Predicting drug-target interaction networks based on functional groups and biological features.

ABSTRACT:

Background

Study of drug-target interaction networks is an important topic for drug development. It is both time-consuming and costly to determine compound-protein interactions or potential drug-target interactions by experiments alone. As a complement, the in silico prediction methods can provide us with very useful information in a timely manner.

Methods/principal findings

To realize this, drug compounds are encoded with functional groups and proteins encoded by biological features including biochemical and physicochemical properties. The optimal feature selection procedures are adopted by means of the mRMR (Maximum Relevance Minimum Redundancy) method. Instead of classifying the proteins as a whole family, target proteins are divided into four groups: enzymes, ion channel

SUBMITTER: He Z 

PROVIDER: S-EPMC2836373 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature