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Bioinformatics Advance Access published online on April 28, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti469
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org
Received February 9, 2005
Revised April 7, 2005
Accepted April 25, 2005

Article

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

Lee-Wei Yang 1*, Xiong Liu 2, Christopher J. Jursa 2, Mark Holliman 1, A. J. Rader 1, Hassan A. Karimi 2, and Ivet Bahar 1

1 Department of Computational Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213
2 Department of Information Science and Telecommunications, University of Pittsburgh, Pittsburgh, PA 15213

* To whom correspondence should be addressed.
Lee-Wei Yang, E-mail: lwy1{at}pitt.edu


  Abstract

Motivation: Knowledge of structure is not sufficient for understanding and controlling protein function. Function is a dynamic property. While protein structural information has been rapidly accumulating in databases, little effort has been invested to date towards systematically characterizing protein dynamics. 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 proteins' collective dynamics.

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 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 twenty 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.

Availability: http://ignm.ccbb.pitt.edu/.


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