title: Identification of ligand binding sites of proteins using the Gaussian Network Model.
abstract: The nonlocal nature of the protein-ligand binding problem is investigated via the Gaussian Network Model with which the residues lying along interaction pathways in a protein and the residues at the binding site are predicted. The predictions of the binding site residues are verified by using several benchmark systems where the topology of the unbound protein and the bound protein-ligand complex are known. Predictions are made on the unbound protein. Agreement of results with the bound complexes indicates that the information for binding resides in the unbound protein. Cliques that consist of three or more residues that are far apart along the primary structure but are in contact in the folded structure are shown to be important determinants of the binding problem. Comparison with known structures shows that the predictive capability of the method is significant.
authors.affiliation: Center for Computational Biology and Bioinformatics, Koc University, Istanbul Turkey.
authors.forename: Ceren
authors.initials: C
authors.lastname: Tuzmen
authors.forename: Burak
authors.initials: B
authors.lastname: Erman
mesh_terms: D001665:Binding Sites; D006801:Humans; D008024:Ligands; D008958:Models, Molecular; D011485:Protein Binding; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism
chemical_list: D008024:Ligands; D011506:Proteins