Predicting drug side-effect profiles based on drug target profiles

Abstract

Identifying the mode-of-action of drug side effects is an important issue in drug discovery. It is necessary to analyze the association between drug-protein interactions (molecular scale) and side effects (phenotypic scale). We propose a new method for large-scale analysis of targeted proteins and side effects, using sparse canonical correlation analysis on the co-occurrence of drugs in target protein profiles and side effect profiles. The proposed method enables us to make a biologically relevant interpretation regarding the relationship between drug–targeted proteins and side effects. We performed pathway enrichment analyses based on biological pathways in the KEGG Pathway database. It was observed that most of the correlated sets tended to be significantly enriched with target proteins that are involved in the same biological pathways, even if the molecular functions of those proteins are different. The proposed method is expected to be useful for predicting potential side effect profiles of drugs or new drug candidate compounds based on their target protein profiles.