93 results about "Pharmacophore" patented technology

The invention discloses a multi-target drug molecule generation model construction method and a multi-target drug design method, and relates to computer drug design and bioinformatics. Determining a corresponding two-dimensional molecular map based on the SMILES sequence; the fully-connected pharmacophore diagram and the two-dimensional molecular diagram are used as input of a GatedGCN module, each atomic node in the two-dimensional molecular diagram is connected with all pharmacophore nodes in the fully-connected pharmacophore diagram in message transmission, and information exchange between different nodes is achieved; the masked SMILES sequence serves as the input of an encoder, and the decoder generates an SMILES sequence conforming to pharmacophore characteristics in an autoregression mode; freezing the network parameters of the GatedGCN module and the encoder; and training the multi-target drug molecule generation model through the elite multi-target molecule set, and reversely optimizing and updating decoder network parameters according to an output result. According to the method, the model fully learns the multi-target molecular structure characteristics, and the multi-target drug molecule generation accuracy is improved.

The invention discloses a multi-target joint optimized antibiotic molecule design system and method applied to the field of biological medicine, and the method comprises the steps: obtaining FabI enzyme and AcrAB-TolC efflux pump structure data, extracting double-target space and physicochemical characteristics, and constructing a joint pharmacophore model containing a FabI inhibition domain and an efflux pump blocking domain; screening candidate molecules meeting a double-domain space matching threshold, screening high-affinity double-target molecules through conformation sampling and free energy calculation, and forming a lead compound library through multi-layer filtration of metabolic stability, membrane penetrability, quantum chemical properties and synthesis feasibility; carrying out electron effect, chain length or heteroatom fine tuning on dominant molecules through in-vitro bacteriostasis and efflux inhibition experiment feedback, and carrying out iterative optimization until MIClt is met; 2 [mu] g / mL and the efflux inhibition rate is gt; according to the present invention, the antibacterial effect and the drug resistance inhibition ability are significantly improved, the molecular synthesizability and the biological safety are ensured, and the engineering design new path is provided for the Gram-negative bacterium drug resistance crisis.

This application discloses a linker and its preparation method. The linker includes pharmacophore P, pharmacophore Q, and deoxynucleotides and / or deoxynucleotide derivatives connecting pharmacophore P and pharmacophore Q. Pharmacophore P is obtained by removing the protecting group from group B, and pharmacophore Q is obtained by removing the protecting group from group X. Group B is obtained by chemically modifying the benzylquinolone carboxylic acid pharmacophore, and group X is obtained by chemically modifying the zenomeprazole pharmacophore. The linker is prepared by linking group B and group X with deoxynucleotides and / or deoxynucleotide derivatives to form the linker, including solid-phase synthesis technology. The method of this application can automatically synthesize molecular probes or bivalent drugs containing two pharmacophores, thereby replacing the traditional stepwise linking method, enabling efficient construction of screening libraries, and allowing control of the spatial distance and spatial orientation of the pharmacophores by adjusting the number and base arrangement of deoxynucleotides.

The invention belongs to the technical field of medicinal chemistry, and particularly relates to a quinoxaline compound as well as a preparation method and application thereof. Specifically, the quinoxaline compound provided by the invention is screened by adopting virtual screening and pharmacophore modes, is novel in structure, has relatively good inhibitory activity on MELK, and solves the problem of insufficient development of an existing MELK inhibitor that the activity is not ideal enough, the chemical structure is not diversified enough and the like.

The invention discloses an indole pyridine chalcone compound and application thereof in medicine for treating colitis, and belongs to the technical field of biological medicine. The compound has a structure as shown in a formula I, wherein R1 is selected from C1-C8 alkyl, C1-C8 alkoxy, halogen, cyano, nitryl and morpholinyl, and R2 is selected from nitryl. According to the invention, multiple excellent pharmacophores such as indole, pyridine, chalcone, sulfonamide and the like are fused in the same molecule for the first time, the preparation method does not need pre-activation of a substrate, does not need a metal catalyst or an additive, and has the advantages of mild reaction conditions, high yield, good selectivity, low cost and environmental friendliness. The compound has strong inhibitory activity on hexokinase 2 (HK2), can significantly inhibit inflammatory response and regulate macrophage polarization, shows an excellent colitis treatment effect in in-vivo and in-vitro experiments, provides a new choice for developing novel colitis treatment drugs, and has a wide medical application prospect.

