Lipschitzian pattern search and immunological algorithm with quasi-newton method for the protein folding problem: an innovative multistage approach

Authors:
A. M. Anile;V. Cutello;G. Narzisi;G. Nicosia;S. Spinella
Affiliations:
Department of Mathematics and Computer Science, University of Catania, Catania, Italy;Department of Mathematics and Computer Science, University of Catania, Catania, Italy;Department of Mathematics and Computer Science, University of Catania, Catania, Italy;Department of Mathematics and Computer Science, University of Catania, Catania, Italy;University of Calabria, Arcavata di Rende (CS), Italy
Venue:
WIRN'05 Proceedings of the 16th Italian conference on Neural Nets
Year:
2005

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Abstract

In this work we show an innovative approach to the protein folding problem based on an hybrid Immune Algorithm (IA) and a quasi-Newton method starting from a population of promising protein conformations created by the global optimizer DIRECT. The new method has been tested on Met-Enkephelin peptide, which is a paradigmatic example of multiple-minima problem, 1POLY, 1ROP and the three helix protein 1BDC. The experimental results show as the multistage approach is a competitive and effective search method in the conformational search space of real proteins, in terms of quality solution and computational cost comparing the results of the current state-of-art algorithms.