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Biophys. J. BioFAST: First Published February 9, 2007. doi:10.1529/biophysj.106.099440
© 2007 by the Biophysical Society.


A more recent version of this article appeared on May 1, 2007.
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BIOPHYSICAL THEORY AND MODELING

Screened non-bonded interactions in native proteins manipulate optimal paths for robust residue communication

Ali Rana Atilgan 1, Deniz Turgut 1 and Canan Atilgan 1*

1 Sabanci University

* To whom correspondence should be addressed. E-mail: canan{at}sabanciuniv.edu.

Submitted on October 12, 2006
Revised on November 8, 2006
Accepted on 18 January 2007


   Abstract
A protein structure is represented as a network of residues whereby edges are determined by intra-molecular contacts. We introduce inhomogeneity into these networks by assigning each edge a weight that is determined by amino-acid pair potentials. Two methodologies are utilized to calculate the average path lengths (APLs) between pairs: To minimize (i) the maximum weight in the strong APL, and (ii) the total weight in the weak APL. We systematically screen edges that have higher than a cutoff potential and calculate the shortest APLs in these reduced networks, while keeping chain connectivity. Therefore, perturbations introduced at a selected region of the residue network propagate to remote regions only along the non-screened edges that retain their ability to disseminate the perturbation. The shortest APLs computed from the reduced homogeneous networks with only the strongest few non-bonded pairs closely reproduce the strong APLs from the weighted networks. The rate of change in the APL in the reduced residue network as compared to its randomly connected counterpart remains constant until a lower bound. Upon further link removal, this property shows an abrupt increase, towards a random coil behavior. Under different perturbation scenarios, diverse optimal paths emerge for robust residue communication.

Key Words: protein-protein interactions, redundant pathways, residue networks, statistical pair potentials, strong disorder, weighted networks







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Copyright © 2007 by the Biophysical Society.