@article {16963645, title = {Localization of binding sites in protein structures by optimization of a composite scoring function}, journal = {Protein Sci}, volume = {15}, number = {10}, year = {2006}, note = {Rossi, Andrea Marti-Renom, Marc A Sali, Andrej P01 AI035707/AI/NIAID NIH HHS/United States R01 GM54762/GM/NIGMS NIH HHS/United States Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov{\textquoteright}t United States Protein science : a publication of the Protein Society Protein Sci. 2006 Oct;15(10):2366-80. Epub 2006 Sep 8.}, pages = {2366-80}, 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.}, keywords = {Amino Acid Sequence Binding Sites Biomechanics Hydrophobicity Ligands *Monte Carlo Method Protein Conformation Proteins/*chemistry Static Electricity}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=16963645}, author = {Rossi, A. and M. A. Marti-Renom and Sali, A.} }