47 results about "Molecular interactions" patented technology

The invention relates to a UCNPs probe-based in-situ dynamic monitoring molecular interaction method, which comprises: S1, providing a UCNPs probe, the core layer of the UCNPs probe being a rare earth up-conversion nanocrystal, the shell layer of the UCNPs probe being an anti-quenching inert material, and the anti-quenching inert material coating the surface of the rare earth up-conversion nanocrystal; the surface of the anti-quenching inert material is modified with ligand molecules, and the ligand molecules are used for being specifically combined with target molecules in a to-be-detected sample; s2, mixing or contacting the UCNPs probe with a to-be-detected sample containing target molecules to construct a to-be-analyzed molecular interaction system; s3, irradiating the molecular interaction system by adopting near-infrared pulse laser, and collecting the change of the fluorescence lifetime tau of the UCNPs along with the time t and the change of the fluorescence intensity I along with the time t in real time to obtain a tau-t curve and an I-t curve; and S4, according to the tau-t curve and the I-t curve, realizing in-situ dynamic monitoring on the molecular interaction state. According to the method, a molecular binding / dissociation event is directly converted into a quantifiable and anti-interference optical signal, and the technical defect that in-situ dynamic monitoring of molecular interaction cannot be achieved in a traditional technology is overcome.

This invention discloses a ferroptosis target identification system and method based on an attention mechanism, belonging to the field of artificial intelligence technology. The system includes modules for extracting multi-source features of ferroptosis regulation, labeling weak signal targets, calculating attention potential energy mapping, and ranking ferroptosis targets. It extracts multimodal features from transcriptome expression, molecular interaction networks, and ferroptosis pathway annotations. Targets with expression intensities below a preset threshold that participate in the ferroptosis pathway are labeled with weak signals. Weak signal characteristics are injected, and a potential energy bias is constructed to complete attention potential energy mapping. Then, through pathway mapping and cross-pathway linkage identification and fusion weights, the target linkage degree is calculated and ranked. This system solves the problem of traditional methods easily neglecting weak signal targets, and can identify targets with insignificant expression changes in the ferroptosis regulatory network. Through attention and pathway-level linkage modeling, the comprehensiveness of target identification is improved, and the obtained ranking results have stability and discriminative power, making it suitable for the identification and research of ferroptosis-related targets.

The invention discloses a method and system for predicting the effect of repairing lung injury by isoliquiritigenin based on machine learning, and relates to the field of drug effect prediction.The method comprises the steps that biomarker data and historical experiment repairing effect data are obtained; on the basis of molecular structure data and biomarker data, calculating a molecular interaction force index and a cell permeability index of the isoliquiritigenin, and analyzing through a multiple regression analyzer in combination with historical experiment repair effect data to obtain a repair effect coefficient; according to the repair effect coefficient, configuring an effect confidence interval, and performing range optimization on the molecular interaction force index and the cell permeability index to obtain an optimized biological activity index; and constructing an effect prediction model based on a neural network, inputting the optimized biological activity indexes into the effect prediction model, and outputting to obtain a lung injury repair effect prediction value. The problems that the prediction precision is insufficient and the prediction is too one-sided due to the lack of comprehensive analysis on a molecular mechanism and a biomarker are solved.

The invention relates to a postoperative acute pain prediction method, belongs to the technical field of medical data analysis and processing, and solves the problem of insufficient postoperative acute pain prediction precision in the prior art. The method comprises the following steps: acquiring multi-omics data and clinical data of a to-be-predicted patient; constructing a primary network of each omics based on the anchor point molecules of each omics; the second-level network and each later-level network are obtained by expanding the previous-level network based on the molecular interaction relationship; taking each level of network as a multi-level molecular interaction network of the to-be-predicted patient; adopting a trained deep learning model to extract high-dimensional biological characteristics of a to-be-predicted patient based on the multistage molecular interaction network; and predicting the pain type of the to-be-predicted patient based on the high-dimensional biological characteristics, the multi-omics data and the clinical data. And the accuracy of postoperative acute pain prediction is improved.

