338 results about "Molecular binding" patented technology

The invention discloses a molecular binding prediction model training method and device, equipment and a storage medium. Relates to the technical field of artificial intelligence. The method comprises the following steps: performing feature extraction on a sequence of a first biomolecule sample through a molecular binding prediction model to obtain a first feature; performing feature extraction on the sequence of the second biomolecule sample through a molecule combination prediction model to obtain a second feature; obtaining an interaction feature based on the first feature and the second feature through a molecular binding prediction model; obtaining a combination probability based on the first feature, the second feature and the interaction feature through a molecular combination prediction model; and adjusting parameters of the molecular binding prediction model based on the binding probability to obtain a trained molecular binding prediction model. By means of the method, the molecular binding prediction model can learn the interaction relation between the sequences of the biomolecules, and then the binding probability between the biomolecules can be predicted more accurately.

Provided herein are methods of performing multiplex detection of ligand binding kinetics. In some embodiments, the methods include contacting ligands with an array of nucleic acid barcoded oscillators disposed on a first surface of a substrate that comprises an electrically conductive coating, applying an AC electric field to the substrate sufficient to induce the nucleic acid barcoded oscillators to oscillate proximal to the first surface of the substrate, and detecting changes in oscillation amplitudes of the nucleic acid barcoded oscillators over a duration to produce sets of ligand binding data. In some embodiments, the methods also include contacting barcode decoding nucleic acids with the array of nucleic acid barcoded oscillators applying an AC electric field to the substrate sufficient to induce the nucleic acid barcoded oscillators to oscillate proximal to the first surface of the substrate, and detecting changes in oscillation amplitudes of the nucleic acid barcoded oscillators over a duration to produce sets of barcode decoding data.

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.

Described herein are platforms, systems, media, and methods for a machine learning-driven iterative drug discovery process. Some aspects comprise: receiving a first input data set comprising first binding interaction information between a target molecule and a library of compounds; processing the first input data set using a machine learning module to generate a model representation of binding interactions, wherein the representation is configured to predict binding between the target molecule and an input compound; determining an updated library of compounds using the model representation of binding interactions, wherein the updated library of compounds comprises one or more new compounds predicted to bind the target molecule; receiving a second input data set comprising second binding interaction information between the target molecule and the updated library of compounds; and processing the second input data set using the machine learning module to update the model representation of binding interactions, wherein the predictive accuracy of the updated model representation is improved.

The invention discloses a lateral flow chromatography test strip for detecting perfluorooctanoic acid by combining gold nanoparticles, a nucleic acid aptamer and an antibody. According to the test strip, a nucleic acid aptamer marked by gold nanoparticles is combined with PFOA molecules to form a nucleic acid aptamer with a G-quadruplex structure, and then the nucleic acid aptamer with the G-quadruplex structure is specifically recognized and captured by an anti-BG4 antibody, so that specific visual detection of perfluorooctanoic acid is realized. After a sample is injected, a G-quadruplex structure formed by the PFOA and the nucleic acid aptamer acts with the anti-BG4 antibody coated on the test strip, so that the gold nanoparticles are agglomerated to generate a chromogenic reaction, the signal intensity can be detected by naked eyes or reading equipment, the visual detection limit is 10 mu M, and the equipment detection limit is 304 nM. The test strip has the advantages of high detection speed, high specificity and high sensitivity, and is suitable for field detection and rapid screening. Compared with a traditional method, the method realizes simple, convenient and economical detection of PFOA, and has a wide application prospect.

The present invention discloses a method for predicting peptides that are capable of binding to HLA molecules that incorporate the crystal structure of HLA molecules. An improved HLA-specific peptide docking workflow is used to simulate the occupancy of a peptide on the binding pocket of an HLA molecule, and three models are trained to predict the binding of the peptide to HLA molecules. The results show that these models predict HLA-allele specific binding peptides with extremely high accuracy.

The present disclosure relates to a mammalian cell which is modified to express on the surface of its membrane a binding domain which binds to a target molecule. The disclosure also relates to protein constructs and nucleic acids for producing such modified mammalian cells, and to methods for using the mammalian cells to deliver therapeutic agents to target cells or tissues in vivo.

