Achieving efficient 3-D comparison models for discovering new therapeutic drugs

Discovering new drugs to treat diseases is often a lengthy and a costly process - we all know that. We may also know that the process involves a combination of lab-based and computational approaches.

Recently scientists have come up with a new virtual screening approach that involves using the 3D structural data of chemical compounds and use them to structurally dock-fit them against a target molecule. The findings appear in the recent issue of the Journal BMC Bioinformatics -an open access journal. The article is available for free download at http://www.biomedcentral.com/1471-2105/10/245.

Called 'LigCSRre', the new computational approach combines a 3D maximum common substructure search algorithm, with a tunable description of atomic compatabilities.

Using 47 experimentally validated active compounds across five protein targets having different specificities, the approach was able to recover about 52% of the co-actives in the top 1% of the ranked list, for a single compound search. The scientists claim this to be better than gold standards of the field while calling it a new efficient and generic approach to the 3D similarity screening of small compounds. Further the flexibility in the software program's structure is stated to open doors for many enhancements.

The program is freely available to the academics for non-profit research at http://bioserv.rpbs.univ-paris-diderot.fr/LigCSRre.html.