143 results about "Protein targeting" patented technology

Provided are compounds that may bind a target protein, and result in modification of the target protein. The compounds may further bind a modifier protein. The modifier protein may carry out or enhance the modification of the target protein. The modification may activate or reactivate the target protein. Also provided are methods of using the compounds.

Disclosed in the present invention is a novel substituted heterocyclic compound having VAV1 target degradation activity. Specifically disclosed is a compound serving as a VAV1 target degradation agent and having the structure of formula (I), or a pharmaceutically acceptable salt, solvate, hydrate, isotopic substituent or isomer of the compound. The compound can be used for preventing or treating diseases related to VAV1 targets or signaling pathways.

The present disclosure relates to a novel class of bifunctional molecules that are useful in a targeted or selective degradation of a protein.

The invention belongs to the technical field of medical chemistry, and particularly relates to a targeted protein degradation compound containing an SYVN1 binding compound and application of the targeted protein degradation compound. According to the invention, a series of compounds interacting with SYVN1 are found, and the compounds can be used as'warheads' to participate in ERAD and effectively degrade transmembrane protein targets. Based on the SYVN1 binding compound, a new TPD technology for hijacking ERAD is established, and a brand new platform is provided for processing TMSPs and other proteins which are difficult to target by the current TPD technology. A SYVN1 interaction compound is further connected with a known ligand interacting with a protein target through a chemical linker, a series of ERADEC molecules are generated, the molecules can significantly degrade target protein, and a new possibility is provided for targeted degradation of drugs.

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 embodiment of the invention provides a drug optimization method and system based on the overall effect of a protein network. The method comprises the following steps: constructing a protein interaction network related to a target disease, and dividing each protein target into a risk protein set and a protection protein set; respectively calculating first binding affinity data of the candidate drugs and each protein target in the risk protein set, and generating a first network comprehensive score based on the first binding affinity data; respectively calculating second binding affinity data of the candidate drugs and each protein target in the protection protein set, and generating a second network comprehensive score based on the second binding affinity data; calculating network confrontation scores of the candidate drugs according to the first network comprehensive score and the second network comprehensive score; and determining whether the candidate drug is a preferred drug based on the network adversarial score. The method can overcome the defect that a single-target drug is insufficient in curative effect due to a network compensation effect, so that safer and more effective candidate drugs are screened out.

The invention discloses a bifunctional molecule compound for inducing SHP2 protein degradation based on a DCAF16 ligand as well as a preparation method and application of the bifunctional molecule compound, belongs to the technical field of medicines, and relates to a bifunctional molecule for inducing SHP2 protein degradation based on the DCAF16 ligand as shown in a general formula (I) or pharmaceutically acceptable salt of the bifunctional molecule, and a pharmaceutical composition containing an SHP2 protein targeted degradation agent. The invention also relates to a preparation method of the compound and application of the compound in preparation of medicines for treating SHP2-mediated tumors and / or other diseases.

Provided here are IRE1 degrader compounds comprising a protein target moiety covalently attached by a linker to an E3 ubiquitin ligase-binding moiety. Also provided are intermediate compositions for the preparation of IRE 1 degrader compounds and methods of treating diseases and disorders such as cancer with the IRE1 degrader compounds.

A compound including formula (I) or formula (II) for use in promoting targeted protein degradation.

The invention discloses a ligand molecule generation method based on multi-modal information guidance, which fully captures high-precision interaction between a protein pocket and a ligand molecule, not only considers structural information of the ligand molecule, but also performs sufficient information guidance aiming at a protein target point molecule generation method. The generated molecules have diversity, and the requirements of subsequent biological docking experiment verification are met; on the other hand, the potential interaction relationship between the protein structure characteristics and the ligand molecules is utilized, different protein targets are fused in the diffusion process, and various modal information is balanced to guide the generation of the ligand molecules.