An iRGD-LAMP2B-EGFP fusion protein mediated exosome surface engineering strategy is adopted, through specific recognition of iRGD peptide and integrin alpha v beta 3, corneal neovascularization core lesion cells are actively targeted, the limitation of off-target toxicity of a traditional delivery system is broken through, and a'accurate focus recognition-efficient homing 'targeted delivery normal form is established. Meanwhile, the screened circular RNA with anti-inflammatory and anti-angiogenesis dual activities is used as a core effector molecule, and in combination with an in-situ loading technology of the circular RNA molecule in an exosome parent cell, stable entrapment and targeted release of a nucleic acid drug in an exosome cavity are realized, and the problems that the nucleic acid drug is easy to degrade and poor in targeting property are solved; and dual guarantee of function specificity and delivery stability is formed. And a synergistic treatment system of a targeting exosome carrier and bifunctional circular RNA is further constructed, active molecules are accurately delivered to focus cells, and an inflammation microenvironment and an angiogenesis pathway are synchronously regulated and controlled.

The invention relates to a small molecule detection method. The method comprises the following steps: forming a multi-component compound containing'a first compound antibody-small molecules / small molecule binding partner compound-a second compound antibody ', and detecting the small molecules in a sample by detecting the multi-component compound, the micromolecule binding partner can be specifically bound with micromolecules, has at least two antigen binding sites, and can be bound with at least two micromolecules to obtain the micromolecule / micromolecule binding partner compound. And forming at least two new conformational epitopes different from the small molecule in the free state and the small molecule binding partner in the free state; each of the first complex antibody and the second complex antibody specifically binds to at least one new conformational epitope, and neither the first complex antibody nor the second complex antibody is an antibody of the small molecule antigen nor a specific antibody of the small molecule binding partner.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for computationally designing a ligand for binding to a target molecule. In one aspect, a method comprises: obtaining target molecule data characterizing at least a portion of a target molecule; processing a network input comprising the target molecule data using an embedding neural network to generate latent conditioning data representing the target molecule; generating, using a generative model and while the generative model is conditioned on the latent conditioning data representing the target molecule, predicted ligand data defining a predicted ligand that is predicted to bind to the target molecule; and providing the predicted ligand data defining the predicted ligand.

The invention relates to the technical field of bioinformatics, and discloses an iterative feedback type protein targeting molecule intelligent generation method and device, and the method comprises the steps: obtaining molecular structure data, training based on the molecular structure data to obtain a molecular fragment language model, and the molecular fragment language model is used for predicting subsequent molecular fragments according to an input molecular fragment sequence; obtaining an attribute preference data set, and performing alignment fine tuning on the pre-trained molecular fragment language model based on the attribute preference data set to obtain an attribute preference alignment model; and obtaining target structure information of the target protein, taking the attribute preference alignment model as a strategy network, iteratively generating and evaluating candidate molecules through a tree search algorithm under the constraint of the target structure information until a termination condition is met, and outputting the optimized protein targeting molecules. According to the application, excellent pharmacological properties can be taken into account while the protein targeting molecule binding effect is ensured, and the molecule generation quality can be dynamically optimized.

The invention belongs to the technical field of protein function prediction, and relates to a recognition system for a natural disordered functional region. The system receives a protein sequence, converts the protein sequence into a sequence representation vector based on a protein language model, and outputs the sequence representation vector to a disordered binding region prediction model and a flexible connection region prediction model respectively. The disordered binding region prediction model is composed of a multi-scale feature processing module and a multifunctional classifier, and the disordered binding region and the binding molecule type thereof are speculated by predicting the probability that each residue in the sequence is located in a disordered region and is bound with five types of molecules including protein, nucleic acid and the like. The flexible connection region prediction model is composed of a single feature processing module and a single classifier, and can predict the probability that each residue in the sequence is located in the flexible connection region. The method has the beneficial effects that on a blind test data set provided by the natural disordered protein and the function prediction evaluation platform CAID of the natural disordered protein, the prediction precision is in the front, so that the method can realize accurate prediction of the disordered functional region.

In one aspect, the disclosure relates to compounds methods for treating or preventing diseases associated with aberrant condensation of a biomolecule in a subject, the method including at least the step of contacting one or more cells in the subject with a fusion protein that includes a J domain protein and a targeting molecule, wherein the targeting molecule binds the biomolecule. In one aspect, the biomolecule can be a target protein that may be mutated and / or include one or more intrinsically disordered regions. In another aspect, the targeting molecule can be a nanobody, but other targeting molecules are also contemplated. In still another aspect, the disclosed method is useful for treating and / or preventing cancers such as blood cancers and non-small cell lung cancer. Also disclosed are methods for disrupting condensates in cell culture.

