The role of computational methods in the identification of bioactive compounds

Computational methods play an ever increasing role in lead finding. A vast repertoire of molecular design and virtual screening methods emerged in the past two decades and are today routinely used. There is increasing awareness that there is no single best computational protocol and correspondingly there is a shift recommending the combination of complementary methods. A promising trend for the application of computational methods in lead finding is to take advantage of the vast amounts of HTS (High Throughput Screening) data to allow lead assessment by detailed systems-based data analysis, especially for phenotypic screens where the identification of compound-target pairs is the primary goal. Herein, we review trends and provide examples of successful applications of computational methods in lead finding.

► Computational compound library design is an essential component for successful lead identification. ► Complementary virtual screening methods used in combination are superior to cascade or consensus virtual screening protocols. ► Computational systems-based analysis of cellular high-throughput screening data promises the possible deconvolution of black-box screens and to allow the identification of relevant compound-target pairs. ► Knowledge-based drug repositioning predicts novel drug-target interactions and is a useful lead finding approach.