Modeling Molecular Recognition

University Of Pittsburgh, Pittsburgh PA

Investigators

Abstract

The objective of this project, jointly supported by Molecular Biophysics in the Division of Molecular and Cellular Biosciences and the Theoretical and Computational Chemistry Program in the Chemistry Division, is to model the early molecular recognition events responsible for the specificity of protein-protein interactions and predict protein interactions. Based on the observation that diffusion accessible states have a definite attraction for their binding site prior to docking, the specific aims of this project are: (1) To develop and make public a suitable set of proteins to benchmark specific and non-specific interactions, detecting the broad minima of the free energy landscape and most likely set of possible binding sites by using validated docking techniques; and (2) to model the relevant interactions between proteins and develop a semi-rigid full-atom Brownian Dynamics platform to evaluate the time scale that two proteins take to move apart from local minima on the free energy landscape of partially desolvated encounter complexes. Preliminary results indicate a sharp separation in the escape time between the binding site and other incidental local minima. Simulations will incorporate flexibility by periodically adjusting side chains to their local environment using a molecular dynamics generated ensemble of pre-calculated conformations. This method will be implemented as a web-server to automatically evaluate the likelihood of any two proteins to interact based on estimates of the escape time from relevant free energy minima. The main idea of this project is to circumvent the bound complex and use the dwelling time, or stickiness, as an estimate for whether or not two proteins physically interact. In vivo, proteins may encounter many potential binding partners. However, a striking set of specific and non-specific interactions encoded in the protein structure tolerates binding only to a unique substrate. Non-specific binding is prevented by keeping random encounters between proteins to last no more than a few nanoseconds, while molecular recognition is triggered when the dwelling time associated with the broad free energy minimum that characterizes the binding site is long enough for induced fit interactions to latch the complex. Despite these insights, to date there is no in silico approach to predict the high affinity complexes. Any progress in this fundamental problem is bound to bring about a better understanding of how proteins work cooperatively in a cell, promoting breakthroughs in every aspect of the biological sciences. The structural genomics revolution along with technologies that predict protein interactions will make it possible to simulate biological processes in silico.