Authors: R.O. Day, J.B. Zydallis, G.B. Lamont and R. Pachter
Affilation: Air Force Institute of Technology, United States
Pages: 32 - 35
Keywords: energy minimization, protein structure prediction problem, genetic algorithm, fast messy genetic algorithm
The Protein Structure Prediction (PSP) problem is a Grand Challenge problem among biochemists, computer scientists and engineers alike. Solving this problem involves correctly predicting the geometrical conformation of a fully folded protein. This paper focuses on CHARMm energy minimization and the use of a genetic algorithm, the fast messy genetic algorithm (fmGA), to obtain solutions to this optimization problem. The fmGA is a novel algorithm that explicitly manipulates building blocks (BBs) in order to obtain "good" solutions to an optimization problem. In order to obtain these "good" solutions, fully speci¯ed competitive templates are used within the fmGA to evaluate the BBs found. This paper presents "good" results of an analysis of various competitive template schemes for the application of the fmGA to the PSP of [Met]-Enkephelin and the much larger Polyalanine peptide.
Nanotech Conference Proceedings are now published in the TechConnect Briefs