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Method for predicating drug-target combination based on grey theory and molecular fingerprints

A prediction method and molecular fingerprint technology, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., can solve the problems of difficult discovery and interpretation, time-consuming and labor-intensive determination of drug-target combination, etc., and achieve the improvement of prediction success rate, The effect of strong promotion and application value

Inactive Publication Date: 2013-02-13
JINGDEZHEN CERAMIC INSTITUTE
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Problems solved by technology

Drugs have many effects (including positive and side effects), and humans have very complex biochemical reaction pathways. Even some populations with slightly different genes may have completely different reactions to the same drug, so it is very difficult to discover and explain these possible effects. Difficult, using experimental methods to determine drug-target binding is time-consuming and laborious, so designing an algorithm that can predict whether a drug and a target can bind will help in the development of new drugs

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  • Method for predicating drug-target combination based on grey theory and molecular fingerprints
  • Method for predicating drug-target combination based on grey theory and molecular fingerprints
  • Method for predicating drug-target combination based on grey theory and molecular fingerprints

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Embodiment Construction

[0036] In order to make the purpose, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, and are not intended to limit the invention.

[0037] figure 1 It shows the implementation process of the drug-target binding prediction method based on gray theory and molecular fingerprint provided by the embodiment of the present invention.

[0038] The forecasting method includes the following steps:

[0039] Step S101, generating protein pseudo amino acid components based on the gray theory GM (1,1) model, and converting the target protein sequence into a 21-dimensional space vector in combination with the amino acid components of the protein sequence;

[0040] Step S102, describe the drug molecule as a 256-dimensional space...

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Abstract

The invention discloses a method for predicating drug-target combination based on the grey theory and molecular fingerprints. The method includes generating protein pseudo amino acid compositions based on a gray theory gray model (GM) (1,1) and converting target protein sequences into 21-dimensional spatial vectors combined with the protein sequence pseudo amino acid compositions; describing drug molecules into a 256-dimensional spatial vector through a drug molecular fingerprint software; combining the 21-dimensional spatial vectors of the protein sequences and the 256-dimensional spatial vector of the drug molecules into 277-dimensional spatial vectors to serve as drug-target combination descriptors; and training sets are trained through a fuzzy K-nearest neighboring method to obtain optimum parameters of a predictor and the drug-target combination descriptors are input into the predictor to predicate whether a drug is associated with a target. According to the method, three-dimensional structures of proteins are not needed to be measured, whether the drug and the proteins can be combined can be predicated by only adding drug molecular fingerprints on a protein one dimensional sequence, and the predication success rate is high.

Description

technical field [0001] The invention belongs to the technical field of drug-target combination, and in particular relates to a method for predicting drug-target combination based on gray theory and molecular fingerprints. Background technique [0002] Identifying drug-target binding is an important step in the drug design process. In recent years, humans have made great efforts to discover new drugs, but the number of new drugs is still very low (about 30 kinds per year). This is partly due to the unacceptable toxicity of many potential drugs. It would be very beneficial to develop algorithms that can predict the sensitivity and toxicity of drugs before they are synthesized. Drugs have many effects (including positive and side effects), and humans have very complex biochemical reaction pathways. Even some populations with slightly different genes may have completely different reactions to the same drug, so it is very difficult to discover and explain these possible effects...

Claims

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Application Information

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IPC IPC(8): G06F19/00G06F19/18
Inventor 肖绚闵建亮
Owner JINGDEZHEN CERAMIC INSTITUTE
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