Testing a New Monte Carlo Strategy for Folding Model Proteins

TL;DR

This paper introduces an efficient Monte Carlo algorithm based on the PERM method for folding simple model proteins, outperforming previous methods in speed and accuracy, and providing detailed insights into folding behavior.

Contribution

The paper adapts the PERM algorithm for protein folding, demonstrating improved efficiency and the ability to find new minimal energy states and analyze thermal spectra.

Findings

Faster folding simulations compared to previous methods

Discovery of new minimal energy states for certain sequences

Enhanced analysis of thermal spectra and folding behavior

Abstract

We demonstrate that the recently proposed pruned-enriched Rosenbluth method PERM (P.~Grassberger, Phys.~Rev.~{\bf E 56} (1997) 3682) leads to very efficient algorithms for the folding of simple model proteins. We test it on several models for lattice heteropolymers, and compare to published Monte Carlo studies of the properties of particular sequences. In all cases our method is faster than the previous ones, and in several cases we find new minimal energy states. In addition to producing more reliable candidates for ground states, our method gives detailed information about the thermal spectrum and, thus, allows to analyze static aspects of the folding behavior of arbitrary sequences.