The invention discloses an engineered protein and application thereof in mediating non-ubiquitination degradation, and belongs to the technical field of biological medicine. The structural domains CATCH1 and CATCH2 of the MIDN protein and the region between the structural domains CATCH1 and CATCH2 are modified for the first time, the modification mode comprises the steps that the structural domains CATCH1 and CATCH2 and the region between the structural domains CATCH1 and CATCH2 are replaced with antibodies or polypeptides, then structure or sequence optimization is conducted on the basis, and the obtained MIDN engineered protein not only retains the proteasome binding capacity of MIDN, but also has the advantages of being capable of improving the protein quality and the like. According to the present invention, the MIDN-based target protein degradation system has the MIDN-based target protein degradation system, can expand the target range to the membrane protein or the cytoplasm protein, can improve the degradation efficiency of the MIDN-based target protein degradation system, further has the antibody-mediated target protein specificity so as to achieve the pathological / physiological protein distinguishing effect, and does not have the obvious toxicity; therefore, the engineered protein provided by the invention has a good application prospect.

The invention relates to the technical field of computational biology and artificial intelligence assisted drug discovery, and discloses a drug-target effect prediction method and system based on multi-mode self-supervised learning. The method comprises the steps of drug side self-supervised pre-training, protein side self-supervised pre-training, multi-feature fusion, drug-protein interaction modeling and multi-task joint prediction. Drug-target effect prediction is carried out based on self-supervised pre-training and multi-modal information fusion, a self-supervised learning method is firstly used to train a deep learning model by using label-free data, and then the deep learning model is used to carry out multi-modal characterization, multi-modal fusion and interaction relationship modeling on drug molecules and protein targets. According to the method, combined prediction of drug-target interaction, affinity and action mechanism can be realized, and the prediction precision and model robustness of the model are effectively improved.

This invention provides pharmaceutical protein degraders and E3 ubiquitin ligase binders for therapeutic applications as described further herein.

The present invention relates to quinazolinones and related compounds which degrade PARP14 and are useful, for example, in the treatment of cancer and inflammatory diseases.

The present invention provides isolated polypeptides capable of specifically binding to a protein target selected from LGALS9, CRP, BTLA, SAA, EGF, or FGA, or to a peptide thereof, especially under urinary conditions, which may be used for predicting in a urine sample of a subject suspected of having an infection whether the infection is a bacterial infection or a viral infection. The present invention further provides methods of diagnostics and treatment using the isolated polypeptides, and suitable diagnostic kits.

The disclosure provides a traditional Chinese medicine efficacy evaluation method and device based on a node-weighted network, equipment and a storage medium. The method determines target disease protein targets and corresponding target weights based on the comprehensive scoring results of candidate disease protein targets by a public database and a large language model. When determining the protein targets of medicinal materials and the corresponding protein target weights of medicinal materials, the prescription ratio, chemical component information, and the interaction probability between the chemical components and the protein targets of each medicinal material in the traditional Chinese medicine prescription to be evaluated are comprehensively considered. The target disease protein targets and the corresponding disease protein target weights, as well as the protein targets of medicinal materials and the corresponding protein target weights of medicinal materials, are added to a pre-constructed protein interaction network. The obtained node-weighted network focuses on the real pharmacological basis, effectively improves the network biological interpretation, and the multi-dimensional network index determined accordingly is used to evaluate the regulation effect of the traditional Chinese medicine prescription to be evaluated on the target disease, which is more accurate.

An isolated antigen binding protein capable of targeting MSLN. The isolated antigen binding protein comprises at least one CDR in an antibody heavy chain variable region VH, and the VH comprises an amino acid sequence as set forth in any one of SEQ ID NO: 8, SEQ ID NO: 13, SEQ ID NO: 69, and SEQ ID NO: 70. Also provided are a chimeric antigen receptor comprising the antigen binding protein, and use of the antigen binding protein in treating tumors.