The present disclosure relates to T-cell receptors (TCRs) that bind to tumor-associated antigens (TAA) for targeting cancer cells, T-cells expressing them, methods for producing them, and methods for treating cancers using them. In particular, the present disclosure relates to TCRs and variants thereof that bind to HLA class I or II molecules with a peptide, such as IGF2BP3-001 having the amino acid sequence KIQEILTQV (SEQ ID NO:1). The present disclosure further relates to peptides, proteins, nucleic acids, and cells for use in immunotherapeutic methods. In particular, the present disclosure relates to cancer immunotherapy.The present disclosure further relates to tumor-associated T-cell peptide epitopes, alone or in combination with other tumor-associated peptides, which can for example serve as active pharmaceutical ingredients in vaccine compositions that stimulate anti-tumor immune responses or stimulate T-cells ex vivo and deliver them to patients. Peptides bound to major histocompatibility complex (MHC) molecules, or the peptides themselves, can also be targets of antibodies, soluble T-cell J receptors and other binding molecules.

The present invention relates to the technical field of in-vitro testing, and in particular to a method for using a sandwich method to test a target molecule in a sample. The present invention provides a method for testing a target molecule in a sample under test, and testing is mainly performed by mean of a sandwich method, greatly improving the accuracy of testing of small molecules in serum. According to the method in the present invention, a complex-specific antibody specifically binding to a target molecule-target molecule binding protein is utilized to form a target molecule-target molecule binding protein-antibody ternary complex for testing. When a blood / serum sample containing the target molecule-target molecule binding protein is tested, in the method in the present invention, firstly, a specific dissociation solution is utilized to treat the sample under test so as to dissociate the target molecule from the target molecule-target molecule binding protein complex in the sample under test, so that the accuracy of testing of the target molecule can be further improved.

The present invention provides molecules that bind to cellular components or parts thereof (e.g., filaments or histones forming the cytoskeleton or nucleoskeleton) that are exposed to the extracellular environment upon cell death, which are specifically observed in diseased tissues, and simultaneously bind to target molecules on or in cells that act specifically in tissues where cell death is observed, such as diseased tissues, abnormal tissues, etc. The molecules of the present invention are useful as drugs that provide significant therapeutic or preventive effects while reducing side effects.

Bispecific binding molecules are disclosed that bind to human MUC16 and human death receptor 5, and can kill cancer cells expressing MUC16 and death receptor 5. Also disclosed are pharmaceutical compositions comprising these antibodies, and methods of treatment for using these antibodies.

The present invention provides a method for screening for a candidate peptide capable of binding to a target molecule, the method including the steps of: (1) preparing a plurality of nucleic acid display libraries containing a barcoded peptide-nucleic acid complex, wherein the barcoded peptide-nucleic acid complex contains a nucleic acid moiety and a peptide moiety, the nucleic acid moiety contains a barcode sequence and a nucleic acid sequence encoding the peptide, and the plurality of nucleic acid display libraries are nucleic acid display libraries, each of which is independently produced by translation using a cell-free translation system; (2) mixing the plurality of nucleic acid display libraries to prepare a mixed nucleic acid display library; (3) bringing the mixed nucleic acid display library into contact with the target molecule; and (4) amplifying a nucleic acid corresponding to the nucleic acid moiety of the barcoded peptide-nucleic acid complex bound to the target molecule, using a barcode primer.

The present invention relates to a method for using an optionally alkoxylated nitrogen-containing polymer in the capture of carbon dioxide, said optionally alkoxylated nitrogen-containing polymer comprising the following steps: a) a step of reacting (i) a di- or oligoamine (A) with (ii) a crosslinking compound (BC) to provide a nitrogen-containing polymer (NP), wherein the crosslinking compound (BC) is (I) phosgene; or (II) comprises at least two amine-reactive groups (ARG), the crosslinking compound (BC) being capable of binding to the amine groups of at least two di- or oligoamine (A) molecules, the nitrogen-containing polymer (NP) comprising the molecular components of the crosslinking compound (BC) that bind to at least two molecular components of the di- or oligoamine (A), the proportion of the crosslinking compound (BC) molecules bound to at least two di- or oligoamine (A) molecules being the crosslinking factor (BF) of the nitrogen-containing polymer (NP), the crosslinking factor (BF) exceeding 50%, the sum of the primary and secondary amine groups of the nitrogen-containing polymer (NP) being at least 600 mg KOH / g, the number average molecular weight (Mn) of the nitrogen-containing polymer (NP) exceeding 600 g / mol, and b) a step of reacting the nitrogen-containing polymer (NP) with an alkylene oxide (AO), wherein the molar ratio of the alkylene oxide (AO) to the NH functionality of the nitrogen-containing polymer (NP) is 0.25 or less, obtainable by a method comprising. The present invention further relates to a method for capturing carbon dioxide from a gas mixture using an optionally alkoxylated nitrogen-containing polymer.

