Allostery pp 385-398

Part of the Methods in Molecular Biology book series (MIMB, volume 796)

A Critical Evaluation of Correlated Mutation Algorithms and Coevolution Within Allosteric Mechanisms

  • Dennis R. Livesay
  • Kyle E. Kreth
  • Anthony A. Fodor
Protocol

Abstract

The notion of using the evolutionary history encoded within multiple sequence alignments to predict allosteric mechanisms is appealing. In this approach, correlated mutations are expected to reflect coordinated changes that maintain intramolecular coupling between residue pairs. Despite much early fanfare, the general suitability of correlated mutations to predict allosteric couplings has not yet been established. Lack of progress along these lines has been hindered by several algorithmic limitations including phylogenetic artifacts within alignments masking true covariance and the computational intractability of consideration of more than two correlated residues at a time. Recent progress in algorithm development, however, has been substantial with a new generation of correlated mutation algorithms that have made fundamental progress toward solving these difficult problems. Despite these encouraging results, there remains little evidence to suggest that the evolutionary constraints acting on allosteric couplings are sufficient to be recovered from multiple sequence alignments. In this review, we argue that due to the exquisite sensitivity of protein dynamics, and hence that of allosteric mechanisms, the latter vary widely within protein families. If it turns out to be generally true that even very similar homologs display a wide divergence of allosteric mechanisms, then even a perfect correlated mutation algorithm could not be reliably used as a general mechanism for discovery of allosteric pathways.

Key words

Allostery Thermodynamic coupling Correlated mutation Covariance Coevolution Mutual information 

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Dennis R. Livesay
    • 1
  • Kyle E. Kreth
    • 1
  • Anthony A. Fodor
    • 1
  1. 1.Department of Bioinformatics and GenomicsUniversity of North Carolina at CharlotteCharlotteUSA

Personalised recommendations