Nanotech 2001 Vol. 2
Nanotech 2001 Vol. 2
Technical Proceedings of the 2001 International Conference on Computational Nanoscience and Nanotechnology

Bioinformatics/Mathematical Biology Chapter 2

Detecting Secondary Peptide Structures by Scaling a Genetic Algorithm

Authors: S.R. Michaud, J.B. Zydallis, G.B. Lamont and R. Pachter

Affilation: Air Force Institute of Technology, United States

Pages: 29 - 32

Keywords: alanine peptide, energy minimization, protein structure prediction problem, genetic algorithm, fast messy genetic algorithm

The ability to accurately predict a polypeptide's molecular structure given its amino acid sequence is important to numerous scientific, medical, and engineering applications. Studies have been conducted in the application of Genetic Algorithms (GAs) to this problem with initial results shown to be promising. In this paper we use the fast messy Genetic Algorithm (fmGA) to attempt to find the minimization of an empirical CHARMM energy model and generation of the associated conformation. Previous work has shown that the fmGA provided favorable results, at least when applied to the pentapeptide [Met]-Enkephelin. We extend these results to a much larger Polyalanine peptide by utilizing secondary structure information. This information is utilized to conduct localized searches on the energy landscape. Results indicate that on average this localized search always produces a better final solution.

Detecting Secondary Peptide Structures by Scaling a Genetic Algorithm

ISBN: 0-9708275-3-9
Pages: 218