149 results about "Target binding" patented technology

The invention discloses a resource binding method, electronic equipment and a storage medium. The method comprises the steps that in response to an interrupt request to be processed of a target instance, a target binding strategy is determined, and the target binding strategy is used for determining that a network card interface corresponding to the interrupt request and processor resources to be bound with the interrupt request are located in the same resource node of a processor architecture; and carrying out resource binding processing on the interrupt request according to the target binding strategy to obtain a binding processing result. The technical problem of poor network performance caused by sequential binding of processor resources only according to the interrupt number in the prior art is solved.

The invention relates to the technical field of bioinformatics and artificial intelligence, and provides a drug-target interaction prediction method and system based on multi-modal feature fusion, and the method comprises the steps: carrying out the word segmentation coding of an obtained to-be-recognized drug sequence and a target sequence, and respectively extracting the subsequence features of a drug and a target; constructing a two-dimensional molecular diagram of the drug and a three-dimensional structure diagram of the target, and respectively extracting diagram structure characteristics of the drug and the target; fusing the subsequence features and graph structure features of the drug and the target through a cross attention mechanism; and carrying out interactive fusion by adopting a bidirectional collaborative attention mechanism to obtain a prediction result of the binding affinity of the drug and the target. According to the invention, by combining the multi-modal complementary information of the drug and the target, deep interaction between different modal features is deeply mined; meanwhile, a two-way collaborative attention mechanism is introduced into interaction modeling of the drug and the target, and the accuracy of drug-target binding affinity prediction is effectively improved.

The invention discloses a fusion protein taking peptide-N-glycosidase as an active component as well as a preparation method and application of the fusion protein, and belongs to the technical field of biological medicines. The fusion protein comprises: (a) peptide-N-glycosidase or a catalytically active fragment thereof; (b) an immunoglobulin Fc domain, or a combination of a tumor or immune cell antigen binding domain and an immunoglobulin Fc domain; (c) a linker peptide; wherein the form of the tumor or immune cell antigen binding domain is Fab, scFv or VHH; the peptide-N-glycosidase or the catalytic activity fragment of the peptide-N-glycosidase is connected with the Fc structural domain of the immunoglobulin through the connecting peptide; the immunoglobulin Fc domain mediates the fusion protein to form a homodimer or a heterodimer. According to the invention, the synergistic function of targeted binding and local deglycosylation of the target molecule is realized, so that the immunosuppressive activity of the target molecule is interfered, and the anti-tumor immune response is enhanced.

Embodiments of the present disclosure relate to modeling DEL data using factorized molecular representations (e.g., hierarchical single and double synthon building blocks), which leverages the hierarchical structure inherent to these molecules. Using factorized molecular representations, machine learning models are trained to learn the underlying binding affinity of compounds to targets and one or more covariates (e.g., loading / repeat noise). This results in machine learning models producing improved predictions in the form of higher enrichment scores that have good correlation with compound-target binding affinity.

The disclosure relates generally to electrodes with a target-binding molecule conjugated on its surface that is overlaid with a polymer of sufficient thickness to restrict ion mobility so that the electrical double layer is moved closer to the site of target binding to the immobilized target-binding molecule. Generally, thickness of the polymer coating layer is such that a target-binding site of the immobilized target-binding molecule is not in the coating layer, e.g., the target-binding site is exposed. The disclosure also provides sensors comprising the electrode and uses of the electrodes and sensors in target analyte detection, e.g., in label-free detection of targets. WO

The invention discloses a 5-bromoindole-2-carboxylic acid methyl ester derivative as well as a preparation method and application thereof in a protein inhibitor, and relates to the technical field of synthesis and preparation of inhibitors. According to the 5-bromoindole-2-carboxylic acid methyl ester derivative, compared with a contrast product, the synthetic route steps of the prepared 5-bromoindole-2-carboxylic acid methyl ester derivative are simpler and more convenient, structural modification and preparation are easier, the application range of a substrate is widened, the yield of the product is increased, and the yield of the product is increased. The differentiated requirements on the molecular structure novelty in the field of kinase inhibitors can be met. An epidermal growth factor receptor (EGFR) inhibitor prepared from the 5-bromoindole-2-carboxylic acid methyl ester derivative is higher in inhibition efficiency on biological activity, the physiological solubility is improved more remarkably, a more excellent and stable target binding result can be shown, and the EGFR inhibitor can be used for preparing an epidermal growth factor receptor (EGFR) inhibitor. The application effect of the compound in scenes such as antitumor drug development and the like is favorably improved.