Provided herein are components for antigen-binding constructs, including antibodies and fragments thereof, such as minibodies and cys-diabodies, that bind to target molecules, e.g., DLL3. In some embodiments, these components are novel complementarity-determining region (CDR) sequences and / or sequences related to and / or portions of CDR sequences. In some embodiments, these components are novel framework region (FR) sequences and / or sequences related to and / or portions of FR sequences. These CDR and FR sequences may provide various benefits. Also provided herein are antigen-binding constructs (minibodies, cys-diabodies, etc.) that include one or more of the CDR or FR sequences or subsequences provided herein.

Described herein is an isolated cell comprising a recombinant T cell receptor (TCR) and a TCR pathway-dependent reporter, wherein the recombinant T cell receptor is specific for a disease-associated antigen bound to an MHC molecule. Also described is an assay for the isolated cell for determining the function or efficacy of a peptide-major histocompatibility complex (pMHC) (pMHC-NP) coupled to a nanoparticle, which can be used as a drug for treating autoimmune diseases or cancer.

This application provides a method for screening inhibitors targeting CYP7A1 and their use in the preparation of anti-liver cancer drugs, relating to the field of tumor targeted drug design technology. The method for screening inhibitors targeting CYP7A1 protein includes: using the crystal structure of human cholesterol 7α-hydroxylase as a receptor model, precise docking screening is performed using software to screen drug-like molecules with molecular weights of 250-500 Da and lipid-water partition coefficients of -1 to 5 from a compound database; a graph neural network active learning model is used to predict and rank the protein-small molecule binding affinity of compounds in the database; the ΔG between candidate molecules and CYP7A1 is calculated using molecular mechanics / generalized Born surface area methods, with molecules having ΔG ≤ -40 kcal / mol considered potential inhibitors. The inhibitors of this application do not rely on the enzymatic activity of CYP7A1 to achieve anti-tumor effects and do not significantly affect cholesterol and bile acid metabolism levels.

According to the preparation method for improving the metal / polymer bonding strength, a polar polymer film layer is pre-plated on the metal surface, the prepared polar polymer film layer and the metal surface containing hydroxyl generate intermolecular acting force, polymer entanglement occurs between the prepared polar polymer film layer and a polymer plate in subsequent thermal connection, and finally the metal / polymer interface acting force is enhanced; and the interface heat transfer efficiency is improved, the interface temperature is increased to 378 DEG C from 331 DEG C, and the metal / polymer interface connection area is increased to 224 mm < 2 > from 179 mm < 2 >. The metal / polymer interface bonding strength is improved by enhancing the metal / polymer interface acting force and improving the interface heat conduction efficiency, the film thickness control freedom degree is high, the film with any thickness can be obtained by controlling spin-coating parameters, and the method has the advantages of being easy to prepare, high in processing efficiency, low in economic cost and wide in application range.

The invention relates to a dehydroepiandrosterone carboxylic acid NHS active ester marker as well as a preparation method and application thereof, dehydroepiandrosterone is selected as an initial raw material of a competitive antigen, the source is wide, the cost is low, dehydroepiandrosterone carboxylic acid NHS active ester is prepared through a two-step reaction, the dehydroepiandrosterone carboxylic acid NHS active ester can be used as an active intermediate, and the dehydroepiandrosterone carboxylic acid NHS active ester marker can be used as a competitive antigen. As a marker for binding protein or other molecules; for example, the dehydroepiandrosterone sulfate magnetic particle chemiluminescence immunoassay reagent with high sensitivity and good specificity can be prepared at low cost.

