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Support vector machine based antiviral inhibitor dissociation rate constant prediction method

A technology of support vector machines and rate constants, applied in the field of bioinformatics, which can solve the problems of drug development loss, no consideration of complex binding kinetics, slow dissociation rate, etc.

Inactive Publication Date: 2016-03-30
BEIJING UNIV OF TECH
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Problems solved by technology

[0006] In the process of early new drug development, since the binding kinetics of the complex was not considered, only the K of the compound d or IC 50 Value as the standard for screening drugs, it is likely to eliminate many compounds with slightly lower affinity but slow dissociation rate, resulting in losses in drug development

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  • Support vector machine based antiviral inhibitor dissociation rate constant prediction method
  • Support vector machine based antiviral inhibitor dissociation rate constant prediction method
  • Support vector machine based antiviral inhibitor dissociation rate constant prediction method

Examples

Experimental program
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Embodiment 1

[0053] Take the influence of the antiviral inhibitor structure on the dissociation rate as an example to specifically illustrate the implementation process of the present invention:

[0054] (1) Acquire molecular descriptors. The molecular descriptor calculation software used in this experiment is Dragon1.1. Input the collected antiviral inhibitor molecules into Dragon, and the calculation software will calculate more than 1600 descriptors in 20 categories. Antiviral Inhibitor K off The value is logarithmically processed, thus establishing a logK off The data sets corresponding to the corresponding inhibitor descriptors are shown in Table 1 (see Table 1 on the attached page).

[0055] (2) Preliminary screening of the data set. The preliminary screening tool we choose is SPSS software. Import the data in step (1) into SPSS to conduct preliminary screening on the data set. The specific screening steps are as follows:

[0056] (2-1) Descriptors having the same data in 90% ...

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Abstract

The present invention discloses a support vector machine based antiviral inhibitor dissociation rate constant prediction method, and belongs to the field of bioinformatics. The method comprises: obtaining a molecular descriptor dataset of anti-viral drugs, screening the dataset by using medical and statistical software SPSS and partial least squares Genetic Algorithms (GA-PLS), inputting the screened dataset into a Matlab, and establishing a regression model by using a support vector machine method. According to the method disclosed by the present invention, the regression prediction model is established by using the molecular descriptor of the drug and a corresponding Koff value, and the Koff value prediction is realized by using the simple and practical method, so that a research process of a relation between the chemical structure and the binding dynamics can be promoted, development efficiency of drug development is improved, and the development cost is reduced.

Description

technical field [0001] The present invention relates to a dissociation rate (K off ) value prediction method, belongs to the field of bioinformatics. Background technique [0002] In recent years, in the process of creating and researching new drugs, the kinetic properties between drugs and targets have attracted more and more attention. Kinetic properties are an activity characteristic that is closely related to in vivo efficacy and safety. During the development of new drugs, the dissociation constant (K d ) or IC 50 The value is determined in the equilibrium state of the closed system, while the drug is in an open system in the body, the concentration and environment are constantly changing, K d or IC 50 Values ​​cannot fully reflect the actual state of drug-target binding in vivo. Therefore, we cannot take K d and IC 50 value as the only criterion for screening drugs. while the K of the complex off Independent of the concentration of free drug, drugs with slow ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
CPCG16B40/00
Inventor 谭建军韩晓丁李春华张小轶王存新
Owner BEIJING UNIV OF TECH
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