Identifying problematic drugs based on the characteristics of their targets.

ABSTRACT: Identifying promising compounds during the early stages of drug development is a major challenge for both academia and the pharmaceutical industry. The difficulties are even more pronounced when we consider multi-target pharmacology, where the compounds often target more than one protein, or multiple compounds are used together. Here, we address this problem by using machine learning and network analysis to process sequence and interaction data from human proteins to identify promising compounds. We used this strategy to identify properties that make certain proteins more likely to cause harmful effects when targeted; such proteins usually have domains commonly found throughout the human proteome. Additionally, since currently marketed drugs hit multiple targets simultaneously, we combined

SUBMITTER: Lopes TJ 

PROVIDER: S-EPMC4555035 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature