Exploring the Energy Landscapes of Protein Folding Simulations with Bayesian Computation

TL;DR

This paper introduces a parallel nested sampling method to efficiently explore protein energy landscapes, providing insights into folding processes and model characteristics through Bayesian analysis of small protein simulations.

Contribution

It presents a parallel implementation of nested sampling for protein folding, enabling detailed energy landscape analysis and thermodynamic estimations.

Findings

Efficient exploration of protein energy landscapes.

Successful folding simulations of small proteins.

Generation of energy landscape charts for qualitative insights.

Abstract

Nested sampling is a Bayesian sampling technique developed to explore probability distributions lo- calised in an exponentially small area of the parameter space. The algorithm provides both posterior samples and an estimate of the evidence (marginal likelihood) of the model. The nested sampling algo- rithm also provides an efficient way to calculate free energies and the expectation value of thermodynamic observables at any temperature, through a simple post-processing of the output. Previous applications of the algorithm have yielded large efficiency gains over other sampling techniques, including parallel tempering (replica exchange). In this paper we describe a parallel implementation of the nested sampling algorithm and its application to the problem of protein folding in a Go-type force field of empirical potentials that were designed to stabilize secondary structure elements in room-temperature simulations. We demonstrate the method by conducting folding simulations on a number of small proteins which are commonly used for testing protein folding procedures: protein G, the SH3 domain of Src tyrosine kinase and chymotrypsin inhibitor 2. A topological analysis of the posterior samples is performed to produce energy landscape charts, which give a high level description of the potential energy surface for the protein folding simulations. These charts provide qualitative insights into both the folding process and the nature of the model and force field used.