An immune algorithm for protein structure prediction on lattice models

被引:134
作者
Cutello, Vincenzo [1 ]
Nicosia, Giuseppe
Pavone, Mario
Timmis, Jonathan
机构
[1] Univ Catania, Dept Math & Comp Sci, I-95125 Catania, Italy
[2] Univ York, Dept Comp Sci, York YO10 5DD, N Yorkshire, England
[3] Univ York, Dept Elect, York YO10 5DD, N Yorkshire, England
关键词
aging operator; clonal selection algorithms; functional model proteins; hypermacromutation operator; hypermutation operator; immune algorithms (IAs); protein structure prediction problem; two-dimensional HP model; three-dimensional HP model;
D O I
10.1109/TEVC.2006.880328
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We present an immune algorithm (IA) inspired by the clonal selection principle, which has been designed for the protein structure prediction problem (PSP). The proposed IA employs two special mutation operators, hypermutation and hypermacromutation to allow effective searching, and an aging mechanism which is a new immune inspired operator that is devised to enforce diversity in the population during evolution. When cast as an optimization problem, the PSP can be seen as discovering a protein conformation with minimal energy. The proposed IA was tested on well-known PSP lattice models, the HP model in two-dimensional and three-dimensional square lattices', and the functional model protein, which is a more realistic biological model. Our experimental results demonstrate that the proposed IA is very competitive with the existing state-of-art algorithms for the PSP on lattice models.
引用
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页码:101 / 117
页数:17
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