The present application relates to ANXA3 protein targeted degradation chimera and its preparation method and application. Specifically, the present application relates to ANXA3 protein targeted degradation chimera, or its pharmaceutically acceptable salt, or its stereoisomer, or a pharmaceutical composition composed of a medically acceptable carrier, and the use in preparing ANXA3 protein targeted degradation chimera and the use in preparing drugs for preventing and / or treating breast cancer. The present application utilizes the PROTAC technology to provide a kind of ANXA3 protein targeted degradation chimera, which can combine ANXA3 protein, selectively degrade ANXA3 protein, inhibit the proliferation of breast cancer cells in vitro, and play the role of anti-breast cancer. Breast cancer refers to breast cancer molecular subtypes such as triple negative, Luminal A type, Luminal B type, Her2+ type.

The application belongs to the technical field of biology and particularly relates to a functional recombinant Cas9 protein targeted to an ovocyte of Procambarus clarkii and application thereof. The protein is NLs-VgSP-Cas9-NLs. The application directly delivers the recombinant Cas9 protein, thereby reducing the risk of integration of exogenous genes. By specifically targeting the ovocyte, off-target effects on somatic cells can be avoided, the efficiency of editing of germ cells is improved, and early development or genetic manipulation can be conveniently studied. The ovocyte of Procambarus clarkii is large, the recombinant Cas9 protein is efficiently delivered by receptor-mediated endocytosis on the surface of the ovocyte, and the problem that microinjection of zygotes cannot be implemented is solved.

This invention provides a multivalent protein-targeting degradation system based on a programmable nucleic acid template, its preparation method, and its applications, belonging to the fields of biomedicine and molecular engineering. The system includes monovalent nucleic acid degradation units and a nucleic acid template. The monovalent degradation unit is formed by hybridization of two nucleic acid chains coupled with a target protein ligand and an E3 ubiquitin ligase ligand. The nucleic acid template has n loading sites, which assemble into multivalent nucleic acid degraders through complementary base pairing. This invention achieves precise control over the spacing and configuration of monovalent units by regulating the template spacer sequence length and topology, resulting in a spatially ordered multivalent synergistic degradation effect and significantly improving the degradation efficiency of target proteins. This system is highly modular and programmable, providing a new technological platform for the development of targeted protein degradation drugs.

The present disclosure provides a polypeptide generation method, device, electronic equipment and storage medium, relates to the technical field of artificial intelligence, in particular to biological computing technology. The method comprises the following steps: obtaining a protein target and a reference polypeptide corresponding to the protein target, wherein the protein target is a protein causing pathological changes; generating a candidate polypeptide corresponding to the reference polypeptide; and inputting the protein target and the candidate polypeptide into an affinity evaluation module for screening to obtain a target polypeptide, wherein the affinity evaluation module comprises at least two levels of evaluation sub-modules arranged in a preset evaluation order, and the later the evaluation sub-module in the evaluation order, the higher the accuracy of the evaluation sub-module. The present disclosure can balance the accuracy and efficiency, and improve the "performance-price ratio" of the polypeptide drug design process.

The present invention relates to an automated peak sorting system having an exceptionally fast processing speed while being as accurate as humans and experts with respect to conventional targeted proteomic peak picking, which requires manual intervention from researchers and wastes a lot of time and resources. A learning model or a computer program capable of executing same, of the present invention, can be useful for rapidly and accurately sorting out a peak optimized for quantification of a plurality of target peptides input as desired by a user through a GUI of the program.

Disclosed are novel methods and pharmaceutical compositions for creating tunable, protein target-specific polypeptides, their use for adjustable regulation of the levels of one or more protein targets and associated biological functions thereof, and applications to highly selective detection and / or isolation of one or more protein targets.

The application discloses a trienomycin photoaffinity probe, a preparation method and application, and comprises the following steps: taking Trienomycinol as a substrate, carrying out a substitution reaction with an iodine-substituted bisaziridine, then removing propylidene protection to obtain a corresponding photoaffinity negative probe; using Fmoc-D-alanine to selectively esterify a hydroxyl group at position 11 of the negative probe, then removing an Fmoc protection group on nitrogen and carrying out condensation with cyclohexanecarboxylic acid to obtain a corresponding photoaffinity positive probe; trienomycin protein target identification comprises the following steps: (1) enrichment of an intermediate Trienomycinol and synthesis of a trienomycin photoaffinity positive probe; (2) target identification of trienomycin by using the photoaffinity probe and molecular biology research on the target. The separated trienomycin intermediate, the synthesized trienomycin probe derivative and the identified trienomycin protein target have the advantages of high originality and high yield.

