OPEN BMC bioinformatics | 26 Oct 2012
A Panjkovich and X Daura
BACKGROUND: Allostery is one of the most powerful and common ways of regulation of protein activity. However,for most allosteric proteins identified to date the mechanistic details of allosteric modulation are notyet well understood. Uncovering common mechanistic patterns underlying allostery would allow notonly a better academic understanding of the phenomena, but it would also streamline the design ofnovel therapeutic solutions. This relatively unexplored therapeutic potential and the putativeadvantages of allosteric drugs over classical active-site inhibitors fuel the attention allosteric-drugresearch is receiving at present. A first step to harness the regulatory potential and versatility ofallosteric sites, in the context of drug-discovery and design, would be to detect or predict theirpresence and location. In this article, we describe a simple computational approach, based on theeffect allosteric ligands exert on protein flexibility upon binding, to predict the existence and positionof allosteric sites on a given protein structure. RESULTS: By querying the literature and a recently available database of allosteric sites, we gathered 213allosteric proteins with structural information that we further filtered into a non-redundant set of 91proteins. We performed normal-mode analysis and observed significant changes in protein flexibilityupon allosteric-ligand binding in 70% of the cases. These results agree with the current view thatallosteric mechanisms are in many cases governed by changes in protein dynamics caused by ligandbinding. Furthermore, we implemented an approach that achieves 65% positive predictive value inidentifying allosteric sites within the set of predicted cavities of a protein (stricter parameters set,0.22 sensitivity), by combining the current analysis on dynamics with previous results on structuralconservation of allosteric sites. We also analyzed four biological examples in detail, revealing thatthis simple coarse-grained methodology is able to capture the effects triggered by allosteric ligandsalready described in the literature. CONCLUSIONS: We introduce a simple computational approach to predict the presence and position of allosteric sitesin a protein based on the analysis of changes in protein normal modes upon the binding of acoarse-grained ligand at predicted cavities. Its performance has been demonstrated using a newlycurated non-redundant set of 91 proteins with reported allosteric properties. The software developedin this work is available upon request from the authors.
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