A New Monte Carlo Algorithm for Protein Folding

TL;DR

This paper introduces an improved Monte Carlo algorithm based on the pruned-enriched Rosenbluth method, significantly enhancing efficiency in protein folding simulations and discovering new minimal energy states for model proteins.

Contribution

The paper presents a novel Monte Carlo algorithm that outperforms previous methods in protein folding simulations and provides finite-temperature estimates.

Findings

Faster folding simulations than previous methods

Discovery of new minimal energy states

Accurate partition function estimates at finite temperatures

Abstract

We demonstrate that the recently proposed pruned-enriched Rosenbluth method (P. Grassberger, Phys. Rev. E 56 (1997) 3682) leads to extremely efficient algorithms for the folding of simple model proteins. We test them on several models for lattice heteropolymers, and compare to published Monte Carlo studies. In all cases our algorithms are faster than all previous ones, and in several cases we find new minimal energy states. In addition to ground states, our algorithms give estimates for the partition sum at finite temperatures.