This invention discloses a KK-LC-1 targeting binding protein and its derivatives, a kit, and applications. The protein sequence of the KK-LC-1 targeting binding protein is shown in one of SEQ ID No. 2, SEQ ID No. 3, SEQ ID No. 4, and SEQ ID No. 5. The KK-LC-1 targeting binding protein of this invention has a molecular weight of only about 17 kDa, approximately one-tenth that of an antibody, exhibiting good tissue penetration. Furthermore, its production process is simple and yields high quantities. The targeting binding protein of this invention demonstrates good targeting activity against KK-LC-1-positive tumors both in vivo and in vitro, and can be used for targeted tumor drug delivery, representing a potential drug for tumor immunotherapy. Simultaneously, a KK-LC-1 serum detection kit was developed using the targeting binding protein, enabling quantitative detection of KK-LC-1 levels in the human body.

The application discloses use of LncRNA00_178, miR-466b-3p and Gucy1b1 as acute lung injury markers or drug targets, and belongs to the technical field of biomarkers and drug targets. LncRNA00_178 can be used as a biomarker for screening or diagnosing acute lung injury, a miR-466b-3p down-regulator can be used to prepare a pharmaceutical composition for preventing and treating acute lung injury, and Gucy1b1 can be used as a drug target to prepare a drug for preventing and / or treating acute lung injury. The application has the beneficial effects that the application proposes that LncRNA00_178 and miR-466b-3p, and miR-466b-3p and Gucy1b1 have a target binding relationship. LncRNA00_178 can be used as a biomarker for screening or diagnosing acute lung injury, the silence of miR-466b-3p inhibits LPS-induced apoptosis of alveolar epithelial cells, and Gucy1b1 can be used as a drug target to prepare a drug for preventing and / or treating acute lung injury. The data provide new insights for the treatment mechanism of ALI and the identification of specific targets, and provide a new idea for the research and development of new drugs for acute lung injury, and have a wide application prospect.

The present disclosure addresses the problem of providing technology for phagocytizing unwanted cells or the like in vivo.　This protein includes, from the N-terminus to the C-terminus, (A) a target binding region that binds to a target, and (C) an SHBG-like domain of ProS.

The present invention relates to humanized nanobodies targeting cadherin 17 and their applications, and to the technical fields of immunology and molecular biology. The complementary determining region of the humanized nanobody includes a CDR1 with an amino acid sequence as shown in SEQ ID NO: 2, a CDR2 with an amino acid sequence as shown in SEQ ID NO: 4, and a CDR3 with an amino acid sequence as shown in SEQ ID NO: 6; the framework region of the humanized nanobody includes a FR1 with an amino acid sequence as shown in any one of SEQ ID NO: 1 and SEQ ID NO: 8, an FR2 with an amino acid sequence as shown in any one of SEQ ID NO: 3, SEQ ID NO: 9, and SEQ ID NO: 11, an FR3 with an amino acid sequence as shown in any one of SEQ ID NO: 5 and SEQ ID NO: 10, and an FR4 with an amino acid sequence as shown in SEQ ID NO: 7. The humanized nanobody of the present invention reduces the immunogenicity of the nanobody, improves the target binding activity and killing activity, and can be used to develop immune detection reagents, CAR-T / NK cell drugs, and antibody drugs.

Disclosed herein are methods and compositions for detecting (+)-methamphetamine using dye-complexed and redox-tag-labeled aptamers that generate a detectable signal upon target binding.

Macromolecule compositions and related methods that effect targeted delivery of therapeutic agents to effector targets in a desired cell, tissue and / or organ of interest while minimizing or avoiding undesirable delivery to other cells, tissues or organs are provided. Compositions and methods related to macromolecules, such as an ANDbody™, that include an effector target binding domain specific for an effector target, and an address binding domain specific for an address target are described. The macromolecules are linked to small molecules.

The invention discloses application of a cacumen biotae extract in activating Nrf2 protein in cells, and particularly relates to the field of cosmetics. Wherein the activation of the Nrf2 protein in the cell is realized by interrupting the Keap1-Nrf2 protein-protein interaction in the cell, and performing targeted combination with the Keap1 protein and releasing the Nrf2 protein. By activating the Nrf2 pathway, the Chinese arborvitae twig and leaf extract can simultaneously achieve anti-oxidation, anti-inflammatory, anti-aging and whitening effects, and meets the requirements of cosmetics for multi-target effects.

The invention belongs to the technical field of biological medicine, and particularly relates to a DLL3 targeted binding protein and application. The DLL3 targeted binding protein has an amino acid sequence as shown in SEQ ID NO. 1, SEQ ID NO. 2 or SEQ ID NO. 3. The DLL3 targeted binding protein disclosed by the invention can be specifically bound with DLL3, the binding affinity reaches nM level, the molecular weight is about 18kDa which is far less than that of a traditional antibody molecule, and the DLL3 targeted binding protein has stronger tissue penetrability and lower immunogenicity. Related tests show that the DLL3 targeted binding protein disclosed by the invention can be used for diagnosis, treatment and drug delivery of DLL3 positive tumors, and has a wide clinical application prospect.

