In silico drug repositioning based on the integration of chemical, genomic and pharmacological spaces.

ABSTRACT:

Background

Drug repositioning refers to the identification of new indications for existing drugs. Drug-based inference methods for drug repositioning apply some unique features of drugs for new indication prediction. Complementary information is provided by these different features. It is therefore necessary to integrate these features for more accurate in silico drug repositioning.

Results

In this study, we collect 3 different types of drug features (i.e., chemical, genomic and pharmacological spaces) from public databases. Similarities between drugs are separately calculated based on each of the features. We further develop a fusion method to combine the 3 similarity measurements. We test the inference abilities of the 4 similarity datasets in drug repositioning under the

SUBMITTER: Chen H 

PROVIDER: S-EPMC7868667 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature