Using motion planning to study protein folding pathways

Abstract

We present a framework for studying protein folding pathways and potential landscapes which is based on techniques recently developed in the robotics motion planning community. In particular, our work uses Probabilistic Roadmap (PRM) motion planning techniques which have proven to be very successful for problems involving high-dimensional configuration spaces. Our results applying PRM techniques to several small proteins (60 residues) are very encouraging. The framework enables one to easily and efficiently compute folding pathways from any denatured starting state to the native fold. This aspect makes our approach ideal for studying global properties of the protein's potential landscape. For example, our results show that folding pathways from different starting denatured states sometimes share some common `gullies', mainly when they are close to the native fold. Such global issues are difficult to simulate and study with other methods.