Bingding Huang, Michael Schroeder:
LIGSITEcsc: Predicting ligand binding sites using the Connolly surface and degree of conservation.

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In: BMC Structural Biology 6 (19), September 2006
© BioMed Central

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 LIGSITEcsc, an extension and implementation of the LIGSITE algorithm. LIGSITEcsc 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. LIGSITEcsc 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



	author = {Bingding Huang and Michael Schroeder},
	title = {LIGSITEcsc: Predicting ligand binding sites using the Connolly surface and degree of conservation},
	journal = {BMC Structural Biology},
	year = {2006},
	volume = {6},
	number = {19},
	url = {}