iGNM: a database of protein functional motions based on Gaussian Network Model. Export

@article{citeulike:270179, abstract = {MOTIVATION: The knowledge of protein structure is not sufficient for understanding and controlling its function. Function is a dynamic property. Although protein structural information has been rapidly accumulating in databases, little effort has been invested to date toward systematically characterizing protein dynamics. The recent success of analytical methods based on elastic network models, and in particular the Gaussian Network Model (GNM), permits us to perform a high-throughput analysis of the collective dynamics of proteins. RESULTS: We computed the GNM dynamics for 20 058 structures from the Protein Data Bank, and generated information on the equilibrium dynamics at the level of individual residues. The results are stored on a web-based system called iGNM and configured so as to permit the users to visualize or download the results through a standard web browser using a simple search engine. Static and animated images for describing the conformational mobility of proteins over a broad range of normal modes are accessible, along with an online calculation engine available for newly deposited structures. A case study of the dynamics of 20 non-homologous hydrolases is presented to illustrate the utility of the iGNM database for identifying key residues that control the cooperative motions and revealing the connection between collective dynamics and catalytic activity.}, address = {Department of Computational Biology, School of Medicine, University of Pittsburgh Pittsburgh, PA 15213, USA. lwy1@pitt.edu}, author = {Yang, L. W. and Liu, X. and Jursa, C. J. and Holliman, M. and Rader, A. J. and Karimi, H. A. and Bahar, I.}, citeulike-article-id = {270179}, citeulike-linkout-0 = {http://view.ncbi.nlm.nih.gov/pubmed/15860562}, citeulike-linkout-1 = {http://www.hubmed.org/display.cgi?uids=15860562}, day = {1}, issn = {1367-4803}, journal = {Bioinformatics}, keywords = {gaussian\_network\_model}, month = {July}, number = {13}, pages = {2978--2987}, posted-at = {2005-10-09 22:14:28}, priority = {2}, title = {iGNM: a database of protein functional motions based on Gaussian Network Model.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/15860562}, volume = {21}, year = {2005} }

TY - JOUR ID - citeulike:270179 L3 - citeulike-article-id:270179 N2 - MOTIVATION: The knowledge of protein structure is not sufficient for understanding and controlling its function. Function is a dynamic property. Although protein structural information has been rapidly accumulating in databases, little effort has been invested to date toward systematically characterizing protein dynamics. The recent success of analytical methods based on elastic network models, and in particular the Gaussian Network Model (GNM), permits us to perform a high-throughput analysis of the collective dynamics of proteins. RESULTS: We computed the GNM dynamics for 20 058 structures from the Protein Data Bank, and generated information on the equilibrium dynamics at the level of individual residues. The results are stored on a web-based system called iGNM and configured so as to permit the users to visualize or download the results through a standard web browser using a simple search engine. Static and animated images for describing the conformational mobility of proteins over a broad range of normal modes are accessible, along with an online calculation engine available for newly deposited structures. A case study of the dynamics of 20 non-homologous hydrolases is presented to illustrate the utility of the iGNM database for identifying key residues that control the cooperative motions and revealing the connection between collective dynamics and catalytic activity. IS - 13 JF - Bioinformatics SN - 1367-4803 AD - Department of Computational Biology, School of Medicine, University of Pittsburgh Pittsburgh, PA 15213, USA. lwy1@pitt.edu EP - 2987 TI - iGNM: a database of protein functional motions based on Gaussian Network Model. VL - 21 SP - 2978 KW - gaussian_network_model AU - Yang, LW AU - Liu, X AU - Jursa, CJ AU - Holliman, M AU - Rader, AJ AU - Karimi, HA AU - Bahar, I PY - 2005/07/01/ UR - http://view.ncbi.nlm.nih.gov/pubmed/15860562 ER -