) and diluted such that final DMSO concentrations remain at or below 1% v / v in final reaction mixtures to prevent peak broadening and ionization suppression. Acoustic dispensing or other nano-volume liquid handling may be used when conducting reactions between selected compounds and protein complexes, to minimize solvent transfer while maintaining compound concentrations suitable for inhibitor screening (0.1-100 pM final).Screening / Reaction Workflow

[0496] The system is configured to conduct reactions between the selected protein complexes and potential inhibitor compounds in a reaction pool. The reactions may be conducted with rapid mixing and short incubation times to minimize subunit exchange between complexes sharing homologous components. For example, in a reaction pool, protein pairs may be combined and allowed to form complexes for 15-30 minutes at controlled temperatures (4-25°C), and potential inhibitor compounds may be added either before complex formation to test prevention of binding, during complex formation to assess competition, or after complex formation to evaluate disruption of pre-formed complexes.

[0497] To address potential ion suppression effects, the system may employ a two-tiered injection strategy. Complexes with significantly different ionization efficiencies may be analyzed in separate tiers, with protein concentrations balanced to ensure all complexes fall within the instrument's dynamic range. For example, highly charged or “sticky” complexes that might suppress other signals may be diluted 10-fold relative to other components in the reaction pool. Data Demultiplexing and Analysis

[0498] The system demultiplexes the reaction products, .e., reaction output samples in each reaction pool, by employing automated charge state deconvolution algorithms (e.g. UniDec) optimized for native mass spectra. The system may utilize the ion trap’s MSn capabilities to isolate and fragment specific complex ions, providing orthogonal validation of complex identity and stoichiometry. For enhanced confidence, trapped ion mobility spectrometry may provide an additional dimension of separation based on collision cross sections, which is particularly useful when analyzing larger reaction pools, e.g., containing 30-50 protein complexes.

[0499] For quantitative analysis, the system may calculate percent inhibition by comparing integrated peak intensities across the entire charge state envelope of each complex. Doseresponse curves may be generated from multiple compound concentrations, enablingdetermination of IC50 values and Hill coefficients. The system may distinguish between different mechanisms of inhibition by comparing results from pre-incubation versus post-formation compound addition experiments.

[0500] The system may advantageously incorporate real-time data processing to enable adaptive experimental design. Initial screening results may inform subsequent multiplexing strategies, with compounds showing promising activity automatically queued for confirmation in lower- multiplex pools or individual complex analysis. Machine learning algorithms may be employed to predict optimal multiplexing configurations based on complex properties and historical screening performance.Example 8. High-Throughput Screening of Enzyme Activities Using 19F NMR Spectroscopy

[0501] In this Example, a system, e g., system 200, is provided for high-throughput screening of enzyme activities on fluorinated substrates using 19F nuclear magnetic resonance (NMR) spectroscopy. The 19F nucleus may provide several advantages including 100% natural abundance, high sensitivity (83% relative to 1H), wide chemical shift dispersion (-300 ppm range), and / or absence of background signals from biological samples. A protein reservoir includes, for example, enzymes that are known to predicted to act on fluorinated substrates. An interaction species reservoir includes, for example, a library of fluorinated substrates (“substrate library”). A system according to embodiments herein selects, from the protein reservoir, a plurality of enzymes to be interacted with at least one substrates, e.g., a plurality of substrates, from the interaction species reservoir.Selection of Enzymes

[0502] The system selects, for inclusion into the protein reservoir, enzymes that are known to predicted to act on fluorinated substrates. Exemplary enzymes include, but are not limited to, fluorinases and defluorinases, cytochrome P450s that metabolize fluorinated drugs, esterases that cleave fluorinated esters, kinases that accept fluorinated ATP analogs, and / or glycosidases that process fluorinated sugar derivatives.