The invention discloses a small molecular probe for targeting a mutant EGFR (Epidermal Growth Factor Receptor). The small molecular probe comprises an EGFR targeting binding group and a fluorophore. The micromolecular probe can be used for imaging diagnosis of EGFR mutant tumors, can also be used for targeted therapy, and has an important clinical application prospect.

This application discloses a method, apparatus, and computer device for evaluating ligand binding sites in a complex. The method involves binding a target ligand to multiple candidate binding sites within a target protein, obtaining a candidate complex conformation corresponding to each candidate binding site; acquiring distance information between each atom of the target protein and each atom of the target ligand in each candidate complex conformation; determining the binding strength information between the target protein and the target ligand in each candidate complex conformation based on the distance information; and determining the target binding site based on the binding strength information. This method can improve the accuracy of ligand binding site evaluation in complexes.

A peptide or a derivative thereof or a salt thereof, including a hydrophobic region, and a hydrophilic region positioned on at least one end side of the hydrophobic region and having hydrophobicity lower than that of the hydrophobic region, including, at one end, a first target binding site capable of binding to a first target, and including, at the other end, a second target binding site capable of binding to a second target. The peptide is applicable to an active targeting DDS.

Embodiments of the disclosure involve modeling DEL data using factorized molecular representations (e.g., hierarchical mono-synthon and di-synthon building blocks), which capitalizes on the inherent hierarchical structure of these molecules. Using the factorized molecular representations, machine learning models are trained to learn latent binding affinity of compounds for targets and one or more covariates (e.g., load / replicate noise). This leads to improved predictions by the machine learning models in the form of higher enrichment scores, which are well-correlated with compound-target binding affinity.

The present disclosure provides: a polypeptide that comprises a ubiquitinated enzyme domain, an exosome transfer domain, and a target binding domain; a nucleic acid that encodes the polypeptide; a vector that includes the nucleic acid; a cell that expresses the polypeptide; an exosome that includes the polypeptide; and a pharmaceutical composition that includes the polypeptide, the nucleic acid, the vector, the cell, and / or the exosome.

The present application provides a guide RNA for inhibiting off-target binding in CRISPR / Cas9-based genome editing, wherein the guide RNA comprises at least one abasic spacer in a crRNA sequence. The effects of the present invention include inhibiting unintended off-target binding while maintaining the target genome editing effect by CRISPR / Cas9 by weakening the binding force with the target DNA while maintaining the structure of the guide RNA.

The present invention discloses a drug-target binding affinity prediction model and method based on a graph dilation and convolution strategy. The present invention performs feature encoding on drug molecules, local information, and targets through a feature encoding module. Feature extraction is performed on the drug molecular structure, local chemical information of the drug molecule, and target structure through a multi-channel general aggregation network module using a graph dilation and convolution strategy, a drug sequence representation learning module using a multi-layer residual convolution network, and a target sequence representation learning module using a bidirectional long-short cycle memory network. Finally, the extracted global drug structural features, local drug chemical features, and target sequence features are concatenated and passed through a DTA prediction module to predict the drug-target affinity value. This effectively improves the drug-target binding affinity prediction accuracy and the success rate of the drug redirection process, solving the problems of low drug-target binding affinity prediction accuracy and low drug redirection process success rate.

A method and device are provided for detecting a target in a biological sample. The target binds to a solid phase substrate. First and second cavities in a plate are filled with an oil. The first and second cavities are in fluid communication with each other. The solid phase substrate is magnetically drawn sequentially from a drop of the biological sample in the first cavity, through the oil, into a drop of the reaction solution in the second cavity. A change in a parameter of the drop of the reaction solution indicates the presence of the target.

This invention proposes a nucleic acid aptamer that specifically binds to human senescent dermal fibroblasts (HDFs), along with its screening, identification, and application. Specific aptamers exhibiting high targeting specificity to human senescent HDFs were screened using Cell-SELEX technology. The three selected candidate aptamers showed binding rates of 57.5%, 86.2%, and 50.7% to senescent HDF cells within the same timeframe, respectively, demonstrating high specificity and targeted binding ability. Furthermore, the aptamer possesses potential for detecting, imaging, and regulating the function of senescent cells, successfully providing a new direction for targeted anti-aging interventions and therapeutic applications.