The present disclosure provides an affinity prediction method, related devices and media. The method comprises: determining a first molecular structure graph and an atomic structure graph of a first biomolecule, and a second molecular structure graph of a second biomolecule; intercepting a binding region graph from the second molecular structure graph; extracting a first graph feature of the first molecular structure graph, a second graph feature of the atomic structure graph, a third graph feature of the second molecular structure graph, and a fourth graph feature of the binding region graph based on a feature extraction network of a preset affinity prediction model; determining a molecular interaction feature based on the first graph feature, the second graph feature, the third graph feature, and the fourth graph feature; and performing affinity prediction on the first biomolecule and the second biomolecule based on the molecular interaction feature to obtain a binding affinity prediction result. The present disclosure can improve the prediction accuracy of the binding affinity between biomolecules. The present disclosure can be applied to various scenarios such as big data, artificial intelligence, cloud technology, etc.

A contrast agent for magnetic resonance imaging (MRI) is proposed, comprising a polarizable agent (tracer) possessing a nuclear spin, wherein tracer molecules can be brought into a polarized state by polarizing their nuclear spins, and a retarder, wherein a molecular interaction of retarder molecules with the tracer molecules results in a prolongation of the T1 relaxation time of the tracer. Furthermore, a method for the production of a hyperpolarized contrast agent, a retarder for use in a contrast agent for MRI, a contrast agent for use in a diagnostic procedure in vivo and / or in vitro, and the use of a retarder in a contrast agent for MRI to prolong the T1 relaxation time of the tracer are proposed.

Disclosed is a method for calculating an eigenstate of a Hamiltonian, comprising the steps of providing at least one classical computing unit and at least one quantum computing unit comprising a plurality of qubits, providing a plurality of physical properties of at least one molecule, initializing an initial state on the at least one quantum computing unit to model the properties of the provided physical properties of the at least one molecule, selecting a plurality of operators from a pool of operators using the at least one quantum computing unit performing measurement operations on the diagonal of the Hamiltonian to calculate the eigenstate of the Hamiltonian describing the at least one molecule, estimating an energy of the eigenstate of the Hamiltonian using the selected plurality of operators, and repeating the previous steps until a convergence criterion is met.

Provided herein are computer-implemented methods for scoring a binding affinity between molecular subsystems. The methods include representing an interaction structure of the molecular subsystems, calculating the molecular interactions between the molecular subsystems, and generating an interaction energy score between the molecular subsystems.

The invention discloses a Leidenfrost effect three-dimensional numerical simulation method based on a double-distribution function lattice Boltzmann method coupled with a finite difference method. The method comprises the following steps: 1, constructing a three-dimensional computational domain and defining lattice point types; 2, initializing a lattice point type, a fluid domain density field, a velocity field, a temperature field and a distribution function; 3, calculating fluid domain density, pressure and thermal diffusion coefficient according to the distribution function; 4, calculating resultant force of molecular interaction force and volume force among different phase states based on a pseudo-potential model; 5, calculating a fluid domain collision process; 6, calculating a migration process; 7, treating wall surface boundary conditions; 8, updating the fluid domain temperature field by using the temperature distribution function, and updating the solid domain temperature field by using a finite difference method; and 9, carrying out loop iteration on the steps 3-8 until the preset simulation time is reached. According to the invention, the whole process of the Leidenfrost phenomenon generated when the liquid drops impact the high-temperature wall surface can be stably and accurately simulated, and an accurate and reliable numerical simulation tool is provided for the design of efficient heat dissipation schemes such as spray cooling and the like.

A sensor has a radiation emitter, a plurality of electrodes, a sensing material (transducer), and a recognition element (receptor, bioreceptor). The radiation element irradiates the sensing material, the plurality of electrodes are in electrical contact with the sensing material, and the recognition element is in contact, either directly or through an interface, with the sensing material. The sensing material receives radiation from the radiation source and interacts with the target material largely through the receptor. Further, the sensing material generates a measurable electrical signal upon interaction with a target molecule, when a potential is applied to the electrodes.

