Localization of binding sites in protein structures by optimization of a composite scoring function. Export

@article{citeulike:1049131, abstract = {The rise in the number of functionally uncharacterized protein structures is increasing the demand for structure-based methods for functional annotation. Here, we describe a method for predicting the location of a binding site of a given type on a target protein structure. The method begins by constructing a scoring function, followed by a Monte Carlo optimization, to find a good scoring patch on the protein surface. The scoring function is a weighted linear combination of the z-scores of various properties of protein structure and sequence, including amino acid residue conservation, compactness, protrusion, convexity, rigidity, hydrophobicity, and charge density; the weights are calculated from a set of previously identified instances of the binding-site type on known protein structures. The scoring function can easily incorporate different types of information useful in localization, thus increasing the applicability and accuracy of the approach. To test the method, 1008 known protein structures were split into 20 different groups according to the type of the bound ligand. For nonsugar ligands, such as various nucleotides, binding sites were correctly identified in 55\%-73\% of the cases. The method is completely automated (http://salilab.org/patcher) and can be applied on a large scale in a structural genomics setting.}, address = {Department of Biopharmaceutical Sciences and Pharmaceutical Chemistry, California Institute for Quantitative Biomedical Research, University of California, San Francisco, California 94143-2552, USA. andrea@salilab.org}, author = {Rossi, A. and Marti-Renom, M. A. and Sali, A.}, citeulike-article-id = {1049131}, citeulike-linkout-0 = {http://dx.doi.org/10.1110/ps.062247506}, citeulike-linkout-1 = {http://www.proteinscience.org/cgi/content/abstract/15/10/2366}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/16963645}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=16963645}, doi = {10.1110/ps.062247506}, issn = {0961-8368}, journal = {Protein Sci}, keywords = {binding, function, localization, printed, protein, scoring, site, structure}, month = {October}, number = {10}, pages = {2366--2380}, posted-at = {2007-01-18 19:05:03}, priority = {2}, title = {Localization of binding sites in protein structures by optimization of a composite scoring function.}, url = {http://dx.doi.org/10.1110/ps.062247506}, volume = {15}, year = {2006} }

TY - JOUR ID - citeulike:1049131 L3 - citeulike-article-id:1049131 N2 - The rise in the number of functionally uncharacterized protein structures is increasing the demand for structure-based methods for functional annotation. Here, we describe a method for predicting the location of a binding site of a given type on a target protein structure. The method begins by constructing a scoring function, followed by a Monte Carlo optimization, to find a good scoring patch on the protein surface. The scoring function is a weighted linear combination of the z-scores of various properties of protein structure and sequence, including amino acid residue conservation, compactness, protrusion, convexity, rigidity, hydrophobicity, and charge density; the weights are calculated from a set of previously identified instances of the binding-site type on known protein structures. The scoring function can easily incorporate different types of information useful in localization, thus increasing the applicability and accuracy of the approach. To test the method, 1008 known protein structures were split into 20 different groups according to the type of the bound ligand. For nonsugar ligands, such as various nucleotides, binding sites were correctly identified in 55%-73% of the cases. The method is completely automated (http://salilab.org/patcher) and can be applied on a large scale in a structural genomics setting. IS - 10 JF - Protein Sci SN - 0961-8368 AD - Department of Biopharmaceutical Sciences and Pharmaceutical Chemistry, California Institute for Quantitative Biomedical Research, University of California, San Francisco, California 94143-2552, USA. andrea@salilab.org EP - 2380 TI - Localization of binding sites in protein structures by optimization of a composite scoring function. VL - 15 SP - 2366 KW - binding KW - function KW - localization KW - printed KW - protein KW - scoring KW - site KW - structure AU - Rossi, A AU - Marti-Renom, MA AU - Sali, A PY - 2006/10// UR - http://dx.doi.org/10.1110/ps.062247506 ER -