Method for screening and/or designing medicines aiming at multiple targets

A target and drug technology, applied in the field of screening and/or designing drugs targeting multiple targets, can solve the problem of not being able to determine whether multiple targets are active

Active Publication Date: 2011-10-19
SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Similarly, methods such as quantitative structure-activity relationship model, pharmacophore model, machine learning regression analysis, and classification

Method used

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  • Method for screening and/or designing medicines aiming at multiple targets
  • Method for screening and/or designing medicines aiming at multiple targets
  • Method for screening and/or designing medicines aiming at multiple targets

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0101] Example 1. Screening method of the present invention——screening drug leads for the kinase combination Abl-FGFR

[0102] 1. Build a training set

[0103] For the kinase combination Abl-FGFR, one target is Abl (denoted as target K1) and the other target is FGFR (denoted as target K2);

[0104] In the data in the prior art, search for substances that can act on K1 and K2 at the same time. This type of substance is a dual inhibitor, and this type of substance is classified as a positive training set, which is recorded as training set A;

[0105] In the data in the prior art, search for substances that can only act on K1. This type of substance is an inhibitor that inhibits K1 but not K2. This type of substance is classified as a negative training set, which is designated as training set B1 ;

[0106] In the data in the prior art, search for substances that can only act on K2. This type of substance is an inhibitor that inhibits K2 but not K1. This type of substance is cla...

Embodiment 2

[0151] Example 2, screening with the SVM model established without multi-target feature selection

[0152] (1) Construction steps of SVM model

[0153] Step I:

[0154] For the kinase combination Abl-FGFR, one target is Abl (denoted as target K1) and the other target is FGFR (denoted as target K2);

[0155] In the data in the prior art, search for substances that can act on K1 and K2 at the same time. This type of substance is a dual inhibitor, and this type of substance is classified as a positive training set, which is recorded as training set A;

[0156] In the data in the prior art, search for substances that can only act on K1. This type of substance is an inhibitor that inhibits K1 but not K2. This type of substance is classified as a negative training set, which is designated as training set B1 ;

[0157] In the data in the prior art, search for substances that can only act on K2. This type of substance is an inhibitor that inhibits K2 but not K1. This type of substa...

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Abstract

The invention discloses a method for screening and/or designing medicines aiming at multiple targets. The method disclosed by the invention comprises the following steps of: 1) marking k targets as target 1, target 2, ...... and target K, and searching a positive training set and a negative training set; obtaining a multiple-target characteristic based on the positive training set and the negative training set respectively; building a target screening model by using an SVM (Support Vector Machine) method based on the multiple-target characteristic; 2) and judging whether a substance to be screened is a medicine primer targeting a plurality of targets by using the target screening model. The method disclosed by the invention has high screening efficiency, and has broad application prospect in the field of development and design of medicines.

Description

technical field [0001] The present invention relates to a method for screening and / or designing drugs against multiple targets. Background technique [0002] At present, many computational methods have been used for the design of drug molecules targeting single targets, and some have been widely used in the discovery of single-target drug lead compounds. Among them, the most common calculation methods include molecular docking, pharmacophore method, structure-activity relationship (SAR), quantitative structure-activity relationship (QSAR), similarity search, machine learning and the combined application of the above methods. Recently, some of the above computational methods have been developed for the discovery of multi-target lead compounds, mainly based on fragment assembly methods and combinatorial methods. The method based on fragment splicing is to connect the backbone bonds of two molecules that are respectively targeted at different targets to form a single molecule,...

Claims

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Application Information

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IPC IPC(8): G06F19/24G06F19/16
Inventor 蒋宇扬陈宇综马晓华
Owner SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
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