The invention provides an application of a TAS2R14 molecular sensory artificial intelligence biosensor in key quality attribute identification of bitter taste of Jinvibration oral liquid. The application comprises the following steps: (1) constructing a biosensor; (2) determining the interaction strength of the sample to be detected and the taste receptor protein by adopting an electrochemical workstation; (3) carrying out specific elution on the key quality attributes combined on the bitter receptors; (4) identifying chemical components in the eluent, comparing the chemical components with all components of the sample to be detected, and screening potential bitter key quality attributes; (5) designing and constructing a pharmacophore of a bitter receptor TAS2R14 agonist of the pharmacophore model; (6) screening to obtain bitter key quality attributes of the Jinvibration oral liquid; and (7) verifying the obtained bitterness key quality attribute. According to the invention, a TAS2R14 bitter protein receptor is taken as an entry point, 10 bitter key quality attributes of the Jinvibration oral liquid are screened out, and method guidance is provided for quality evaluation and control of a traditional Chinese medicine compound oriented by property, taste and efficacy.

The invention discloses a method for solving a molecular docking problem based on a QAOA quantum circuit and a related device. The method comprises the following steps: acquiring a Hamiltonian used for representing the molecular docking problem; a QAOA quantum circuit containing M * N quantum bits is constructed based on the Hamiltonian, and each quantum bit has 1gt; the state represents the butt joint of the first pharmacophore and the second pharmacophore and the 0gt of each quantum bit; the state indicates that the first pharmacophore is not butted with the second pharmacophore; optimizing the QAOA quantum circuit based on the topological structure of the quantum chip of the real quantum computer to obtain an optimized QAOA quantum circuit; the optimized QAOA quantum circuit runs on the basis of a quantum chip of a real quantum computer so as to solve the molecular docking problem. According to the method, the molecular docking problem is solved by optimizing the QAOA quantum circuit, so that the optimal combination mode of the molecular docking problem is obtained, and the accuracy of the operation result of the QAOA quantum circuit is improved.

A method for predicting drug-target interaction includes: determining a first drug association matrix according to drug attribute information, the drug attribute information including at least one of a drug structure similarity, a pharmacophore similarity, a side effect similarity, and a GO pathway-based similarity of drugs, and the first drug association matrix being used to characterize feature information of each drug on at least one drug attribute; determining a first target association matrix according to target attribute information, the target attribute information including at least one of a target structure similarity and a target interaction relationship of targets, and the first target association matrix being used to characterize feature information of each target on at least one target attribute; and predicting a probability of interaction between a drug and a target according to the first drug association matrix and the first target association matrix.

This invention provides a class of multi-target heteropeptides based on N-4-piperidinyl-N-phenylpropionamide analogs and neuropeptide FF. These heteropeptides use the small-molecule N-4-piperidinyl-N-phenylpropionamide and the polypeptide-structured neuropeptide FF as chemical templates. A series of peptide-small-molecule hybrid peptides are obtained by chemically coupling the pharmacophores of the N-4-piperidinyl-N-phenylpropionamide analog and the neuropeptide FF. In vivo pharmacological activity identification in animals shows that these heteropeptides possess analgesic activity without opioid-like side effects such as addiction and respiratory depression. Furthermore, compounds 1-4 and compounds 7-9 do not exhibit analgesic tolerance and can be used for long-term analgesic treatment of chronic pain. Therefore, these heteropeptides based on N-4-piperidinyl-N-phenylpropionamide analogs and neuropeptide FF can be used to prepare analgesic drugs.

