34 results about "Quantitative structure–activity relationship" patented technology

The invention discloses a method for forecasting the acute toxicity of organic compounds by building a quantitative structure-activity relationship model with a quantum chemistry method. The method fully geometrically optimizes compound structures by using a Gaussian procedure so as to obtain quantum chemistry parameters including molecular volume, relative molecular mass, highest occupied molecular orbital energy, lowest unoccupied molecular orbital energy, energy gaps of frontier molecular orbital, dipole moment, solvation energy, electron energy and the like; using the quantum chemistry parameters and a hydrophobicity parameter as structural descriptors; in combination with toxicity data, quantitative relationship equations between various structural descriptors and toxicity are established according to a written procedure based on partial least square stepwise linear regression to obtain the multiple correlation coefficient, F-test value and sum of squared residuals, and then the model is verified so as to guarantee the external predictive ability. Therefore, the method can quickly and effectively forecast the toxicity of organic compounds to be studied, and provide necessary basic data for risk assessment and supervision of chemicals.

The invention discloses a building method of a two-level fitting quantitative structure-activity relationship (QSAR) model for forecasting compound activity. The building method includes following procedures: 1 a plurality of compounds with the same frames are utilized as a training set, and the train set compounds are divided into substituent groups and are coincided; 2 a linear regression method is utilized to calculate local physiological action produced by each substituent group, and a preceding-stage fitting model is built; 3 according to the local physiological action which is obtained in calculating mode in the procedure 2, a neural network method is utilized to calculate the whole biological activity, and a backward-stage fitting model is built; and 4 the preceding-stage fitting model and the backward-stage fitting model are combined to form the front-and-back two-stage QSAR model. According to the building method, the linear regression method and the neural network method are combined to build the model, the neural network method has good fitting performance, and compared with a traditional linear model, the built model can accurately forecast the biological activity of the compounds.

The invention discloses a method for predicting organic chemical biodegradability according to a logistic regression algorithm. According to the method for predicting organic chemical biodegradability, on the basis that the molecular structure of a compound is obtained, a person just needs to calculate descriptors of representational structure characteristics and use a built quantitative structure-activity relationship (QSAR) model, and accordingly the biodegradability of the organic compound can be fast and efficiently predicted. The method for predicting organic chemical biodegradability is low in cost, and easy and convenient and fast to adopt, and saves large required labor sources, cost and time. According to the method for predicting organic chemical biodegradability, modeling completely accords with the QSAR model building and guidelines for use of the Organization for Economic Co-operation and Development (OECD), only 14 molecular structure descriptors are adopted, the logistic regression method which is clear and transparent in algorithm is applied, and therefore the method for predicting organic chemical biodegradability is easy to understand and apply. Model application fields are explicit, and 1629 kinds of compounds are covered. The method for predicting organic chemical biodegradability according to the logistic regression method has good fitting effect, robustness and prediction ability, can effectively predict biodegradability of a plurality of organic compounds and provide important data support to organic chemical risk assessment and management, and has important significance in ecological risk assessment.

The invention relates to a building method of a 3-dimensional quantitative structure-activity relationship (3D-QSAR) model, in particular to building of the 3D-QSAR model based on HIV-1 inhibitor molecules and consistency model building, and belongs to the technical field of biological information. The HIV-1 inhibitor molecules are selected to perform 3D-QSAR and consistency model research so as to mine the relationship between the structure of an inhibitor and the anti-HIV activity of the inhibitor. According to the method, the bioactivities of compounds with similar structures are predicted through building of a mathematical model based on the chemical characteristics (such as hydrophilcity, hydrophobicity, electrostatic property, polarity and three-dimensional structure) of the inhibitor. A consistency model is built with a statistics method on the basis of three 3D-QSAR models, and the aim is to further enhance the prediction capability of the model. The obtained model can better predict the anti-HIV activities of compounds, and the prediction accuracy of the anti-HIV activity of a brand new compound is increased. Compared with other methods, the method has the advantages that the medicament discovery efficiency is increased, and the medicament discovery cost is reduced.

The invention relates to a method for predicting affinity of the interaction between a biomarker p53 and an organic phosphate fire retardant. The method includes the following steps of establishing a quantitative structure-activity relationship QSAR model of the affinity KD and training set compound molecule descriptors through a partial least square method so as to obtain an affinity KD value, and predicting the affinity according to the affinity KD value. By the adoption of the method, interaction between the organic phosphate fire retardant and the biomarker p53 which are of different structures can be predicted, the method is low in cost and easy, convenient and rapid to achieve, and a large amount of labor, a large number of expenses and a large amount of time which are needed by experimental tests can be saved; the prediction result obtained through the method can provide the important data support for organic chemical ecological risk assessment and management, and the method has important theoretical and practical significance.

