A Genetic Algorithm with Backtracking for Protein Structure Prediction

A. Katikireddy and C.M. Johnson (USA)

Keywords

Genetic Algorithms, HP Model, Protein Structure Prediction.

Abstract

Protein Structure Prediction (PSP) aims at determining the three-dimensional shape of a protein molecule from its amino acid sequence. This problem is known to be NP Complete and has been declared one of the “Grand Challenge Problems” of biochemistry. A simple and widely studied abstraction used in PSP is the hydrophobic-hydrophilic (HP) model in which the protein conformation is restricted to self-avoiding paths when embedded onto a lattice. In this paper, we propose a simple genetic algorithm for finding the optimal conformation of a protein using the three-dimensional square HP model. A backtracking procedure is used to resolve the positional collisions and illegal conformations that occur during the course of genetic search. Backtracking is shown to be a simple and efficient means of collision repair that requires little overhead. Empirical results show that a genetic algorithm using backtracking can obtain the lowest energy structure of an amino acid sequence in fewer energy evaluations than earlier approaches.

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