title: Protein-protein binding sites prediction by 3D structural similarities.
abstract: Identifying the location of binding sites on proteins is of fundamental importance for a wide range of applications including molecular docking, de novo drug design, structure identification, and comparison of functional sites. In this paper, we develop an efficient approach for finding binding sites between proteins. Our approach consists of four steps: local sequence alignment, protein surface detection, 3D structure comparison, and candidate binding site selection. A comparison of our method with the LSA algorithm shows that the binding sites predicted by our method are somewhat closer to the actual binding sites in the protein-protein complexes. The software package is available at  http://sites.google.com/site/guofeics/pro-bs  for noncommercial use.
authors.affiliation: School of Computer Science and Technology, Shandong University, Jinan 250101, Shandong, China.
authors.forename: Fei
authors.initials: F
authors.lastname: Guo
authors.forename: Shuai Cheng
authors.initials: SC
authors.lastname: Li
authors.forename: Lusheng
authors.initials: L
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D008954:Models, Biological; D008958:Models, Molecular; D011485:Protein Binding; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D016415:Sequence Alignment / Q000379:methods; D012984:Software
chemical_list: D011506:Proteins