[0503] The system determines a pooling configuration for inclusion of enzymes from the protein reservoir into a reaction pool. The system may combine up to 20-50 enzyme reactions in a reaction pool, which may be included in a single NMR tube, with each enzyme-substrate pair producing products in non-overlapping spectral regions.Substrate Library

[0504] The system selects, for inclusion into the substrate library, substrates with substrateproduct pairs that exhibit distinct 19F chemical shifts separated by at least 0.5 ppm. For example, a fluorinated benzoate ester substrate at -112 ppm may be converted by an esterase to fluorobenzoic acid at -105 ppm, providing 7 ppm separation. The substrates are selected such that multiple reactions can be monitored simultaneously without spectral overlap. This allows enzymes to be pooled in a reaction pool based on their substrate specificities and expected chemical shift ranges.Screening / Reaction Workflow

[0505] The system is configured to conduct reactions between the selected enzymes and substrates in a reaction pool. The enzymes and their respective fluorinated substrates are combined in a buffered solution compatible with NMR analysis. Reactions may proceed at controlled temperatures (e.g., 25-37°C) directly in the NMR spectrometer, enabling real-time monitoring. The system may employ a flow-NMR setup for continuous measurement of multiple pooled reactions, with automated sample changing every 5-30 minutes.

[0506] The system includes a molecular analysis module, e g., NMR instrument, utilizing 19F NMR pulse sequences with appropriate relaxation delays to ensure quantitative measurements. The molecular analysis module may collect spectra at regular intervals (e.g., every 1-5 minutes) to generate time-resolved reaction profiles. Signal integration may provide quantitative information about substrate consumption and product formation rates.Data Demultiplexing and Analysis

[0507] The system demultiplexes the reaction products, .e., reaction output samples in each reaction pool, by employing peak deconvolution algorithms to resolve overlapping signals and assign them to specific enzyme-substrate pairs. The system may advantageously utilize the high resolution of NMR to distinguish between closely related products, even those differing by a single fluorine position. Machine learning algorithms may be trained on reference spectra to automatically identify and quantify reaction products in complex mixtures.

[0508] Quality control measures may include the use of internal fluorinated standards (e.g., trifluoroacetic acid) for chemical shift referencing and quantification, control reactions without enzymes to assess chemical stability, and / or temperature calibration using standard NMR thermometer compounds.

[0509] Example Embodiments

[0510] Embodiment 1 is a system for concurrent measurements of interacting molecules from at least two biological process wherein the biological processes are selected such that the process interacting molecules can be sufficiently discerned by a molecular analysis module

[0511] Embodiment 2 is a system for concurrent measurements of degree / quantity of change in at least two interacting molecules from at least two biological reactions wherein the biological reactions are selected such that the interacting molecules can be sufficiently discerned by mass spectrometer

[0512] Embodiment 3 is the system of embodiment 2 wherein the reaction is a result of a protein.

[0513] Embodiment 4 is the system as in any previous embodiment, wherein the protein is an enzyme.

[0514] Embodiment 5 is the system as in any previous embodiment, wherein the reaction is a result of a whole cell.

[0515] Embodiment 6 is the system concurrent measurements of degree / quantity of change in at least two label-free interacting molecules from at least two biological reactions wherein the biological reactions are selected such that the reaction chemicals can be sufficiently discerned by mass spectrometer.

[0516] Embodiment 7 is the system as in any previous embodiment, wherein the reactions are a result of label-free protein.

[0517] Embodiment 8 is a system for concurrent measurements of chemicals affected by protein reactions wherein the chemicals are combined into one volume to be measured by mass spectrometry and protein reactions are of at least two different proteins.

[0518] Embodiment 9 is a system for concurrent measurements of binding molecules from at least two biological processes, wherein the biological processes are selected such that the binding molecules can be sufficiently discerned by mass spectrometry.

[0519] Embodiment 10 is the system as in any previous embodiment, wherein the system is comprised of a protein reservoir; an interaction species reservoir; a reaction components reservoir; a multiplexer; a reaction chamber; a molecular analysis module; and a demultiplexer.