This invention relates to the field of medicinal chemistry, specifically to a capsaicin-like compound containing isopropanolamine, its preparation method, and its application. This type of compound has a structure as shown in general formula (I). The invention uses capsaicin and isopropanolamine as pharmacophores, connecting the two pharmacophores with different bridging chains to synthesize a series of capsaicin-like derivatives containing isopropanolamine. These compounds exhibit excellent inhibitory effects on plant pathogenic bacteria such as rice bacterial blight, citrus canker, rice bacterial leaf streak, and kiwifruit canker; and plant pathogenic fungi such as cucumber gray mold, pepper wilt, rapeseed sclerotinia rot, eggplant verticillium wilt, wheat scab, potato late blight, blueberry root rot, grape coccidioidomyces, dragon fruit anthracnose, and rice sheath blight, providing an important scientific basis for the research and development of new pesticides.

The invention discloses a parameterized constraint system and method for efflux pump avoidance and off-target risk inhibition, which are applied to the field of biological medicines, and aims to solve the dual problem that toxic risks are caused by efflux pump mediated drug resistance enhancement and off-target combination of existing antibacterial drugs. The method comprises the following steps: constructing an efflux pump identification avoidance five-dimensional feature space and a target spot specificity geometric-electrical constraint boundary, performing structure mapping and deviation degree evaluation on candidate molecules, and triggering directional modification; the target matching is verified through molecular docking, and if the target does not reach the standard, the pharmacophore is locally adjusted; virtual screening is carried out based on an off-target protein database, a secondary structure disturbance mechanism is started for high-risk molecules, and a stereoisomerism or electrical reversal group is introduced to destroy non-target binding; according to the method, collaborative optimization of antibacterial efficacy, drug resistance avoidance and safety risk is achieved, and the research and development efficiency and druggability of candidate molecules are remarkably improved.

The invention belongs to the technical field of organic synthesis, and particularly relates to a synthetic method of a methionine NH-thioimine derivative and a polypeptide compound thereof. According to the invention, methionine ester or polypeptide molecules containing methionine ester are used as raw materials, and the methionine NH-thioimine derivative stably existing in an inner salt form or a polypeptide compound containing a methionine NH-thioimine structure is obtained through oxidative amination and one-time removal of a trifluoroacetyl protecting group and ester, so as to solve the problem of S, S-dimethyl sulfoxide. The method solves the problem that methionine thioimine cannot be widely applied due to instability of an S, S '-dialkyl thioimine structure in the prior art, realizes stable preparation of an unstable thioimine structure, is simple to operate, mild in condition and good in functional group compatibility, is suitable for preparation of various polypeptide molecules containing methionine NH-thioimine, and has wide application prospects. And a key technical support is provided for construction of a pharmacophore library containing methionine NH-thioimine.

The application belongs to the technical fields of synthesis of compounds and pharmaceutical applications, and discloses an anti-tumor pterostilbene piperazine conjugate as well as a preparation method and application thereof. The pterostilbene, piperazine and various substituents are spliced in one molecule by using a molecular hybridization method, a novel anti-tumor pterostilbene piperazine conjugate is synthesized, and it is found through anti-tumor activity research that the anti-tumor activity of the conjugate is obviously higher than that of the two pharmacophores alone, and the conjugate has the potential to become a novel anti-tumor drug. The pterostilbene piperazine conjugate is synthesized, and it is found for the first time that the compound has good anti-tumor activity, can significantly inhibit the proliferation of various tumor cells in vitro, including hepatocarcinoma, triple-negative breast cancer, colon cancer and ovarian cancer cells, has little toxicity to normal cells, and can inhibit the migration ability of tumor cells. Therefore, the compound synthesized by the application has good anti-tumor application prospect.