The invention relates to a method for predicating vapor pressure of liquid phase of organic substance by quantitative structure-activity relationship model. On the basis of known compound structure, the method computes molecular structural descriptor of the structure and uses the quantitative relationship between the built molecular structure and vapor pressure to predicate liquid phase vapor pressure of the organic compound quickly and effectively. The method can be applied in a plurality of kinds of organic compounds, can predicate vapor pressure at different temperature values is suitable for obtaining vapor pressure data in different countries and areas in different latitudes and altitudes and provides necessary base data for risk assessment and supervision of chemicals.

The invention discloses a method for predicting acute toxicity of an organophosphorous flame retardant on a zebra fish based on QSAR/QEcoSAR method combination and belongs to the technical field of quantitative structure-activity relationship (QSAR) for chemical environment supervision. The method comprises the steps that based on the chemical reaction principle and the minimum energy principle, QSAR and QEcoSAR are combined, and a multivariate linear regression method is adopted to construct a QSAR model of LC50 and training set compound molecule descriptors (electronegativity, chemical hardness, chemical force, eletrophilicity and other characteristics). The method is low in cost and convenient and fast to use, and a large amount of manpower, cost and time needed in experimental testingcan be saved; and by use of the prediction result, important data support can be provided for ecological risk evaluation and management of organophosphorous chemicals, and therefore the method has important realistic significance and theoretical value.

The invention discloses a method for predicating the acute toxicity of organophosphorus pesticide on aquatic organisms through the quantitative structure activity relationship. On the basis that the structure of chemical compound is known, geometrical full optimization is performed on a Gaussian program to obtain the MV, the MW, the EHOMO, the ELUMO, the difference value delta E (hartree), the DM and the like to serve as structural descriptors, regression parameters of all parameters, the multiple correlation coefficient and an F-test value are obtained in combination with data of toxicity of the organophosphorus pesticide on aquatic organisms through the programmed partial least squares stepwise linear regression program, and quantitative relationships between the various structural descriptors and the toxicity. Thus, the toxicity of the organophosphorus pesticide on the aquatic organisms can be fast, conveniently and effectively predicted, and essential basic data are provided for risk assessment and supervision on the organophosphorus pesticide.

The invention relates to a method for constructing a three-dimensional quantitative structure activity relationship model of a B-cell lymphoma-2 (Bcl-2) protein inhibitor and application of the method and belongs to the technical field of biological information. The method comprises the following steps of: according to the known small molecule inhibitor, establishing the three-dimensional quantitative structure activity relationship model of the Bcl-2 protein inhibitor by using a three-dimensional quantitative structure activity relationship technology; and further improving the accuracy of the model by using technologies for analyzing molecular similarity, optimizing molecular conformation, optimizing parameters and the like. By the invention, the Bcl-2 protein binding constants of an active unknown compound can be quickly predicted, and clues of the active compound are acquired within short time. Compared with the conventional high-throughput screening technology, the invention has the advantages of greatly improving screening efficiency and reducing cost.

The present invention relates to a seawater quality reference prediction method based on a quantitative structure-activity relationship of metal and metalloid. According to the method, the toxic endpoint of unknown metal is predicted according to a quantitative relationship between the structural feature of metallic ions and the marine life acute toxic effect, and a risk concentration for protecting different proportions of marine life is analyzed and deduced in conjunction with sensitivity distribution of different species; and a QSAR metal toxicity prediction model is established by integrating metal physical and chemical structure parameters and toxic mechanisms of different marine life and is applied to prediction of an unknown seawater quality reference maximum concentration. The seawater acute reference prediction method based on the metal quantitative structure-activity relationship is based on the ecology principle; the system screens various marine species and takes the screened marine species as smallest biological prediction sets; and single-parameter toxicity prediction models are established separately, thereby improving the model precision and prediction ability.

The present invention relates to the development of a virtual screening model for predicting antipsychotic activity using quantitative structure activity relationship (QSAR), molecular docking, oral bioavailability, ADME and Toxicity studies. The present invention also relates to the development of QSAR model using forward stepwise method of multiple linear regression with leave-one-out validation approach. QSAR model showed activity-descriptors relationship correlating measure (r²) 0.87 (87%) and predictive accuracy of 81% (rCV²=0.81). The present invention specifically showed strong binding affinity of the untested (unknown) novel compounds against anti-psychotic targets viz., Dopamine D2 and Serotonin (5HT_2A) receptors through molecular docking approach. Theoretical results were in accord with the in vitro and in vivo experimental data. The present invention further showed compliance of Lipinski's rule of five for oral bioavailability and toxicity risk assessment for all the active Yohimbine derivatives. Therefore, use of developed virtual screening model will definitely facilitate the screening of more effective antipsychotic leads/drugs with improved antipsychotic activity and also reduced the drug discovery cost and duration.