The application discloses a polypeptide with binding affinity to IL-6 and application thereof. The amino acid sequence of the polypeptide comprises one or more of sequences shown in SEQ ID NO. 1-6. The application obtains the polypeptide with affinity to IL-6 through screening, which can specifically bind to IL-6, so that IL-6 is enriched, and then IL-6 is adsorbed at an inflammation infection site, thereby providing more choices for treatment of diseases related to removal of inflammatory factors and IL-6 overabundance, and the polypeptide can be used for IL-6 detection and preparation of drugs for targeted binding to IL-6 or treatment of diseases related to IL-6.

The purpose of the present invention is to provide lipid nanoparticles capable of efficiently introducing a nucleic acid into T cells. Provided are lipid nanoparticles each comprising: a nucleic acid encapsulated in each of the lipid nanoparticles; a cationic lipid; sterol or a sterol derivative; DSPC; a targeted polyalkylene glycol-modified lipid linked to a target binding site; and a non-targeted polyalkylene glycol-modified lipid to which the target binding site is not linked. The target binding site targets a target site on each T cell. The amount of the cationic lipid is 35.0-55.0 mol% with respect to the total lipid amount of the lipid nanoparticles. The amount of sterol is 25.0-40.0 mol% with respect to the total lipid amount of the lipid nanoparticles. The amount of DSPC is 15.0-35.0 mol% with respect to the total lipid amount of the lipid nanoparticles. The N / P ratio is 8.0-12.0.

The invention discloses a compound targeting AT1R, which is composed of a target head molecule targeting AT1R, a PEG linker, an aspartic acid linker and a chelating agent, and can be used as a component of a PET tracer agent targeting AT1R. A target head molecule can be embedded into a hydrophobic'pocket 'of AT1R protein, so that high-affinity and high-selectivity targeted binding is realized; the PEG connexon can prolong the residence time of the PET tracer agent targeting the AT1R at the tumor part; different numbers of aspartic acids can regulate and control the pharmacokinetic properties of the PET tracer agent targeting the AT1R, reduce the liver and gall and intestinal signal backgrounds of the PET tracer agent targeting the AT1R, and improve the target-to-cost ratio. Therefore, accurate diagnosis and treatment of digestive system diseases such as digestive tract tumor and liver cancer can be realized. The invention further discloses a PET tracer agent targeting AT1R as well as a preparation method and application of the PET tracer agent.

The invention discloses an electrochemical sensor for glycoprotein detection and a glycoprotein detection method. The method comprises the following steps: anchoring an aptamer-protein conjugate on the surface of a gold electrode, and then assembling an anti-fouling peptide around the aptamer-protein conjugate to form an imprinted self-assembled monolayer film. And removing the combined protein through an acid solution to form a biocompatible imprinting cavity capable of being used for recombining a target object. The imprinted cavity can eliminate non-specific adsorption and enhance targeted binding efficiency. The sensor can be used for directly detecting carcino-embryonic antigens with the concentration as low as 0.1 ng / mL through an electrochemical impedance spectroscopy method. Besides, homodimer concanavalin A (ConA) is used as a recognition element and a cross-linking agent, homodimer glucose oxidase (GOx) is assembled on the surface of the electrode in situ, a protein network can be formed, and enzyme catalysis signal amplification detection is achieved. Through in-situ formation of a ConA-GOx assembly, the sensitivity is improved by 100 times.

Described herein are reagents and methods for improving signal in imaging mass cytometry. Aspects include mass tags with a large number of labeling atoms, chemical modifications to mass tags and additional reagents to reduce background and / or maintain target binding of mass tagged specific binding partners (SBPs), and schemes for associating a plurality of mass tags with a single SBP. As such, embodiments include any combination of one or more reagents and their use. The reagents, kits and methods herein may be used for mass cytometry, including imaging mass cytometry. In some aspects, reagents, kits or methods may be used for delivery of a large number of radioisotopes to a target analyte, for example for therapeutic use or radiometric detection. In certain aspects, only non-radioactive isotopes may be used for mass cytometry.

The application discloses a drug-target binding affinity prediction model training method and a prediction method based on contrast learning, and belongs to the technical field of drug-target binding affinity prediction. In order to solve the problem that the prediction effect of the existing DTA prediction based on contrast learning needs to be improved, the application selects positive and negative samples according to the similarity between drug molecular structures, the similarity between target sequences, and the similarity between drugs and targets in an affinity graph to optimize the effect of contrast learning, extracts drug-target features of three different scales of sequences, molecular structures and affinity graphs, fully utilizes drug and target information, captures potential relationships between cross-scale feature information through a multi-scale feature contrast learning framework, maximizes mutual information between different scales, and performs feature alignment and feature fusion, and then obtains a prediction model based on contrast loss, and the prediction model is used to realize drug-target binding affinity prediction.