[0520] Embodiment 11 is a system for concurrent measurements of a plurality of protein reactions, the system comprising: a) a protein reservoir configured to store a plurality of proteins;b) an interaction species reservoir configured to store a plurality of interaction species; c) a reaction components reservoir configured to store a plurality of reaction components; d) a multiplexer operatively coupled to the protein reservoir, the interaction species reservoir, and the reaction components reservoir, the multiplexer comprising: i) a processor; ii) a database; and iii) a sample handling system; e) a reaction chamber operatively coupled to the multiplexer and configured to host a plurality of concurrent reactions; f) a molecular analysis module operatively coupled to the reaction chamber and configured to analyze combined reaction outputs; and g) a demultiplexer operatively coupled to the molecular analysis module and configured to process analysis results, the demultiplexer comprising: i) a processor; and ii) a database.

[0521] Embodiment 12 is the system as in any previous embodiment, wherein the molecular analysis module comprises a mass spectrometer.

[0522] Embodiment 13 is the system as in any previous embodiment, wherein the mass spectrometer is selected from the group consisting of: Matrix-Assisted Laser Desorption / Ionization Time-of-Flight (MALDI-TOF), Electrospray Ionization Mass Spectrometry (ESLMS), Liquid Chromatography-Mass Spectrometry (LC-MS), Gas Chromatography-Mass Spectrometry (GC-MS), Inductively Coupled Plasma Mass Spectrometry (ICP-MS), and Secondary Ion Mass Spectrometry (SIMS).

[0523] Embodiment 14 is the system as in any previous embodiment, wherein the protein reservoir is configured to store at least 1,000 unique proteins.

[0524] Embodiment 15 is the system as in any previous embodiment, wherein the interaction species reservoir is configured to store at least 1,000,000 unique interaction species.

[0525] Embodiment 16 is the system as in any previous embodiment, wherein the multiplexer is configured to combine at least 1,000 concurrent reactions into a single sample for analysis.

[0526] Embodiment 17 is the system as in any previous embodiment, wherein the reaction chamber is configured to host reactions with volumes ranging from 100 picoliters to 10 microliters.

[0527] Embodiment 18 is the system as in any previous embodiment, wherein the demultiplexer is configured to process data from at least 1,000,000 concurrent reactions combined into a single sample.

[0528] Embodiment 19 is the system as in any previous embodiment, further comprising a user interface module operatively coupled to at least one of the multiplexer, the reaction chamber, the molecular analysis module, and the demultiplexer.

[0529] Embodiment 20 is the system as in any previous embodiment, wherein the multiplexer is configured to implement sample pooling strategies based on physicochemical properties of the proteins and interaction species.

[0530] Embodiment 21 is a system for concurrent measurements of a plurality of protein reactions using pooling configurations, the system comprising: a) a protein reservoir configured to store a plurality of proteins; b) an interaction species reservoir configured to store a plurality of interaction species; c) a multiplexer operatively coupled to the protein reservoir and the interaction species reservoir, the multiplexer comprising: i) a processor; ii) a database storing information on physicochemical properties of the proteins and interaction species; and iii) a sample handling system; wherein the processor is configured to: iv) access the stored information on physicochemical properties; v) generate pooling configurations based on the physicochemical properties, wherein each pooling configuration specifies a combination of at least two proteins or at least two interaction species for concurrent reaction; and vi) control the sample handling system to prepare pooled samples according to the generated pooling configurations; d) a reaction chamber operatively coupled to the multiplexer and configured to host the pooled samples for concurrent reactions; e) a molecular analysis module operatively coupled to the reaction chamber and configured to analyze combined reaction outputs from the pooled samples; and f) a demultiplexer operatively coupled to the molecular analysis module and configured to process analysis results and deconvolute data from the pooled samples.

[0531] Embodiment 22 is the system as in any previous embodiment, wherein the physicochemical properties comprise at least one of: molecular weight, isoelectric point, hydrophobicity, charge, size, and known interaction profiles.

[0532] Embodiment 23 is the system as in any previous embodiment, wherein the pooling configurations are designed to minimize potential interference between different molecular species in each pooled sample.

[0533] Embodiment 24 is the system as in any previous embodiment, wherein the pooling configurations are designed to maximize the information obtained from each pooled sample.

[0534] Embodiment 25 is the system as in any previous embodiment, wherein the processor is further configured to generate pooling configurations that group proteins based on their compatibility for pooling.