According to the multi-feature fusion oral bioavailability prediction method, device, equipment and medium provided by the invention, the features of four dimensions including the graph structure feature, the fingerprint feature, the physical and chemical descriptor and the pharmacophore feature of the molecular object of the candidate drug are fused to comprehensively describe the molecular characteristics of the drug, so that the method has stronger characterization capability and can be used for predicting the oral bioavailability of the drug. And the prediction accuracy can be improved. Besides, the fused features are processed by adopting a plurality of different expert processing models corresponding to a plurality of preset different result types, differentiated processing strategies can be adopted for different chemical structure types, and the method can adapt to different application scenes.

The invention relates to the technical field of computational toxicology, and discloses a method for calculating combination of perfluorinated and polyfluorinated alkyl compounds and PPARalpha based on a pharmacophore model, which comprises the following steps: acquiring a PFAS initial data set, acquiring a PPARalpha ligand binding domain crystal structure, and optimizing the structure; selecting representative PFAS to carry out molecular docking, and carrying out simulated annealing optimization to obtain an optimal binding posture; then generating a pharmacophore model; the models are screened; performing rigid fitting screening by using a pharmacophore model; carrying out molecular dynamics simulation on the representative hit object, and verifying the stability; protein is extracted by culturing cells in vitro, a thermal displacement experiment is carried out, and the thermal stability effect of PFAS on PPARalpha is verified. According to the method, comprehensive virtual screening of PFAS-PPAR alpha interaction based on pharmacophores is provided, a calculation framework based on protein and compound structures is established, and the method is suitable for environmental pollutant screening and safer chemical design.

There are disclosed imidazolinopyrimidinone compounds that have activity to induce TRAIL gene expression in macrophages. There is further disclosed a method for treating various cancers comprising administering effective amounts of an imidazolinopyrimidinone having the structure of Formula I herein.

A method for reverse virtual screening based on programmable quantum computing, characterized in that the method comprises the following steps: S1. Calculating a binding interaction graph of the given small molecule and the target protein molecule on the computer based on different pharmacophore distances for a given small molecule and a target protein molecule; S2. Encoding an adjacency matrix of the binding interaction graph into a platform for quantum-reverse virtual screening by decomposing the adjacency matrix; S3. Performing a Gaussian Bose scan over the platform for quantum-reverse virtual screening, which includes the following substeps: S31. Generating a set of single-mode vacuum compression states with different compression levels using the acousto-optic modulator to chop the pulsed laser to pump the nonlinear crystal, and sending the set of single-mode vacuum compression states into the cyclic optical path of the quantum processing unit module; S32. Performing a high-dimensional global primary state evolution operation by an electro-optic modulator in the cyclic optical path, and inputting the evolution result into the detection module, where the number of electro-optic modulators is two and the electro-optical modulator is equipped with a power amplifier for amplifying an analog signal and is controlled by a programmable arbitrary waveform generator; S33. Measuring the presence or absence of the number of photons in each mode by a single-photon superconducting detector in the detection module, and inputting the measurement result into the computer to obtain the sample result processed by the quantum algorithm; and S4. Generating all full-linkage subgraphs of the binding interaction graph according to the sampling results, and generating a full-linkage subgraph with the greatest weight by sorting all full-linkage subgraphs according to weight, thereby directly determining the optimal binding mode between the small molecule and the target protein molecule by the structure of the full-linkage subgraph with the greatest weight.

The invention relates to the technical field of medical imaging diagnosis, in particular to a CSF1 receptor-targeted PET (positron emission tomography) developer as well as a labeled precursor, a preparation method and application thereof. The structural formula of a labeled precursor compound pre-FPPA of the PET imaging agent for targeting the CSF1 receptor provided by the invention is as shown in a formula I, and the structural formula of the PET imaging agent 18F-FPPA for targeting the CSF1 receptor provided by the invention is as shown in a formula II. According to the invention, a 6-Aryl group is used as a pharmacophore, the structure of the 6-Aryl group is completely consistent with that of an original drug in a CSF1 receptor antagonist (DFFPA), only isotope difference exists, and the consistency of stability, affinity and specificity of the 6-Aryl group can be ensured to the greatest extent. The prepared PET imaging agent 18F-FPPA has good stability and pharmacokinetic characteristics, and a foundation is laid for scientific research and clinical application of an F-18 labeled targeted CSF1 receptor PET imaging agent.

