Software

LIGSITE^csc: predicting ligand binding sites using the Connolly surface and degree of conservation

Bingding Huang and Michael Schroeder

Bioinformatics Group, Biotechnological Center, Technical University Dresden, Germany

author email corresponding author email

BMC Structural Biology 2006, 6:19doi:10.1186/1472-6807-6-19

Published:	24 September 2006

Abstract

Background

Identifying pockets on protein surfaces is of great importance for many structure-based drug design applications and protein-ligand docking algorithms. Over the last ten years, many geometric methods for the prediction of ligand-binding sites have been developed.

Results

We present LIGSITE^csc, an extension and implementation of the LIGSITE algorithm. LIGSITE^csc is based on the notion of surface-solvent-surface events and the degree of conservation of the involved surface residues. We compare our algorithm to four other approaches, LIGSITE, CAST, PASS, and SURFNET, and evaluate all on a dataset of 48 unbound/bound structures and 210 bound-structures. LIGSITE^csc performs slightly better than the other tools and achieves a success rate of 71% and 75%, respectively.

Conclusion

The use of the Connolly surface leads to slight improvements, the prediction re-ranking by conservation to significant improvements of the binding site predictions. A web server for LIGSITE^csc and its source code is available at scoppi.biotec.tu-dresden.de/pocket.