Modelling and Predicting Allostery with Propagation of Rigidity Across Protein Structures

Abstract

To deeply understand how proteins function, one must examine their flexibility and dynamics. One critical way proteins regulate their dynamics and ultimately function is through a universal phenomenon known as “allostery” which has been coined as “second secret of life”. Allostery involves functional change at one site induced by a perturbation event to a distant allosteric site which is topographically distinct from an active site. In spite of its importance, the molecular mechanisms that give rise to allostery are still poorly understood and long-preached potential of allostery remains elusive. In order for the full benefits of allostery to be taken advantage of, both for basic understanding of proteins and to develop new classes of drugs, we must develop allostery models that allow us to describe how signals propagate across long distances in protein structures. We have recently developed rigidity-transmission allostery (RTA) algorithm, an extremely fast computational method based on mathematical algorithms in rigidity theory. RTA algorithm provides a mechanical interpretation of allosteric signaling and is designed to predict if perturbation of rigidity (mimicking ligand binding) at one site of the protein can transmit and propagate across a protein structure and in turn cause a transmission and change in conformational degrees of freedom at a second distant site, resulting in allosteric transmission. We will illustrate our method, identification of novel allosteric sites and a detailed mapping of allosteric pathways, which are in agreement with NMR data studies on various class of proteins: GPCRs [Nature Communication 2018], enzyme fluorocatate dehalogenase [Science 2017, J. Am. Chem. Soc. (2019)], and others. RTA method is computational very efficient and can scan many unknown sites for allosteric communication, identifying potential new allosteric sites and it can be used to engineer allosteric modification of protein function.