The invention relates to a method and a system for constructing a free energy surface of a molecular binding / dissociation path. The construction method of the free energy surface of the molecule binding / dissociation path comprises the following steps: quantifying the relevance of an atom pair distance / angle and a binding state by adopting a mutual information analysis method so as to screen out candidate reaction coordinates; performing short-time pre-simulation verification on the candidate reaction coordinates to determine dominant reaction coordinates; taking the dominant reaction coordinates as navigation, and carrying out adaptive path sampling through reinforcement learning to obtain an optimized path; and calculating free energy of the optimized path, and constructing a free energy surface of the molecular binding / dissociation path based on the obtained free energy. According to the method, the dominant reaction coordinates are automatically identified, and the adaptive path sampling technology is adopted, so that the problems of subjectivity and intermediate state omission of a traditional fixed reaction coordinate method can be solved, the calculation precision and efficiency of a free energy surface can be improved, and a more reliable theoretical tool is provided for molecular interaction mechanism research.

This invention discloses a dual-functional aqueous zinc-ion battery high-voltage electrolyte, its preparation method, and its application, belonging to the field of aqueous zinc-ion battery technology. The invention uses additives with the general structural formula R consisting of hydroxyl, carboxyl, acetyl, and methoxy groups to prepare the electrolyte. These additives contain oxygen-containing functional groups that can act as hydrogen bond acceptors, significantly improving the aqueous solubility of the molecules. Furthermore, they can regulate the electrolyte ion concentration through specific interactions with solvent molecules, thereby controlling the solvation sheath structure of zinc ions by reducing the number of solvent molecules. Simultaneously, these functional groups containing oxygen atoms as hydrogen bond acceptors are strong electron-withdrawing groups, capable of interacting with water molecules to form intermolecular hydrogen bonds. The oxygen atom acts as an electron donor, and the hydrogen atoms in water act as proton donors, disrupting the original hydrogen bonds and tetrahedral structure of water molecules. By blocking the formation of the hydrogen bond network of water molecules, this effectively inhibits water-induced corrosion side reactions and hydrogen evolution behavior.

The invention relates to a contrast agent for nuclear spin imaging, comprising a polarizable agent (tracer) having a nuclear spin, tracer molecules being polarizable by polarizing the nuclear spins thereof, and comprising a retarding agent (retarder), a molecular interaction of retarder molecules with tracer molecules resulting in an extension of the T1 relaxation time of the tracer. The invention further relates to a method for producing a hyperpolarized contrast agent, to a retarder for use in a contrast agent for nuclear spin imaging, to a contrast agent for use in an in vivo and / or in vitro diagnostic method, and to the use of a retarder in a contrast agent for nuclear spin imaging in order to extend the T1 relaxation time of the tracer.

The invention discloses an ellagic acid composite solid dispersion and a preparation method thereof. The preparation method comprises the following steps: S1, respectively preparing a fucoidin aqueous solution and an ellagic acid ethanol suspension; s2, mixing the two solutions to obtain a mixed solution; s3, adding the modified polysorbate 20 and the chitosan-CPP compound, and performing ultrasonic stirring; s4, ball milling; and S5, carrying out reduced pressure rotary evaporation to remove the solvent, drying, crushing, and sieving with a 100-mesh sieve to obtain the product. Ternary synergistic compounding is formed through the fucoidin-modified polysorbate 20-chitosan-CPP compound, a multi-dimensional molecular interaction network is constructed, and the effect of remarkably improving the water solubility and dispersion stability of ellagic acid is achieved; wherein xylooligosaccharide branched chains of the modified polysorbate 20, hydroxyl groups of the fucoidin and phosphate groups of the chitosan-CPP compound form a multi-point hydrogen bond cross-linked structure through hydrogen bonds, and the hydrophobic association effect and lattice stacking among ellagic acid molecules are broken through the steric hindrance effect.

