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A parallel evolutionary algorithm for molecule structure prediction

El ghazali Talbi 

INRIA, Lille 59655, France

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.


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Presentation: Invited at E-MRS Fall Meeting 2007, Symposium G, by El ghazali Talbi
See On-line Journal of E-MRS Fall Meeting 2007

Submitted: 2007-06-01 05:44
Revised:   2009-06-07 00:44