[0535] Embodiment 26 is the system as in any previous embodiment, wherein the processor is further configured to generate pooling configurations that group interaction species based on their compatibility for pooling.

[0536] Embodiment 27 is the system as in any previous embodiment, wherein the processor is further configured to adaptively modify pooling configurations based on feedback from the demultiplexer.

[0537] Embodiment 28 is a method for concurrent measurements of a plurality of protein reactions, the method comprising: a) providing a plurality of proteins; b) providing at least one interaction species; c) optionally providing at least one reaction component; d) using a multiplexer to combine said proteins, interaction species, and optional reaction components in a reaction chamber to create at least two distinct reactions, wherein each reaction comprises at least one protein from the plurality of proteins; e) allowing the at least two distinct reactions to occur; f) using the multiplexer to combine outputs from the at least two distinct reactions; g) analyzing the combined reaction outputs using a molecular analysis module; h) processing the analysis results using a demultiplexer; and i) storing the generated output.

[0538] Embodiment 29 is the method as in any previous embodiment, wherein the step of analyzing the combined reaction outputs comprises mass spectrometry analysis.

[0539] Embodiment 30 is the method as in any previous embodiment, wherein the mass spectrometry analysis employs a technique selected from the group consisting of: Matrix- Assisted Laser Desorption / Ionization Time-of-Flight (MALDI-TOF), Electrospray Ionization Mass Spectrometry (ESLMS), Liquid Chromatography-Mass Spectrometry (LC-MS), Gas Chromatography-Mass Spectrometry (GC-MS), Inductively Coupled Plasma Mass Spectrometry (ICP-MS), Direct Injection Mass Spectrometry (DIMS), Ion Trap Mass Spectrometry and Secondary Ion Mass Spectrometry (SIMS).

[0540] Embodiment 31 is the method as in any previous embodiment, wherein the step of providing a plurality of proteins comprises providing at least 1,000 unique proteins.

[0541] Embodiment 32 is the method as in any previous embodiment, wherein the step of providing at least one interaction species comprises providing at least 1,000,000 unique interaction species.

[0542] Embodiment 33 is the method as in any previous embodiment, wherein the step of using a multiplexer to combine outputs from the at least two distinct reactions comprises combining at least 1,000 concurrent reactions into a single sample for analysis.

[0543] Embodiment 34 is the method as in any previous embodiment, wherein the step of allowing the at least two distinct reactions to occur comprises maintaining reaction volumes ranging from 100 picoliters to 10 microliters.

[0544] Embodiment 35 is the method as in any previous embodiment, wherein the step of processing the analysis results using a demultiplexer comprises processing data from at least 1,000,000 concurrent reactions combined into a single sample.

[0545] Embodiment 36 is the method as in any previous embodiment, further comprising a step of receiving user input through a user interface module operatively coupled to at least one of the multiplexer, the reaction chamber, the molecular analysis module, and the demultiplexer.

[0546] Embodiment 37 is the method as in any previous embodiment, wherein the step of using a multiplexer to combine said proteins, interaction species, and optional reaction components comprises implementing sample pooling strategies based on physicochemical properties of the proteins and interaction species.

[0547] Embodiment 38 is the method for concurrent measurements of a plurality of protein reactions using pooling configurations, the method comprising: a) accessing stored information on physicochemical properties of a plurality of proteins and a plurality of interaction species; b) generating pooling configurations based on the physicochemical properties, wherein each pooling configuration specifies a combination of at least two proteins or at least two interaction species for concurrent reaction; c) preparing pooled samples according to the generated pooling configurations using a sample handling system; d) allowing concurrent reactions to occur in the pooled samples; e) analyzing combined reaction outputs from the pooled samples using a molecular analysis module; f) processing the analysis results ...