The invention relates to the technical field of bioinformatics and functional food development, and discloses a plant-source alpha-amylase inhibitory peptide high-throughput screening method and application thereof.The method comprises the steps that firstly, white kidney beans are selected and subjected to wall breaking and degreasing treatment, and efficient extraction is conducted; a three-stage gradient process is adopted for enzymolysis, and a series ultrafiltration membrane system is adopted for refining white kidney bean protein; separating white kidney bean protein, performing high-precision mass spectrum identification, screening peptide fragments, and constructing a candidate database; constructing a peptide-amylase molecular interaction screening network; collecting alpha-amylase inhibitory peptide data to carry out data enhancement, training a PAMIS-Net model, and carrying out model performance optimization; inputting the optimized PAMIS-Net model into the database in batches to intelligently screen high-activity candidate peptide fragments, and establishing a comprehensive scoring model for experimental verification; according to the method, the problems of low screening efficiency and poor prediction precision of the active peptide caused by difficulty in integration of multi-dimensional information such as sequences, structures and physicochemical properties in the prior art are solved.

A multi-modal surface plasmon resonance detector for measuring molecular interactions is provided herein. The multi-modal surface plasmon resonance detector includes a detector frame manufactured by metal additive manufacturing, the detector frame comprising integrated conformal cooling passages. The multi-modal surface plasmon resonance detector includes a prism providing a plurality of optical faces for a plurality of optical paths. The multi-modal surface plasmon resonance detector includes a first detection path configured for surface plasmon resonance detection. The multi-modal surface plasmon resonance detector includes a second detection path configured for surface plasmon resonance imaging. The multi-modal surface plasmon resonance detector includes a sensor chip interface configured to receive a sensor chip. The multi-modal surface plasmon resonance detector includes a liquid cooling system configured to circulate liquid through the integrated conformal cooling passages.

This application discloses a method, apparatus, device, and medium for determining the force field parameters of fluorinated compounds in some embodiments. In this method, multi-orientation scanning captures anisotropic features that can comprehensively cover molecular interactions, adaptive Boltzmann weighting factors can automatically focus on thermodynamically probable regions, and effective temperature fitting can achieve wide temperature range adaptation, thereby improving the accuracy of determining the force field parameters of fluorinated compounds.

The application discloses a kind of metal organic framework UiO-66 modified terahertz super surface detection lung cancer marker 2-pentanone method.The method is based on a kind of terahertz multi-resonance super surface sensor, and its unit structure is composed of two S-shaped open resonant ring and an antenna, produces three independent resonant valleys.To improve detection selectivity and structural stability, the application is functionalized to super surface using three-layer modification strategy: APTES is introduced in sequence to form stable interface layer, spin-coated amino-rich PEI layer is provided with additional adsorption sites to interact with ketone molecules, and finally spin-coated metal organic framework UiO-66 is used as sensing layer to realize effective pre-enrichment of 2-pentanone.During detection, three resonant valleys show linear red shift with the increase of 2-pentanone concentration, and the lowest test concentration is 20 ppm.The application uses multi-resonance characteristics combined with multi-dimensional response mode to realize rapid, high-sensitivity and high-selectivity non-contact detection of lung cancer marker 2-pentanone.

The invention discloses umami peptide from euphausia superba and application of the umami peptide, and belongs to the technical field of bioactive peptide. The number of the umami peptides from the euphausia superba is five, and the amino acid sequences of the umami peptides from the euphausia superba are shown as SEQ ID NO.1 The umami peptide can be used as or used for preparing a flavor enhancer. According to the method, the antarctic krill protein is taken as a raw material, virtual hydrolysis is carried out, joint screening is carried out by adopting an umami peptide prediction model, and through physicochemical property prediction, five potential umami peptides which are non-toxic and good in water solubility are finally obtained. Molecular interaction analysis shows that the umami peptide can be stably combined with a T1R3 key site, and the interaction mainly comprises non-covalent acting forces such as hydrogen bonds and hydrophobic interaction. The invention constructs a screening and mechanism analysis strategy of the antarctic krill umami peptide based on combination of virtual enzymolysis, multi-model prediction and molecular docking, and provides a theoretical basis for directional development of natural umami peptide and high-valued utilization of antarctic krill marine protein resources.

