中国物理B ›› 2009, Vol. 18 ›› Issue (6): 2615-2621.doi: 10.1088/1674-1056/18/6/082

• 8000 CROSSDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY • 上一篇    

Structure optimization by heuristic algorithm in a coarse-grained off-lattice model

刘景发   

  1. Computer and Software Institute, Nanjing University of Information Science and Technology, Nanjing 210044, China
  • 收稿日期:2006-12-14 修回日期:2008-12-20 出版日期:2009-06-20 发布日期:2009-06-20
  • 基金资助:
    Project supported by the Foundation of Nanjing University of Information Science and Technology and the Excellent Youth Foundation of Education Office of Hunan Province, China (Grant No 07B009).

Structure optimization by heuristic algorithm in a coarse-grained off-lattice model

Liu Jing-Fa(刘景发)†   

  1. Computer and Software Institute, Nanjing University of Information Science and Technology, Nanjing 210044, China
  • Received:2006-12-14 Revised:2008-12-20 Online:2009-06-20 Published:2009-06-20
  • Supported by:
    Project supported by the Foundation of Nanjing University of Information Science and Technology and the Excellent Youth Foundation of Education Office of Hunan Province, China (Grant No 07B009).

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摘要： A heuristic algorithm is presented for a three-dimensional off-lattice AB model consisting of hydrophobic (A) and hydrophilic (B) residues in Fibonacci sequences. By incorporating extra energy contributions into the original potential function, we convert the constrained optimization problem of AB model into an unconstrained optimization problem which can be solved by the gradient method. After the gradient minimization leads to the basins of the local energy minima, the heuristic off-trap strategy and subsequent neighborhood search mechanism are then proposed to get out of local minima and search for the lower-energy configurations. Furthermore, in order to improve the efficiency of the proposed algorithm, we apply the improved version called the new PERM with importance sampling (nPERMis) of the chain-growth algorithm, pruned-enriched-Rosenbluth method (PERM), to face-centered-cubic (FCC)-lattice to produce the initial configurations. The numerical results show that the proposed methods are very promising for finding the ground states of proteins. In several cases, we found the ground state energies are lower than the best values reported in the present literature.

Abstract: A heuristic algorithm is presented for a three-dimensional off-lattice AB model consisting of hydrophobic (A) and hydrophilic (B) residues in Fibonacci sequences. By incorporating extra energy contributions into the original potential function, we convert the constrained optimization problem of AB model into an unconstrained optimization problem which can be solved by the gradient method. After the gradient minimization leads to the basins of the local energy minima, the heuristic off-trap strategy and subsequent neighborhood search mechanism are then proposed to get out of local minima and search for the lower-energy configurations. Furthermore, in order to improve the efficiency of the proposed algorithm, we apply the improved version called the new PERM with importance sampling (nPERMis) of the chain-growth algorithm, pruned-enriched-Rosenbluth method (PERM), to face-centered-cubic (FCC)-lattice to produce the initial configurations. The numerical results show that the proposed methods are very promising for finding the ground states of proteins. In several cases, we found the ground state energies are lower than the best values reported in the present literature.

Key words: protein folding, off-lattice model, heuristics, FCC-lattice

中图分类号:  (Proteins)

  • 87.14.E-
87.15.A- (Theory, modeling, and computer simulation) 87.15.B- (Structure of biomolecules) 87.15.Cc (Folding: thermodynamics, statistical mechanics, models, and pathways)