LIGSITEcsc:: predicting ligand binding sites using the Connolly surface and degree of conservation

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 LIGSITEcsc and its source code is available at scoppi.biotec.tu-dresden.de/pocket.