
Extended particle swarm optimisation method for folding protein on triangular lattice
Author(s) -
Guo Yuzhen,
Wu Zikai,
Wang Ying,
Wang Yong
Publication year - 2016
Publication title -
iet systems biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.367
H-Index - 50
eISSN - 1751-8857
pISSN - 1751-8849
DOI - 10.1049/iet-syb.2015.0059
Subject(s) - particle swarm optimization , lattice (music) , folding (dsp implementation) , protein folding , physics , computer science , statistical physics , algorithm , engineering , structural engineering , nuclear magnetic resonance , acoustics
In this study, the authors studied the protein structure prediction problem by the two‐dimensional hydrophobic–polar model on triangular lattice. Particularly the non‐compact conformation was modelled to fold the amino acid sequence into a relatively larger triangular lattice, which is more biologically realistic and significant than the compact conformation. Then protein structure prediction problem was abstracted to match amino acids to lattice points. Mathematically, the problem was formulated as an integer programming and they transformed the biological problem into an optimisation problem. To solve this problem, classical particle swarm optimisation algorithm was extended by the single point adjustment strategy. Compared with square lattice, conformations on triangular lattice are more flexible in several benchmark examples. They further compared the authors’ algorithm with hybrid of hill climbing and genetic algorithm. The results showed that their method was more effective in finding solution with lower energy and less running time.