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Towards accurate residue–residue hydrophobic contact prediction for α helical proteins via integer linear optimization

Towards accurate residue–residue hydrophobic contact prediction for α helical proteins via... A new optimization‐based method is presented to predict the hydrophobic residue contacts in α‐helical proteins. The proposed approach uses a high resolution distance dependent force field to calculate the interaction energy between different residues of a protein. The formulation predicts the hydrophobic contacts by minimizing the sum of these contact energies. These residue contacts are highly useful in narrowing down the conformational space searched by protein structure prediction algorithms. The proposed algorithm also offers the algorithmic advantage of producing a rank ordered list of the best contact sets. This model was tested on four independent α‐helical protein test sets and was found to perform very well. The average accuracy of the predictions (separated by at least six residues) obtained using the presented method was ∼66% for single domain proteins. The average true positive and false positive distances were also calculated for each protein test set and they are 8.87 and 14.67 Å, respectively. Proteins 2009. © 2008 Wiley‐Liss, Inc. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Proteins: Structure Function and Bioinformatics Wiley

Towards accurate residue–residue hydrophobic contact prediction for α helical proteins via integer linear optimization

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References (50)

Publisher
Wiley
Copyright
Copyright © 2009 Wiley Subscription Services
ISSN
0887-3585
eISSN
1097-0134
DOI
10.1002/prot.22202
pmid
18767158
Publisher site
See Article on Publisher Site

Abstract

A new optimization‐based method is presented to predict the hydrophobic residue contacts in α‐helical proteins. The proposed approach uses a high resolution distance dependent force field to calculate the interaction energy between different residues of a protein. The formulation predicts the hydrophobic contacts by minimizing the sum of these contact energies. These residue contacts are highly useful in narrowing down the conformational space searched by protein structure prediction algorithms. The proposed algorithm also offers the algorithmic advantage of producing a rank ordered list of the best contact sets. This model was tested on four independent α‐helical protein test sets and was found to perform very well. The average accuracy of the predictions (separated by at least six residues) obtained using the presented method was ∼66% for single domain proteins. The average true positive and false positive distances were also calculated for each protein test set and they are 8.87 and 14.67 Å, respectively. Proteins 2009. © 2008 Wiley‐Liss, Inc.

Journal

Proteins: Structure Function and BioinformaticsWiley

Published: Jan 1, 2009

Keywords: ; ; ; ; ;

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