Using Topological Data Analysis and RRT to Investigate Protein Conformational Spaces

Abstract

Investigating the conformational space of proteins is essential in order to associate their structures with their fundamental functions. Nonetheless, it is a challenging task, both experimentally and computationally. Because of the transient nature of these conformational changes and the fact that they are impermanent, empirical methods have fallen short to capture them. In silico methods, on the other hand, have shown great promise in exploring these conformational pathways. In this article, we provide an extensive evaluation of our previously introduced, robotics inspired conformational search algorithm (RRT* with Monte Carlo). We then identify what intermediate conformations appear the most in our generated conformational pathways using TDA Mapper, a topological data analysis algorithm, and examine how close these intermediate conformations are to existing experimental data.