Reference : A parallel hybrid genetic algorithm for protein structure prediction on the computati...
Scientific journals : Article
Engineering, computing & technology : Computer science
A parallel hybrid genetic algorithm for protein structure prediction on the computational grid
Tantar, Alexandru-Adrian mailto [INRIA Futurs -- LIFL/CNRS UMR 8022]
Melab, N. [Univ Sci & Tech Lille Flandres Artois, CNRS UMR 8576, F-59655 Villeneuve Dascq, France.]
Talbi, E.-G. [> >]
Parent, B. [> >]
Horvath, D. [> >]
Future Generation Computer Systems
Elsevier Science Bv
[en] protein structure prediction ; genetic algorithm ; Hill Climbing ; parallel computing ; grid computing
[en] Solving the structure prediction problem for complex proteins is difficult and computationally expensive. In this paper, we propose a bicriterion parallel hybrid genetic algorithm (GA) in order to efficiently deal with the problem using the computational grid. The use of a near-optimal metaheuristic, such as a GA, allows a significant reduction in the number of explored potential structures. However, the complexity of the problem remains prohibitive as far as large proteins are concerned, making the use of parallel computing on the computational grid essential for its efficient resolution. A conjugated gradient-based Hill Climbing local search is combined with the GA in order to intensify the search in the neighborhood of its provided configurations. In this paper we consider two molecular complexes: the tryptophan-cage protein (Brookhaven Protein Data Bank ID 1L2Y) and alpha-cyclodextrin. The experimentation results obtained on a computational grid show the effectiveness of the approach. (c) 2006 Elsevier B.V. All rights reserved.

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