title: Interactions in native binding sites cause a large change in protein dynamics.
abstract: Cellular functions are regulated by molecules that interact with proteins and alter their activities. To enable such control, protein activity, and therefore protein conformational distributions, must be susceptible to alteration by molecular interactions at functional sites. Here we investigate whether interactions at functional sites cause a large change in the protein conformational distribution. We apply a computational method, called dynamics perturbation analysis (DPA), to identify sites at which interactions have a large allosteric potential D(x), which is the Kullback-Leibler divergence between protein conformational distributions with and without an interaction. In DPA, a protein is decorated with surface points that interact with neighboring protein atoms, and D(x) is calculated for each of the points in a coarse-grained model of protein vibrations. We use DPA to examine hundreds of protein structures from a standard small-molecule docking test set, and find that ligand-binding sites have elevated values of D(x): for 95% of proteins, the probability of randomly obtaining values as high as those in the binding site is 10(-3) or smaller. We then use DPA to develop a computational method to predict functional sites in proteins, and find that the method accurately predicts ligand-binding-site residues for proteins in the test set. The performance of this method compares favorably with that of a cleft analysis method. The results confirm that interactions at small-molecule binding sites cause a large change in the protein conformational distribution, and motivate using DPA for large-scale prediction of functional sites in proteins. They also suggest that natural selection favors proteins whose activities are capable of being regulated by molecular interactions.
authors.affiliation: Computer and Computational Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.
authors.forename: Dengming
authors.initials: D
authors.lastname: Ming
authors.forename: Michael E
authors.initials: ME
authors.lastname: Wall
mesh_terms: D000465:Algorithms; D000818:Animals; D001665:Binding Sites; D000081247:CSK Tyrosine-Protein Kinase; D002417:Cattle; D017364:Collagenases / Q000737:chemistry; D006801:Humans; D008024:Ligands; D008958:Models, Molecular; D009113:Muramidase / Q000737:chemistry; D011485:Protein Binding; D011487:Protein Conformation; D011505:Protein-Tyrosine Kinases / Q000737:chemistry; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D019809:Streptavidin / Q000737:chemistry; D013552:Swine; D014362:Trypsinogen / Q000737:chemistry; D014422:Turkeys; D019061:src-Family Kinases
chemical_list: D008024:Ligands; D011506:Proteins; D014362:Trypsinogen; D019809:Streptavidin; D011505:Protein-Tyrosine Kinases; D000081247:CSK Tyrosine-Protein Kinase; D019061:src-Family Kinases; C000631346:CSK protein, human; D009113:Muramidase; D017364:Collagenases