Claims

CLAIMS:

1. A system for concurrent measurement of a plurality of interacting molecules, the system comprising: a protein reservoir configured to store proteins, an interaction species reservoir configured to store interaction species, at least one processor configured to: select, from the protein reservoir, a plurality of proteins to be interacted, select, from the interaction species reservoir, at least one interaction species to be interacted, wherein the at least one interaction species and the plurality of proteins are determined according to at least one reaction pool of a pooling configuration, each reaction pool including at least two selected proteins from the plurality of proteins and at least one selected interaction species from the at least one interaction species; a reaction chamber configured for conducting individual reactions between the plurality of proteins and the at least one interaction species to generate a plurality of reaction output samples; and a molecular analysis module configured to measure the plurality of reaction output samples, wherein measuring includes concurrent measurement of at least two of the reaction output samples associated with a reaction pool selected according to the pooling configuration.

2. The system of claim 1, wherein: the at least one interaction species includes a plurality of interaction species, the selected interaction species includes at least two interaction species, and the at least one reaction pool includes a plurality of reaction pools.

3. The system of any of the preceding claims, wherein concurrent measurement includes measurement of all of the reaction output samples associated with the reaction pool selected according to the pooling configuration.

4. The system of any of the preceding claims, further comprising a sample handling system configured to: receive control instructions from the at least one processor, and provide operative coupling between any combination of the protein reservoir, the interaction species reservoir, the reaction chamber, and the molecular analysis module, wherein operative coupling includes one or more of protein transfer, interaction species transfer, and reaction output sample transfer.

5. The system of claim any of the preceding claims, wherein the protein reservoir or the interaction species reservoir includes the reaction chamber.

6. The system of claim 4, wherein: the reaction chamber includes a plurality of reaction vessels, each reaction vessel being configured for conducting one of the individual reactions to generate the plurality of reaction output samples; the sample handling system is configured to combine the plurality of reaction output samples into at least one combined reaction output sample according to the pooling configuration, and the molecular analysis module is configured to measure the reaction output samples in the at least one combined reaction output sample.

7. The system of claim 4, wherein: the sample handling system is configured to combine proteins from the plurality of proteins with interaction species from the at least one interaction species in the reaction chamber according to the pooling configuration, the reaction chamber is configured for conducting a plurality of the individual reactions concurrently to generate a combined reaction output sample, and the molecular analysis module is configured to measure the combined reaction output sample.

8. The system of claim 7, wherein the reaction chamber includes a plurality of individual reaction vessels, each individual reaction vessel being configured for concurrently conductingthe plurality of the individual reactions according to the pooling configuration, and the molecular analysis module is configured to measure a plurality of combined reaction output samples.

9. The system of any of the preceding claims, wherein the molecular analysis module is configured for sequential measurement of multiple combined reaction output samples, each associated with a different reaction pool.

10. The system of any of the preceding claims, further comprising a reaction components reservoir configured to store a plurality of reaction components for adjusting reaction conditions.

11. The system of any of the preceding claims, wherein the molecular analysis module is configured to directly measure at least one physicochemical property of reaction outputs associated with the plurality of reaction output samples.

12. The system of any of the preceding claims, wherein the molecular analysis module includes a mass spectrometer employing one or more techniques selected from the group consisting of: Matrix-Assisted Laser Desorption / Ionization Time-of-Flight (MALD TOF), Electrospray Ionization Mass Spectrometry (ESI-MS), Liquid Chromatography-Mass Spectrometry (LC-MS), Gas Chromatography-Mass Spectrometry (GC-MS), Inductively Coupled Plasma Mass Spectrometry (ICP-MS), Direct Injection Mass Spectrometry (DIMS), Ion Trap Mass Spectrometry and Secondary Ion Mass Spectrometry (SIMS).

13. The system of any of the preceding claims, wherein the molecular analysis module includes at least one device selected from the group comprising: a spectrophotometer; a chromatography system; a Nuclear Magnetic Resonance (NMR) spectrometer; a fluorescence spectrometer; a Raman spectrometer; and a capillary electrophoresis system.

14. The system of any of the preceding claims, wherein the pooling configuration includes pairings between each of the plurality of proteins with each of the at least one interaction species.

15. The system of any of the preceding claims, wherein the reaction chamber is configured for reaction of label free proteins, label free interaction species, or both.

16. The system of any of the preceding claims, wherein the at least one processor is further configured to obtain the pooling configuration, the pooling configuration being determined according to at least one criterion.