The invention aims to establish an efficient, fast and reliable screening method of TTR (transthyretin) small-molecule inhibitors, overcomes the defects of the prior art and is applicable to design of medicines for amyloidosis caused by TTR fibrosis. A small-molecule database is screened and predicted by means of 3D-QSAR (3-dimensional quantitative structure activity relationship), molecular docking, pharmacophore models and the like; small molecules capable of serving as lead compounds are determined preliminarily; further cell screening is performed. The screening method is fast and efficient; a plurality of drug screening and design methods based on receptors and ligands are applied; accordingly, reliability of screening results is improved greatly. Cell levels are subjected to biological screening by lead compounds obtained by screening, so that screening speed is higher and development and search cycle of novel inhibitors is shortened.

The invention provides rabies virus inhibition polypeptide. The sequence of the rabies virus inhibition polypeptide is PPDVHTPPHALWRLHLILRVELVRMWWH, and belongs to the field of biochemistry and molecular biology. After being optimized by using QSAR (Quantitative Structure Activity Relationship), the polypeptide and cell-penetrating peptide form fusion peptide, and thus a function of inhibiting virus replication in cells can be achieved. The method is high in specificity, easy to operate and applicable to control on post-cell rabies viruses.

The invention relates to a method for determining a magnetic type of a hexagonal crystal system metal oxide by utilizing a computer. The method belongs to the technical field of quantitative structure-activity relationship for ecological risk assessment. The method utilizes a Visualizer module of MS software to construct a crystal model based on lattice parameters of hexagonal crystal system metaloxidation; converting an original unit cell into a rhombohedral lattice primitive cell by utilizing Symmetry in a Build function of the Visualizer module of the software; setting magnetic propertiesand magnetic moment for metal atoms in the lattice along a diagonal of a formal spin in electronic configuration by utilizing a Modify function of the Visualizer module of the software; performing quantum mechanics structure optimization processing by utilizing a Geometry Optimization function in a Dmol3 module of the MS software, and calculating energy of the metal oxide with different magnetic properties by using an Energy function in the Dmol3 module; and finally comparing the energy under different magnetic conditions by utilizing the Visualizer module of the MS software, and determining the magnetic type of the hexagonal crystal system metal oxide. The method disclosed by the invention has the advantages of rapid computing, simple operation, low equipment requirement, wide measurementrange and high precision.

A three-dimensional quantitative structure-activity relationship method has process B1 of calculating the coordinates of the respective atoms contained in the plural molecules thus superposed in the virtual space, process B2 of calculating interatomic distances between each atom and other atoms and identifying the shortest interatomic distance among thus calculated interatomic distances and two atoms constituting the shortest interatomic distance; process B3 of deleting the two atoms having the shortest interatomic distance from the three-dimensional space and generating an atom which represents the two atoms in the weighted average coordinates of the two atoms to delete, when the shortest interatomic distance thus calculated is equal to or smaller than a predetermined threshold value; process B4 of returning to the second process B2 after the third process B3 and executing the second process B2 including the atoms formed during the third process B3; and process B5 of terminating the process B when the shortest interatomic distance thus calculated is exceeds the predetermined threshold. This method enables strikingly reducing the memory zone and amount of computation required for 3D QSAR analysis.

The invention discloses a method for predicting a hydrolysis rate of sulfur-containing organic compounds in the atmosphere, and belongs to the field of ecological risk assessment test strategies. A QSAR (Quantitative Structure Activity Relationship) model is constructed by adopting a partial least squares and a multiple linear regression, and the hydrolysis rate of the sulfur-containing organic compounds is obtained according to the QSAR model. The model of the invention is wide in application and has good practicability, stability and prediction effect. The hydrolysis rate of the sulfur-containing organic compounds in the atmosphere can be effectively and quickly predicted on the basis of obtaining a sulfur-containing organic molecular structure only by calculating a descriptor which represents a structural feature and applying the QSAR model. The prediction method has the characteristics of being convenient and fast, low in cost, and can provide important data support for the ecological risk assessment and management of the sulfur-containing organic compounds and is of great significance.

The invention belongs to the field of medicines and provides a medicine screening method and relative medicines, a medicine package, a sustained release preparation, a targeting preparation, a controlled release preparation, a quick release preparation and a treatment method. The medicine screening method provided by the invention is used for screening compounds with the same parent nucleus (or the same framework) in a combined manner, wherein the compounds include synthetic compounds and bio-transformed compounds but not include compounds contained in organisms. The compounds only refer to the compounds with the same structural formula, and chemical isomers with the same molecular formula are regarded as one compound. The screening method does not comprise a step of screening the compounds with the same parent nucleus which are obtained through combinatorial chemistry. The medicine screening method, the obtained medicines and the application thereof provided by the invention have the advantages as follows: 1, combinations of chemicals in hundreds of years are retrospectively studied, thereby improving the medicine screening purposiveness and reducinig the development cost and the societal public burden; 2, the treatment effect is improved, and the toxic and side effects are reduced; and 3, the research dimensionality of the quantitative structure-activity relationship (QSAR) is widened.