This invention relates to methods, components, and systems for determining characteristic properties of molecular interactions. The method includes providing a liquid sample comprising particles capable of being in equilibrium and non-equilibrium states. The particles comprise a marker in at least one of their equilibrium and non-equilibrium states. The method further includes subjecting the sample to a conditional transition including a temperature jump and / or a pressure jump, bringing the particles to a non-equilibrium state; reading out the marker as a function of time during at least a portion of the relaxation time of the particles; and determining the characteristic properties of the molecular interactions.

The invention discloses a drug interaction prediction method and device for an ADME process and a medium, and relates to the technical field of medicine. The method is applied to a drug interaction prediction model obtained by training a TRACE model, and comprises the processes of enhanced molecular map construction, feature extraction and prediction. According to the method, external chemical knowledge (chemical element knowledge graph) is introduced in a molecular graph construction process, so that the modeling capability of the model on a molecular complex structure and a long-range dependency relationship is improved, and the adaptability to a traditional Chinese medicine complex component system is remarkably enhanced; the TRACE model adopted by the invention can automatically identify high-risk substructures closely related to the ADME process, and a scientific and efficient solution is provided for safety evaluation and druggability prediction of drug combination of traditional Chinese medicine components and chemical drugs thereof. The risk of molecular interaction in the new drug research and development process and the traditional Chinese medicine modernization process can be effectively reduced, and the improvement of the drug safety management level is promoted.

The invention discloses a chemical evolution prediction method based on a spectroscopy inversion neural network algorithm, and relates to the technical field of inversion prediction. According to the method, a chemical and material database is firstly constructed, so that data support is provided for subsequent prediction; the molecular descriptor fusing the spectral characteristics, the microstructure and the physical property associated information is generated, and the defects that a traditional molecular descriptor is single in information and insufficient in representativeness are overcome; the molecular descriptor is used as input, a spectrum structure-effect relationship prediction model with common feature extraction and multi-branch special prediction capabilities is constructed, and spectrum-structure, structure-effect and spectrum-effect associated synchronous precise learning is realized; the compatibility and reliability of the input data and the model are ensured by carrying out noise reduction and standardization preprocessing on the target spectroscopic data subsequently, and finally, chemical structure change parameters, molecular interaction rules and physical property evolution trend data are directly output through model inversion, so that the defects that a traditional method needs multi-step splitting and experimental verification is tedious are avoided.

The utility model relates to the technical field of sample preparation, in particular to a molecular interaction sample preparation system, which is used for sample preparation and concentration preparation of a molecular interaction instrument, and comprises a base, a sample tray, a sample preparation device and a sample preparation device, the composite pipetting device is arranged above the base, and the composite pipetting device comprises an eight-channel pipetting module which is used for executing simultaneous pipetting operation of a plurality of samples and is suitable for batch sample treatment and gradient dilution; the single-channel pipetting module is used for transferring and distributing small-volume samples and is suitable for micro-sample treatment; and the composite moving device is used for driving the eight-channel pipetting module and the single-channel pipetting module to move in the horizontal direction and the vertical direction. The scheme is used for supporting sample preparation and concentration preparation work of molecular interaction instruments such as a surface plasmon resonance instrument (SPR), a biological layer interference analyzer (BLI) and a micro thermophoretic mover (MST).

Compositions, methods, and kits for performing multiplexed, spatially resolved, or single-cell chromatin analysis are provided.

A system for characterizing chiral molecules including an interaction zone arranged to receive a sample of chiral molecules; a laser source arranged to emit pulsed laser radiation, the laser radiation being suitable for interacting with the molecules in the interaction zone; a polarization modulator arranged to elliptically polarize the laser radiation; an optical cavity configured to redirect the pulsed laser radiation into the interaction zone several times; a detector arranged to measure a chiroptical signal produced by the interaction between the molecules and the laser radiation; and a determiner arranged and / or programmed to determine at least the chirality of the molecules from the detected chiroptical signal.