A molecular docking method based on a CIM includes: constructing a 3D molecular structure diagram based on a selected drug molecule to obtain a ligand graph; constructing an internal pseudo-atom point diagram of a receptor target based on a selected receptor molecule to obtain a receptor graph; constructing a ligand-receptor similarity graph based on the ligand graph and the receptor graph, where the ligand-receptor similarity graph includes vertices and edges between any two vertices, and any vertex of includes a point in the ligand graph and a point in the receptor graph; determining whether each edge exists; and constructing a pharmacophore model based on the ligand-receptor similarity graph to determine whether the selected drug molecule could inhibit activity of the selected receptor, where the pharmacophore model is configured to calculate a maximum weight clique between the selected drug molecule and the selected receptor to screen a drug molecule compound.

The application belongs to the technical field of pharmaceutical chemistry, and particularly relates to a pyrazine compound and a preparation method and application thereof. The compound provided by the application is screened in a virtual screening and pharmacophore manner, has a novel structure, has good inhibitory activity on MNK1, and the above compound makes up for the problems of insufficient ideal activity and insufficient diversity of chemical structure of existing MNK1 inhibitors, and the like.

The application discloses a method for screening sEH inhibitors based on a pharmacophore model and molecular docking, and belongs to the field of food science and technology. The steps of the method mainly comprise the following steps: preparation of a training set and a test set, construction of a pharmacophore model, construction of a to-be-screened set, screening of the to-be-screened set by using the optimal pharmacophore model and molecular docking, and screening based on binding energy. The application solves the problem that rapidness and accuracy cannot be considered simultaneously in the current polypeptide screening process by jointly using a pharmacophore model and flexible docking.

The present application relates to the field of bioinformatics, and proposes a drug target correlation identification method based on spatial atlas and isometric network. Firstly, the three-dimensional spatial geometric atlas of target protein and the microcosmic chemical topological graph of drug molecule are deduced and constructed respectively, so as to losslessly reserve the physical conformation of receptor and the local pharmacophore of small molecule. Secondly, the three-dimensional isometric graph neural network and the graph message passing mechanism are jointly used for deep feature representation. Finally, the affinity measurement strategy based on hyperbolic space is introduced, the features are losslessly projected into the Poincare ball model with constant negative curvature, and the correlation probability between drugs and targets is predicted by using the non-Euclidean geometric distance. The present application can effectively overcome the feature congestion problem of traditional space, fully excavate the implicit hierarchical information inside complex biological molecules, significantly improve the accuracy and generalization robustness of drug target correlation analysis, and provide effective technical support for new drug research and development, drug repositioning and precise medication.

The application discloses a kind of virtual screening method of antitumor drug with TEAD as target point, belong to antitumor field, a kind of virtual screening method of antitumor drug with TEAD as target point, including following steps: S1: with TEAD2 as receptor protein, the binding site of receptor protein and ligand is predicted;S2: the establishment of pharmacophore model is carried out to binding site, and the pharmacophore that plays a key role in the process of protein and ligand combination is screened out, the key pharmacophore obtained by prediction is used to match and screen Specs database, ligand is sorted according to pharmacophore score, and the ligand that is selected in the front of matching order can be realized, based on the principle and method of key pharmacophore model, dominant water molecule docking and conformation scoring, virtual screening is carried out to Specs database, and the compound with good pharmacophore matching and better docking capacity is screened out, it has good application value and prospect in the development field of antitumor drug with TEAD as target point.

A system and method for pharmacophore-conditioned generation of molecules. The system and method modifies a conditional variational autoencoder (CVAE) such that the latent space in generation of a molecule is not conditioned on the pharmacophore space of the molecule. This allows for generation of pharmacophore descriptors independently from the conditional on which CVAE has been trained, removing a substantial impediment to the use of CVAEs for exploration of pharmacophore descriptors of a molecule.