It provides a complex for target protein degradation. [Solution] The present invention relates to a novel compound-peptide nucleic acid-aptamer complex for targeted protein degradation and its applications. The complex is manufactured by binding a novel compound to a peptide nucleic acid and introducing an aptamer that can bind complementaryly to the peptide nucleic acid. It has been confirmed to have the effect of targeting and degrading intracellular target proteins such as Tau, nucleolin, and eIF4E, and can be usefully utilized in related industries.

The invention discloses a PAI-1 protein targeting peptide compound (called P peptide for short) with a thrombus dissolving effect and application thereof, and belongs to the field of biological medicine. The PAI-1 targeted thrombolytic polypeptide compound comprises P1, P2, P3 and P4, and is characterized in that the compound is derived from a core structure 'X-Asp-Glu-Leu-Cys-X-Tyr-Tyr-X-X-Cys-X' (cyclization is performed through a disulfide bond between Cys, and X represents any type of amino acid), and the compound can be specifically bound with a key binding site of PAI-1. The polypeptide can significantly reduce the inhibitory effect of PAI-1 on plasminogen activators (tPA, uPA), enhance the activity of a fibrinolytic system, and generate in-vivo and in-vitro thrombolysis effects. The polypeptide compounds P1, P2, P3 and P4 not only have a thrombolysis effect, but also can reduce the expression level of pro-inflammatory cytokines (IL-1beta, TNF-alpha, IL-6 and the like), which shows that the polypeptide compounds also have an anti-inflammatory effect. In conclusion, the polypeptide compound can be used for preparing a PAI-1 antagonist, a thrombolytic agent and an anti-inflammatory agent related to thrombus.

The application discloses a method for constructing a high-throughput protein capture interface by antibody adsorption, which comprises the following steps: S1, synthesizing a tetrahedral framework nucleic acid structure; S2, mixing a capture antibody and the synthesized tetrahedral framework nucleic acid structure on a gold island substrate to prepare a high-throughput protein capture interface; S3, placing the gold island substrate in a wet box for overnight incubation; S4, blocking the capture interface to prevent non-specific adsorption; S5, incubating a protein target; S6, incubating a detection antibody; S7, incubating a fluorescent secondary antibody; S8, washing the capture interface with pure water and centrifuging and air-drying; and S9, performing fluorescent imaging and quantification on the capture interface by using a chip scanner. The method for constructing a high-throughput protein capture interface by antibody adsorption has high uniformity, and can realize high-throughput, high-sensitivity and high-accuracy protein capture and quantitative detection.

Provided are multispecific B7H3-targeting compounds and methods of using the same. The multispecific compounds include bispecific targeting proteins comprising a B7H3-targeting domain and an immune cell engaging domain, and trispecific targeting proteins comprising a B7H3-targeting domain, an immune cell engaging domain, and an immune cell activating domain. The methods of using include methods of inducing NK-mediated cell killing, methods of inducing NK in vivo expansion, and methods of treating cancer.

The present application relates to an assay method using affinity crosslinking of DNA-linked ligands to proteins to enable small molecule screening and determination of apparent affinity constants of ligands to the proteins. This method has been applied to determine 96 compounds' dissociation constants to a protein target simultaneously, and directly determine a compound's IC50 against five protein targets concurrently in crude cell lysates. Additionally, this approach was used to screen a Library of Pharmacologically Active Compounds (LOPAC) library against dihydrofolate reductase (eDHFR), enabling the discovery of a novel eDHFR inhibitor (IC50=7.9 μM). An assay kit and the method of uses are within the scope of this disclosure.