A PARALLEL HYBRID GA FOR PEPTIDE 3-D STRUCTURE PREDICTION

Abstract

The present work describes recent advances made in the system for 3-D structure prediction of polypeptides being developed in our laboratory. The system was originally conceived as a conformational space search procedure based on a simple genetic algorithm. However, the complexity of the system and the need to produce better fit conformers as artificial evolution proceeds, compelled us to improve the algorithm in two substantial aspects. The first is a parallelization of the original algorithm to enrich the diversity of conformers in the population and the second a hybridization of the original GA in order to process the atoms of the side chains.
The results are exemplified with the prediction of the 3D structure for CRAMBIN.