Exploring the biologically relevant chemical space for drug discovery.

Both recent studies and our calculation suggest that the physicochemical properties of launched drugs changed continuously over the past decades. Besides shifting of commonly used properties, the average biological relevance (BR) and similarity to natural products (NPs) of launched drugs decreased, reflecting the fact that current drug discovery deviated away from NPs. To change the current situation characterized by high investment but low productivity in drug discovery, efforts should be made to improve the BR of the screening library and hunt drugs more effectively in the biologically relevant chemical space. Additionally, a multiple dimensional molecular descriptor, named the biologically relevant spectrum (BRS) was proposed for quantitative structure-activity relationships (QSAR) study or screening library preparation. Prediction models for 43 biological activity categories were developed with BRS and support vector machine (SVM). In most cases, the overall prediction accuracies were around 95% and the Matthew's correlation coefficients (MCC) were over 0.8. Thirty-seven out of 48 drug-activity associations were successfully predicted for drugs that launched from 2006 to 2012, which were not included in the training data set. A web-server named BioRel ( http://ibi.hzau.edu.cn/biorel ) was developed to provide services including BR, BRS calculation, activity class, and pharmacokinetic property prediction.