Inference of Protein Structures by Immune Algorithm

Abstract

Genetic algorithm(GA) has been used widely to inference the globally stable conformation(s) of molecules. GA is essentially a parallel algorithm and has the feature to search not only for the globally stable conformation but also for locally stable states which are similar to the globally stable conformation. In the case of condensed phase such as solutions or solids, molecules are under the interactions with other molecules. As intermolecular interactions are weak compared to the covalent forces of molecules, locally stable conformations in isolated state may still have similar structures in condensed media. It is known that flexible molecules like enkephalin analogs take two or more conformations even in the crystal states. This facts means some of locally stable conformations of isolated flexible molecules may be identical to the conformations in crystal states. To get the variety of stable conformations, we developed the GA to comprise immune system and built immune algorithm(IA). IA suppresses the conformations in high concentration to get the variety of conformations. GA and IA were applied to enkephalin analogs and collagen like peptides. We found (1) IA searched more variety of conformations than GA did, (2) enkephalins gave more conformational variety than collagen peptides.