The flawless functioning of the protein is essentially related to its three-dimensional structure. Therefore,predicting protein structure from its amino acid sequence is a fundamental problem that draws researchers' attentionin many areas. The protein structure prediction problem (PSP) can be formulated as a combinatorial optimization problem based on simplified lattice models such as the hydrophobic-polar model. In this paper, we propose a new hybridalgorithm that combines three different known heuristic algorithms: the genetic algorithm, the tabu search strategy,and the local search algorithm to solve the PSP problem. Regarding the evaluation of the proposed approach, wepresent an experimental study, where we consider the quality of the product solution as the main assessment criterion.Furthermore, we compared the proposed algorithm with state-of-the-art algorithms using a selection of well-studiedbenchmark instances.
Protein structure prediction, 2D triangular lattice, HP model, genetic algorithm, local search algorithm, tabu search strategy, minimal energy conformation
SADEK, BOUROUBI and BOUMEDINE, NABIL
"A new hybrid genetic algorithm for protein structure prediction on the 2Dtriangular lattice,"
Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 29:
2, Article 2.
Available at: https://journals.tubitak.gov.tr/elektrik/vol29/iss2/2