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Biophys. J. BioFAST: First Published August 4, 2006. doi:10.1529/biophysj.106.085894
© 2006 by the Biophysical Society.

A more recent version of this article appeared on October 15, 2006.
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BIOPHYSICAL THEORY AND MODELING

Optimization and evaluation of a coarse-grained model of protein motion using X-ray crystal data

Dmitry A Kondrashov 1, Qiang Cui 1 and George N. Phillips, Jr. 2*

1 University of Wisconsin - Madison
2 University of Wisconsin-Madison

* To whom correspondence should be addressed. E-mail: phillips{at}biochem.wisc.edu.

Submitted on March 27, 2006
Revised on May 21, 2006
Accepted on 20 June 2006


  Abstract
Simple coarse-grained models, such as the Gaussian Network Model, have been shown to capture some of the features of equilibrium protein dynamics. We extend this model by using atomic contacts to define residue interactions and introducing more than one interaction parameter between residues. We use B-factors from 98 ultra-high resolution (≤ 1.0 Å) X-ray crystal structures to optimize the interaction parameters. The average correlation between GNM fluctuation predictions and the B-factors is 0.64 for the data set, consistent with a previous large-scale study. By separating residue interactions into covalent and noncovalent, we achieve an average correlation of 0.74, and addition of ligands and cofactors further improves the correlation to 0.75. However, further separating the noncovalent interactions into nonpolar, polar, and mixed yields no significant improvement. The addition of simple chemical information results in better prediction quality without increasing the size of the coarse-grained model.

Key Words: coarse-grained models, debye-waller factors, elastic network model, normal mode analysis, protein dynamics




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Copyright © 2006 by the Biophysical Society.