NovoFLAP: A ligand-based de novo design approach for the generation of medicinally relevant ideas.

NovoFLAP is a computer-aided de novo design tool that generates medicinally relevant ideas for ligand-based projects. The approach combines an evolutionary algorithm (EA-Inventor) with a powerful ligand-based scoring function that uses both molecular shape and pharmacophore features in a multiconformational context (FLAP). We demonstrate that NovoFLAP can generate novel ideas that are not only appealing to design scientists but are also validated by comparison to compounds known to demonstrate activity at the desired biological target. NovoFLAP provides a novel computer-aided design technique that can be used to generate ideas that maintain desirable molecular attributes, such as activity at the primary biological target, while offering opportunities to surmount additional design challenges. Application to the design of the first nonbasic 5HT(1B) antagonist is presented.

Statistical tools for virtual screening.

In large-scale virtual screening (VS) campaigns, data are often computed for millions of compounds to identify leads, but there remains the task of prioritizing VS "hits" for experimental assays and the dilemma of assessing true/false positives. We present two statistical methods for mining large databases: (1) a general scoring metric based on the VS signal-to-noise level within a compound neighborhood; (2) a neighborhood-based sampling strategy for reducing database size, in lieu of property-based filters.