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Drug-target combined predicating method based on complexity and molecular fingerprints

A prediction method and molecular fingerprinting technology, applied in special data processing applications, instruments, electronic digital data processing, etc., can solve the problems of time-consuming and laborious determination of drug-target binding, difficulty in discovery and interpretation, and achieve strong promotion and application value. , predict the effect of improving the success rate

Inactive Publication Date: 2015-06-03
JINGDEZHEN CERAMIC UNIV
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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

Method used

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  • Drug-target combined predicating method based on complexity and molecular fingerprints
  • Drug-target combined predicating method based on complexity and molecular fingerprints
  • Drug-target combined predicating method based on complexity and molecular fingerprints

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Embodiment Construction

[0033] 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, not to limit the invention.

[0034] figure 1 It shows the implementation process of the drug-target binding prediction method based on the complexity and molecular fingerprint provided by the embodiment of the present invention.

[0035] The forecasting method includes the following steps:

[0036] Step S101, generating protein pseudo amino acid components based on the complexity and the doublet, combining the protein sequence amino acid components to convert the target protein sequence into a 421-dimensional space vector;

[0037] Step S102, describe the drug molecule as a 256-dimensional space vector through the drug molecule ...

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Abstract

The invention discloses a drug-target combined predicating method based on complexity and molecular fingerprints. On the basis of the complexity and amino acid diad compositions, protein pseudo-amino acid compositions are generated, and protein sequence amino acid compositions are combined to convert target protein sequences into a 421 dimensional spatial vector; drug molecules are described into a 256 dimensional spatial vector through drug molecular fingerprint software; the 421 dimensional spatial vector which describes the protein sequences and the 256 dimensional spatial vector which describes the drug molecules are combined to form a 677 dimensional spatial vector serving as a drug-target combined descriptor; and an ambiguity K neighboring method is used for training a training set to obtain the best parameter of a predictor, and the drug-target combined descriptor is input into the predicator for predicating whether a drug is related to a target. According to the method, three dimensional structures of protein are not required to be measured, only one-dimensional sequences of the protein and the drug molecular fingerprints are required to predicate whether the drug and the protein can be combined, and the predicating success ratio 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 complexity 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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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/10
Inventor 肖绚闵建亮
Owner JINGDEZHEN CERAMIC UNIV
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