Prediction of Peptide Conformation by the Multicanonical Algorithm

TL;DR

This paper evaluates the multicanonical algorithm's ability to predict peptide structures, demonstrating its accuracy and thermodynamic calculation advantages over traditional methods like simulated annealing.

Contribution

It introduces the multicanonical algorithm as an effective tool for peptide conformation prediction with exact ensemble control and thermodynamic analysis capabilities.

Findings

Accurate lowest-energy peptide conformation prediction

Exact control over the canonical ensemble

Thermodynamic quantities derived from a single run

Abstract

We test the effectiveness of the multicanonical algorithm for the tertiary structure prediction of peptides and proteins. As a simple example we study Met-enkephalin. The lowest-energy conformation obtained agrees with that determined by other methods such as Monte Carlo simulated annealing. But unlike to simulated annealing the relationship to the canonical ensemble remains exactly controlled. Thermodynamic quantities at various temperature can be calculated from one run.