Modelling Proteins Conformation in Solution. Part I: A Parallel GA Engine for Protein Conformational Space Mapping

Carlos A. Del Carpio [1] (
Valentin Gogonea [2] (

[1] Lab. for Informatics & AI in Molecular and Biological Sciences
Dept. of Ecological Engineering,
Toyohashi University of Technology
Tempaku, Toyohashi 441. Japan
[2] Computer Chemistry Center, Institute for Organic Chemistry
Erlangen-Nurnberg University, Nagelsbachstr.
25, D-91052 Erlangen, Germany


This article is the first of a series of papers describing the development of a n automatic system for prediction of the three dimensional conformation of prote ins in solution. In this first part we discuss the implementation of the protein conformational space mapping engine. This is a procedure based on a robust parallel genetic algorithm which runs on a network of transputers. We describe aspects of the algorithm related to the major factors that influence the protein folding process and describe their implementation within the scheme of the evolutionary algorithm. Among them, we make a throughout review of the co-operativity of emergent partial secondary structures as the evolutionary process proceeds and its effects on the stability of new generated conformers as well as a better performance of the GA. We then undertake the hydrogen bond and synthesize the demographic trends in known proteins suggested by Stickle et. al., and also implement them as an index of gooness assessment of the generations of protein conformers. Finally, we make an intensive analysis of the packing of the amino acid side chains and show how a hybrid algorithm can utter a relaxation of the perturbations brought about by the operations of the GA, and the genuine improvement of the overall process. In the second paper of this series we propose guidelines under which we implement the solvent effect which in concourse with the above mentioned factors results in a system for protein 3D structure prediction in solution.