Drug combination network based drug combined action predicting method

A joint action and combined network technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems that are not suitable for rational discovery of optimal drug combinations, unknown kinetic parameters and intermediate product concentration data, and dynamic models limitations

Inactive Publication Date: 2013-04-24
SICHUAN UNIV
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Problems solved by technology

However, the dynamic simulation method is still limited in its wide application in the rational design of drug combinations. This is mainly due to its inherent shortcomings, that is, the kinetic parameters and intermediate product concentration data of a large number of biochemical reaction

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  • Drug combination network based drug combined action predicting method
  • Drug combination network based drug combined action predicting method
  • Drug combination network based drug combined action predicting method

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[0086] In order to make the content of the present invention easier to be understood clearly, the following further describes the present invention in detail based on specific embodiments in conjunction with the accompanying drawings.

[0087] According to the method of the present invention, this embodiment adopts the following steps:

[0088] 1) Obtain information on drug combination effects for modeling

[0089] The drug combination effect information used in the embodiment of the present invention is obtained from the public drug database TTD (Therapeutic target database, http: / / bidd.nus.edu.sg / group / ttd / ) and the public drug interaction database (DCDB, http: / / www.cls.zju.edu.cn / dcdb / ), the data will be used as a positive data set for building a classification prediction system. The obtained fields include the names of the two drugs, the combined action type, and the action effect. The value of the action type field includes "pharmacodynamics" and "pharmacokinetics". Since the ...

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Abstract

The invention discloses a drug combination network based drug combined action predicting method. The method includes: constructing a drug combination network (DCN), and utilizing the DCN to integrate drug synergism combination information, drug-target mutual action information and target protein-protein mutual action information; and mapping targets of two drugs on the DCN respectively, determining an adjacent group of combined acting drugs in the DCN, determining topological network features and biological function relation features of the adjacent group, integrating the topological network features and the biological function relation features of the adjacent group, determining a feature vector of the adjacent group based on integration, establishing a drug combined action effect predicting model based on a support vector machine (SVM), and adopting the support vector machine classification algorithm to predict whether combination of the two drugs generates synergic effects or not. By the method, combined effects of new drugs can be accurately predicted, and the drug combination network based drug combined action predicting method has important value to accelerate development of novel drug combined treatment schemes.

Description

1. Technical field [0001] The invention relates to the field of computer-aided drug molecule design, in particular to a drug combination effect prediction method based on drug combination network. 2. Background technology [0002] The disease treatment effect of single-component molecular targeted drugs usually cannot be maintained for a long time. Although the disease can be controlled to a certain extent in the short term, relapse often occurs after a certain period of time, and it is difficult to achieve the expected curative effect. This is mainly because there are usually multiple complex and redundant signaling regulatory pathways in cells, through which cells can develop drug resistance to tolerate drug treatment. Therefore, multi-component drug combination therapy can more effectively control cell signaling regulatory pathways by simultaneously regulating multiple biological target molecules in the disease network system, and can overcome the limitations of single-ta...

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Application Information

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IPC IPC(8): G06F19/18
Inventor 邹俊杨胜勇魏于全张康苏智广
Owner SICHUAN UNIV
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