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 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.


CONCLUSIONS
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
Huang
Bingding
B
Bioinformatics Group, Biotechnological Center, Technical University Dresden, Germany. bingding.huang@biotec.tu-dresden.de
Schroeder
Michael
M
D000465:Algorithms; D001665:Binding Sites; D030562:Databases, Protein; D008024:Ligands; D008958:Models, Molecular; D011506:Proteins / Q000737:chemistry*
D008024:Ligands; D011506:Proteins