Automatic identification and representation of protein binding sites for molecular docking. Export

@article{citeulike:211806, abstract = {Molecular docking is a popular way to screen for novel drug compounds. The method involves aligning small molecules to a protein structure and estimating their binding affinity. To do this rapidly for tens of thousands of molecules requires an effective representation of the binding region of the target protein. This paper presents an algorithm for representing a protein's binding site in a way that is specifically suited to molecular docking applications. Initially the protein's surface is coated with a collection of molecular fragments that could potentially interact with the protein. Each fragment, or probe, serves as a potential alignment point for atoms in a ligand, and is scored to represent that probe's affinity for the protein. Probes are then clustered by accumulating their affinities, where high affinity clusters are identified as being the "stickiest" portions of the protein surface. The stickiest cluster is used as a computational binding "pocket" for docking. This method of site identification was tested on a number of ligand-protein complexes; in each case the pocket constructed by the algorithm coincided with the known ligand binding site. Successful docking experiments demonstrated the effectiveness of the probe representation.}, address = {Arris Pharmaceutical Corporation, South San Francisco, California 94080, USA.}, author = {Ruppert, J. and Welch, W. and Jain, A. N.}, citeulike-article-id = {211806}, citeulike-linkout-0 = {http://www.proteinscience.org/cgi/content/abstract/6/3/524}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/9070435}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=9070435}, issn = {0961-8368}, journal = {Protein Sci}, keywords = {cavities, docking, surflex}, month = {March}, number = {3}, pages = {524--533}, posted-at = {2006-05-17 13:44:19}, priority = {2}, title = {Automatic identification and representation of protein binding sites for molecular docking.}, url = {http://www.proteinscience.org/cgi/content/abstract/6/3/524}, volume = {6}, year = {1997} }

TY - JOUR ID - citeulike:211806 L3 - citeulike-article-id:211806 N2 - Molecular docking is a popular way to screen for novel drug compounds. The method involves aligning small molecules to a protein structure and estimating their binding affinity. To do this rapidly for tens of thousands of molecules requires an effective representation of the binding region of the target protein. This paper presents an algorithm for representing a protein's binding site in a way that is specifically suited to molecular docking applications. Initially the protein's surface is coated with a collection of molecular fragments that could potentially interact with the protein. Each fragment, or probe, serves as a potential alignment point for atoms in a ligand, and is scored to represent that probe's affinity for the protein. Probes are then clustered by accumulating their affinities, where high affinity clusters are identified as being the "stickiest" portions of the protein surface. The stickiest cluster is used as a computational binding "pocket" for docking. This method of site identification was tested on a number of ligand-protein complexes; in each case the pocket constructed by the algorithm coincided with the known ligand binding site. Successful docking experiments demonstrated the effectiveness of the probe representation. IS - 3 JF - Protein Sci SN - 0961-8368 AD - Arris Pharmaceutical Corporation, South San Francisco, California 94080, USA. EP - 533 TI - Automatic identification and representation of protein binding sites for molecular docking. VL - 6 SP - 524 KW - cavities KW - docking KW - surflex AU - Ruppert, J AU - Welch, W AU - Jain, AN PY - 1997/03// UR - http://www.proteinscience.org/cgi/content/abstract/6/3/524 ER -