17. The system of claim 16, wherein the at least one criterion includes a criterion that expected measurement results observable by the molecular analysis module of each reaction output sample associated with a reaction pool be differentiable.

18. The system of claim 16, wherein the at least one criterion includes a criterion based on physicochemical properties of the plurality of proteins and the at least one interaction species selected for the pooling configuration.

19. The system of claim 16, wherein the at least one criterion includes a criterion based on one or more of: molecular weights of expected reactant products associated with each reaction pool, spectral characteristics of expected reactant products associated with each reaction pool, chromatographic behavior of expected reactant products associated with each reaction pool, ionization properties of expected reactant products associated with each reaction pool, chemical stability of expected reactant products associated with each reaction pool, chemical reactivity of expected reactant products associated with each reaction pool, or hydrophilicity and / or hydrophobicity of expected reactant products associated with each reaction pool.

20. The system of any of the preceding claims, wherein the at least one processor is further configured to demultiplex the concurrent measurement to differentiate measurement results associated with each reaction output sample within the reaction pool.

21. The system of any of the preceding claims, wherein the at least one processor is further configured to: obtain, from the molecular analysis module, pool measurement data corresponding to measurements from a combined reaction output sample; demultiplex the pool measurement data to obtain individual measurements of outputs of the individual reactions, wherein the individual measurements include positive indications of reactions between proteins and interaction species and / or negative indications of reactions between proteins and interaction species; and store the individual measurements as demultiplexed pool measurement data in a protein reactions database.

22. A method for measuring a plurality of interacting molecules concurrently, the method to be performed by a system comprising: a protein reservoir configured to store proteins, an interaction species reservoir configured to store interaction species, a reaction chamber, a molecular analysis module, and at least one processor configured to execute the method, the method comprising: selecting, from the protein reservoir, by the at least one processor, a plurality of proteins to be interacted; selecting from the interaction species reservoir, by the at least one processor, at least one interaction species to be interacted, wherein the at least one interaction species and the plurality of proteins are determined according to at least one reaction pool of a pooling configuration, each reaction pool including at least two selected proteins from the plurality of proteins and a selected interaction species from the at least one interaction species;conducting, in the reaction chamber, individual reactions between the plurality of proteins and the at least one interaction species to generate a plurality of reaction output samples; and measuring the plurality of reaction output samples, wherein measuring includes concurrent measurement, by the molecular analysis module, of at least two of the reaction output samples of a reaction pool selected according to the pooling configuration.

23. The method of claim 22, wherein: the at least one interaction species includes a plurality of interaction species, the selected interaction species includes at least two interaction species, and the at least one reaction pool includes a plurality of reaction pools.

24. The method of any of claims 22-23, wherein concurrent measurement includes measurement of all of the reaction output samples associated with the reaction pool selected according to the pooling configuration.

25. The method of any of claims 22-24, further comprising providing, by the at least one processor to a sample handling system, control instructions to provide operative coupling between any combination of the protein reservoir, the interaction species reservoir, the reaction chamber, and the molecular analysis module, wherein operative coupling includes one or more of protein transfer, interaction species transfer, and reaction output sample transfer.

26. The method of any of claims 22-25, wherein the protein reservoir or the interaction species reservoir includes the reaction chamber27. The method of any claim 25, further comprising: conducting, in individual reaction vessels of the reaction chamber, one of the individual reactions to generate the plurality of reaction output samples; combining, by the sample handling system, the plurality of reaction output samples into at least one combined reaction output sample according to the pooling configuration, andmeasuring, by the molecular analysis module, the reaction output samples in the at least one combined reaction output sample.

28. The method of claim 23, further comprising: combining, by the sample handling system, the plurality of proteins with the at least one interaction species in the reaction chamber according to the pooling configuration; conducting, in the reaction chamber, a plurality of the individual reactions according to the pooling configuration to generate a combined reaction output sample; and measuring, by the molecular analysis module, the combined reaction output sample.

29. The method of claim 28, wherein the reaction chamber includes a plurality of individual reaction vessels, each individual reaction vessel being configured for concurrently conducting the plurality of the individual reactions according to the pooling configuration, and the molecular analysis module is configured to measure a plurality of combined reaction output samples.