The present invention relates to a method of querying a molecular interaction between a first and a second partner moiety wherein the first partner moiety is joined to a first partial effector sequence and the second partner moiety is joined to a second partial effector sequence. The first part effector sequence and the second part effector sequence form a function-separated HaloTag system. The first partner is a peptide sequence encoded by a polynucleotide sequence and physically contiguous with the polynucleotide sequence. The method according to the invention comprises the steps of: a) contacting a first partner moiety with a second partner moiety in the presence of a HaloTag substrate covalently linked to a separation function; b) separating the first partner part attached to the separating function; c) determining the molecular interaction between the first partner part and the second partner part by detecting the presence of the polynucleotide sequence.

The application discloses a multi-channel molecular interaction detection device and method based on imaging and photoelectric array detection, and relates to the technical field of molecular interaction detection. The device comprises a multi-channel optical fiber array, an imaging optical system, a photoelectric detection unit and a signal processing module. The imaging optical system can perform spatial separation imaging on multiple light signals, or perform time sequence separation imaging through a high-speed shutter and channel polling. The photoelectric detection unit adopts a CMOS / CCD area sensor, a photodiode array or a photomultiplier tube array, so that a single detection module replaces traditional multiple spectrometers. The signal processing module realizes non-crosstalk signal extraction and analysis of each channel through ROI partition, time sequence division or channel addressing. The application can be compatible with multiple signals such as biological layer interference spectrum, laser reflection spectrum and up-conversion nanometer material probe emission spectrum, has the advantages of low cost, small size, high channel consistency and strong expansibility, can effectively suppress channel crosstalk, and is suitable for high-throughput detection scenes.

The invention belongs to the technical field of SERS (Surface Enhanced Raman Scattering) detection, and particularly relates to a preparation method and application of an Ag / MnFe2O4 composite SERS substrate. According to the preparation method disclosed by the invention, the MnFe2O4 semiconductor and the Ag nano material are controllably compounded, so that the SERS active substrate with multiple functions is constructed. The invention provides a charge transfer mechanism of a semiconductor-noble metal interface in a composite system, clarifies a regulation and control rule and a driving mechanism of the charge transfer mechanism on molecular interaction, further develops an efficient and sensitive novel molecular detection method, and provides a new technical scheme for rapid detection of organic pollutants.

An apparatus is provided that introduces rapidly spinning vortices in a fluid, including water. It incorporates a fluid system, or fluid source, with a vortex creation apparatus and a frequency generation device. The vortices prepare the fluid to have memorized electromagnetic frequency signatures of harmful materials erased, and a new, desirable signature introduced. The desirable frequency can be introduced though a number of means, such as an electrical frequency generator. The desirable frequencies make the fluid an inhospitable environment for biological contaminants, such as bacteria, algae, and fungi, reducing their numbers in the fluid. A portion of the fluid may be passed through a plurality of micro-spheres to interact with the water molecules to polarize mineral salts preventing the formation of deposits on the inside of related plumbing. The apparatus further includes an integral cleaning system and method that periodically detects when the micro-spheres lose their effectiveness due to a coating of mineral deposits contained in the fluid and dispenses a biologic cleaning fluid to cleanse the micro-spheres.

This invention discloses a microarray spectral scanning analysis system based on a spatiotemporally continuous temperature gradient, belonging to the fields of spectral analysis and precision automation technology. It includes a sample reservoir, a sample cell, a sample introduction module, a temperature control module, an optical path module, a motion device, and a spectral detection and analysis unit. The sample cell corresponds to the outlet end of the sample introduction module and serves as a sample carrier accessory for detection. The sample introduction module establishes the sample introduction relationship between the sample cell and the sample reservoir by closing or opening one or more channels, or by spotting or injecting samples. The temperature control module uses real-time or time-sharing detection during temperature increase. The spectral detection and analysis unit is used for axial scanning detection relative to the sample cell. This invention can, with the aid of a single device, simultaneously or almost simultaneously measure three spectral characteristics of the sample, including any combination of light scattering, fluorescence, and absorbance. Furthermore, it can obtain information such as molecular interactions, stability, particle size, dispersion, aggregation, and viscosity through mathematical models or calculations.