The invention discloses a microneedle patch for in-vivo space-time omics analysis and a preparation method and application thereof, and belongs to the technical field of gene detection. Comprising the following steps: performing high-density modification on the surface of the microneedle for molecular binding; preparing a micro-needle base grinding tool for constructing a micro-needle patch; connecting the universal primer probe and the capture primer probe to the bar code probe; the microneedle patch captures to-be-detected molecules in a living body in situ; a probe complementary with the strand displacement region is added, polymeric strand displacement is carried out, and the obtained product can be used for constructing a sequencing library to realize spatial omics analysis of a living sample; the microneedle after strand displacement can be coupled with the bar code probe again to realize reuse of the microneedle for a new round of reaction. According to the method, the analysis of the spatial group in the living body sample is realized at extremely low cost, the operation is simple, the application field is wide, and the method can be used for detecting genomes, transcriptomes, proteomes, epigenomes, metabolomes and the like.

A method for detecting a target of interest in a tissue sample is disclosed. The method includes: a) obtaining or having obtained a tissue sample, the tissue sample comprising DNA, non-RNA molecules, and RNA, the RNA comprising the target of interest; b) permeabilizing the tissue sample; c) substantially degrading DNA in the tissue sample; d) introducing primers or probes specific for the target of interest into the tissue sample, wherein the primers or probes bind to the target of interest; and e) detecting the target of interest in the tissue sample by detecting the primers or probes bound to the target of interest. A method for producing a hydrogel within the tissue sample is also disclosed.

The invention relates to the technical field of active ingredient extraction, and particularly provides an extraction method for classifying and screening active ingredients, raw materials are subjected to low-temperature freeze-drying pretreatment by adopting supercritical CO2, and treatment is performed for 4-6 hours under the conditions of minus 40-minus 20 DEG C and 8-12 MPa, so that the active ingredients are reserved to the greatest extent; through gradient ultrasonic-assisted extraction of ultrapure water, a 50% ethanol solution and a 95% ethanol solution, step-by-step separation of water-soluble, alcohol-soluble and fat-soluble components is realized; carrying out multi-dimensional purification by using a composite chromatographic column containing a 0.2 mu m ceramic membrane layer, a macroporous adsorption resin layer and a sephadex layer; a two-channel biosensor array is adopted to synchronously detect a cell response signal and a molecule binding signal, and components with the activity intensity reaching 80% or above are screened; and finally, carrying out vacuum rotary evaporation concentration and spray drying to obtain a finished product, and completing system purity verification through a high performance liquid chromatography-mass spectrometry technology to form a complete quality control system.

The present invention relates to peptides, proteins, nucleic acids and cells for use in immunotherapeutic methods. In particular, the present invention relates to the immunotherapy of cancer. The present invention furthermore relates to tumor-associated T-cell peptide epitopes, alone or in combination with other tumor-associated peptides that can for example serve as active pharmaceutical ingredients of vaccine compositions that stimulate anti-tumor immune responses, or to stimulate T cells ex vivo and transfer into patients. Peptides bound to molecules of the major histocompatibility complex (MHC), or peptides as such, can also be targets of antibodies, soluble T-cell receptors, and other binding molecules.

Described herein are interferometric sensors that can be used for biochemical testing. Each interferometric sensor includes an interference layer immobilized along a surface of a monolithic substrate. Analyte binding molecules can be coated along a surface of the interference layer. During biochemical testing, when analyte molecules in a sample bind to the analyte binding molecules, a biological layer will form. The monolithic substrate has a higher refractive index than the interference layer. Furthermore, the interference layer can be designed to have a refractive index that is substantially similar to a refractive index of the biological layer.

The invention discloses a small molecule binding protein design method. The method comprises the following steps: S1, a structure acquisition step: acquiring a compound structure of a target small molecule ligand and protein; s2, a candidate sequence generation step: generating a candidate protein sequence set by adopting a protein generation model and adjusting parameters corresponding to the protein generation model according to the compound structure in the step S1; s3, a primary screening step; compounding the candidate protein sequence set in the step S2 with the small molecule ligand in the step S1, predicting a compound structure I, and screening a potential sequence from the compound structure I; s4, a fine screening stage: compounding the potential sequence screened in the step S3 with the small molecule ligand in the step S1, predicting a compound structure II, and screening a preferred protein sequence I from the compound structure II. Through deep fusion of AI generation and physical screening, a layer-by-layer progressive accurate screening funnel is constructed, and the false positive rate is greatly reduced.