The invention belongs to the technical field of biological medicine, and particularly relates to an aromatic heterocyclic compound, a preparation method thereof and application of the aromatic heterocyclic compound in tumor resistance. According to the aromatic heterocyclic compound disclosed by the invention, the structural design is based on a structure-activity optimization concept of a bisaryl structure, and the core pyrrolo aromatic ring structure can realize pi-pi stacking and hydrogen bond coordination on a molecular level, so that stable molecular recognition is favorably formed with a protein kinase active pocket or a microtubule binding region; a nitrogen atom of the heterocyclic ring part is used as a hydrogen bond acceptor and forms stable hydrogen bond interaction with a target protein hinge region or key amino acid residues, so that the binding capacity of the compound and a kinase target is enhanced; substituent groups on the aromatic ring part can influence coplanarity and hydrophobic interaction of molecules by adjusting electron cloud density, so that compatibility with a target protein hydrophobic pocket is enhanced; the polarity distribution of the substituent group gives consideration to the solubility and membrane permeability of the compound at the same time, so that the accessibility and pharmacokinetic stability of a pharmacophore at a cellular level are ensured.

The invention discloses a molecular property prediction method based on a frequency domain enhanced graph neural network, and the method comprises the steps: enabling a pre-training module to decompose a molecular graph into three isomer graphs, namely a molecular scaffold graph, a functional group graph and a pharmacophore graph, and capturing the characteristics of different layers of molecules; according to the graph neural network based on a high and low frequency feature extraction module and a dynamic message passing mechanism, the high and low frequency feature extraction module is introduced, so that the modeling capability of complex features of a molecular graph is enhanced; a category weight adjustment mechanism and a task weight adjustment mechanism solve the problems of unbalanced category distribution and multi-task heterogeneity in a molecular property prediction task; and the comparison learning loss calculation module is used for shortening the feature distance of the positive sample pair and deducing the feature distance of the negative sample pair, so that the discrimination capability of molecular prediction is improved. The method shows excellent performance in molecular property prediction tasks, especially has significant advantages in class imbalance and small sample scenes, and has wide practical application value.

The invention discloses a moxifloxacin hapten, antigen and antibody as well as a preparation method and application thereof, and belongs to the technical field of small molecule immunodetection.The moxifloxacin hapten, antigen and antibody are obtained by introducing an alkyl connecting arm-(CH2) n-NH2 with a specific length to a secondary amino group, away from a quinolone mother nucleus, of moxifloxacin, according to the present invention, the carbostyril is introduced into the molecule so as to endow the molecule with chemical operability on the premise of not disturbing the pharmacophore of the quinolone mother nucleus, such that the molecule can efficiently couple the carrier protein and induce the generation of the high affinity and high specificity antibody so as to finally construct the immunodetection system suitable for the treatment drug monitoring and the bedside instant detection scene;

The present disclosure relates to a method and device for designing a target-specific drug in which a deep learning algorithm is combined with a water pharmacophore model. More particularly, the present disclosure relates to a device and method for generating the library of novel compounds by securing specificity to a target protein through a water pharmacophore (WP) model, and then performing deep learning.

A macrocyclic polypeptide bearing a pharmacophore is produced by reacting (i) a peptide with two reactive groups X1 and X2; and (ii) a reactive compound comprising reactive groups Y1, Y2 and Z, such that X1 forms a bond by reaction with Y1 and X2 forms a bond by reaction with Y2. Reactive group Z is then reacted with a compound bearing a pharmacophore R in benign aqueous conditions. The macrocycles may be displayed in a library, such as a phage display library, and used to biopan for affinity against a selected target.

A method of inhibiting phosphorylation of the tau protein and / or a TLR4-mediated immune response is disclosed. The method contemplates administering to cells in recognized need thereof such as cells of the central nervous system an effective amount of a of a compound or a pharmaceutically acceptable salt thereof that binds to a pentapeptide of filamin A (FLNA) of SEQ ID NO: 1, and contains at least four of the six pharmacophores of FIGS. 35-40.