Differential Evolution for Protein Structure Prediction Using the HP Model

被引:0
|
作者
Santos, J. [1 ]
Dieguez, M. [1 ]
机构
[1] Univ A Coruna, Dept Comp Sci, La Coruna, Spain
来源
FOUNDATIONS ON NATURAL AND ARTIFICIAL COMPUTATION: 4TH INTERNATIONAL WORK-CONFERENCE ON THE INTERPLAY BETWEEN NATURAL AND ARTIFICIAL COMPUTATION, IWINAC 2011, PART I | 2011年 / 6686卷
关键词
GENETIC ALGORITHM; OPTIMIZATION; PRINCIPLES; 2D;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We used Differential Evolution (DE) for the problem of protein structure prediction. We employed the HP model to represent the folding conformations of a protein in a lattice. In this model the nature of amino acids is reduced considering only two types: hydrophobic residues (H) and polar residues (P), which is based on the recognition that hydrophobic interactions are a dominant force in protein folding. Given a primary sequence of amino acids, the problem is to search for the folding structure in the lattice that minimizes an energy potential. This energy reflects the fact that the hydrophobic amino acids have a propensity to form a hydrophobic core. The complexity of the problem has been shown to be NP-hard, with minimal progress achieved in this category of ab initio folding. We combined DE with methods to transform illegal protein conformations to feasible ones, showing the capabilities of the hybridized DE with respect to previous works.
引用
收藏
页码:323 / 333
页数:11
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