Testing a new Monte Carlo Algorithm for Protein Folding

TL;DR

This paper introduces an efficient Monte Carlo algorithm, PERM, for protein folding that outperforms previous methods, finds new minimal energy states, and provides detailed insights into folding behavior.

Contribution

The paper presents PERM, a novel Monte Carlo algorithm that significantly improves the efficiency and accuracy of protein folding simulations on lattice models.

Findings

PERM is faster than previous algorithms for protein folding.

The method discovers new minimal energy states.

Provides detailed analysis of folding thermodynamics.

Abstract

We demonstrate that the recently proposed pruned-enriched Rosenbluth method PERM (P. Grassberger, Phys. Rev. E, in press (1997)) leads to extremely 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.