Modelling Allostery using a Computational Analysis of Side-Chain Interactions

Abstract

Allostery refers to the regulation of protein activity arising from an effector molecule, such as a ligand, binding to a protein. The exact mechanisms that take place in allosteric regulation are still a source of debate within the protein research community. To gain a better understanding of allosteric mechanisms, we devised a computational model of allostery that focused on simple protein structures that have a fixed backbone but dynamic side chains.

Our model relied on a statistical analysis of side-chain couplings to determine the effect of side-chain fluctuations. To obtain the side-chain dataset required for the statistical analysis, we used an energy minimization procedure contained within the UCSF Chimera molecular modelling software to evaluate concerted side-chain movements. We also derived residue networks and designed graph algorithms that mimicked allosteric signal propagations. These techniques enabled us to identify highly fluctuating sites within a protein structure and to uncover potential functionally important residues.

We evaluated our methods by applying them to the PDZ3 domain of the PSD-95 protein. This protein structure was chosen due to its relatively small size and rigid backbone. We identified residues that experienced high levels of side-chain fluctuations, and our results agreed with experimentally determined functionally important residues. Comparing the results for the apo and holo forms of the protein also revealed structural elements, such as side-chain fluctuations within alpha helices, that are important for allosteric signal transmissions.