30. The method of any of claims 22-29, further comprising sequentially measuring multiple combined reaction output samples, each associated with a different reaction pool.

31. The method of any of claims 22-30, further comprising adjusting reaction conditions in the reaction chamber by use of reaction components stored in a reaction components reservoir.

32. The method of any of claims 22-31, further comprising directly measuring at least one physicochemical property of reaction outputs associated with the plurality of reaction output samples.

33. The method of any of claims 22-32, wherein the molecular analysis module includes a mass spectrometer employing one or more techniques selected from the group consisting of Matrix- Assisted Laser Desorption / Ionization Time-of-Flight (MALD TOF), Electrospray Ionization Mass Spectrometry (ESLMS), Liquid Chromatography-Mass Spectrometry (LC-MS), Gas Chromatography-Mass Spectrometry (GC-MS), Inductively Coupled Plasma MassSpectrometry (ICP-MS), Direct Injection Mass Spectrometry (DIMS), Ion Trap Mass Spectrometry and Secondary Ion Mass Spectrometry (SIMS).

34. The method of any of claims 21-33, wherein the molecular analysis module includes at least one device selected from the group comprising: a spectrophotometer; a chromatography system; a Nuclear Magnetic Resonance (NMR) spectrometer; a fluorescence spectrometer; a Raman spectrometer; and a capillary electrophoresis system.

35. The method of any of claims 22-34, wherein the pooling configuration includes pairings between each of the plurality of proteins with each of the at least one interaction species.

36. The method of any of claims 22-35, wherein the plurality of proteins, the at least one interaction species, or both are label free.

37. The method of any of claims 22-36, further comprising obtaining, by the processor, the pooling configuration, the pooling configuration being determined according to at least one criterion.

38. The method of claim 37, wherein the at least one criterion includes a criterion that expected measurement results observable by the molecular analysis module of each reaction output sample associated with a reaction pool be differentiable.

39. The method of claim 37, wherein the at least one criterion includes a criterion based on physicochemical properties of the plurality of proteins and the at least one interaction species selected for each reaction pool.

40. The method of claim 37, wherein the at least one criterion includes a criterion based on one or more of: molecular weights of expected reactant products associated with each reaction pool, spectral characteristics of expected reactant products associated with each reaction pool, chromatographic behavior of expected reactant products associated with each reaction pool, ionization properties of expected reactant products associated with each reaction pool, chemical stability of expected reactant products associated with each reaction pool, chemical reactivity of expected reactant products associated with each reaction pool, or hydrophilicity and / or hydrophobicity of expected reactant products associated with each reaction pool.

41. The method of any of claims 22-40, further comprising demultiplexing the concurrent measurement to differentiate measurement results associated with each reaction output sample within the combined reaction output samples.

42. The method of any of claims 22-41, further comprising: obtaining, from the molecular analysis module, pool measurement data corresponding to measurements from a combined reaction output sample, demultiplexing the pool measurement data to obtain individual measurements of outputs of the individual reactions, wherein the individual measurements include positive indications of reactions between proteins and interaction species and / or negative indications of reactions between proteins and interaction species, and. storing the individual measurements as demultiplexed pool measurement data in a protein reactions database.

43. A method for measuring a plurality of interacting modules concurrently, the method to be performed by a system comprising: a protein reservoir, an interaction species reservoir, a reaction chamber, a molecular analysis module, andat least one processor configured to execute the method, the method comprising: selecting, by the at least one processor from the protein reservoir, a plurality of proteins to be interacted; selecting, by the at least one processor from the interaction species reservoir, at least one interaction species to be interacted, generating, by the at least one processor, a pooling configuration including one or more reaction pools, each reaction pool including at least two selected proteins from the plurality of proteins and a selected interaction species from the at least one interaction species; and for each of the plurality of pools: individually reacting, within the reaction chamber, the at least two selected proteins with the selected interaction species to generate a plurality of reaction output samples; and measuring the plurality of reaction output samples, wherein measuring includes concurrent measurement, by the molecular analysis module, of at least two reaction output samples in the plurality of reaction output samples.

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