Analysis of multiple compound-protein interactions reveals novel bioactive molecules.

ABSTRACT: The discovery of novel bioactive molecules advances our systems-level understanding of biological processes and is crucial for innovation in drug development. For this purpose, the emerging field of chemical genomics is currently focused on accumulating large assay data sets describing compound-protein interactions (CPIs). Although new target proteins for known drugs have recently been identified through mining of CPI databases, using these resources to identify novel ligands remains unexplored. Herein, we demonstrate that machine learning of multiple CPIs can not only assess drug polypharmacology but can also efficiently identify novel bioactive scaffold-hopping compounds. Through a machine-learning technique that uses multiple CPIs, we have successfully identified novel lead compounds fo

SUBMITTER: Yabuuchi H 

PROVIDER: S-EPMC3094066 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature