Author:
Benítez César Manuel Vargas,Lopes Heitor Silvério
Abstract
Abstract
This work presents a master-slave parallel genetic algorithm for the protein folding problem, using the 3D-HP side-chain model (3D-HP-SC). This model is sparsely studied in the literature, although more expressive than other lattice models. The fitness function proposed includes information not only about the free-energy of the conformation, but also compactness of the side-chains. Since there is no benchmark available to date for this model, a set of 15 sequences was used, based on a simpler model. Results show that the parallel GA achieved a good level of efficiency and obtained biologically coherent results, suggesting the adequacy of the methodology. Future work will include new biologically-inspired genetic operators and more experiments to create new benchmarks.
Publisher
Springer Science and Business Media LLC
Reference28 articles.
1. Anfinsen CB Principles that govern the folding of protein chains. Science (181)
2. Armstrong NB Jr, Lopes HS, Lima CRE (2007) Reconfigurable computing for accelerating protein folding simulations. Lect Notes Comput Sci 4419:314–325
3. Atkins J, Hart WE (1999) On the intractability of protein folding with a finite alphabet. Algorithmica 25(2–3):279–294
4. Benítez CMV, Lopes HS (2009) Algoritmo genético aplicado à predição da estrutura de proteínas utilizando o modelo 3D-HP side chain. In: Anais do VII encontro nacional de inteligência artificial (ENIA)
5. Benítez CMV, Lopes HS (2009) A parallel genetic algorithm for protein folding prediction using the 3DHP side-chain model. In: Proceedings of IEEE congress on evolutionary computation. IEEE Computer Society, Piscataway, pp 1297–1304
Cited by
9 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献