Population-based local search for protein folding simulation in the MJ energy model and cubic lattices
| Autor: | Leonidas Kapsokalivas, Kathleen Steinhöfel, Andreas Alexander Albrecht, Xiangchao Gan |
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| Rok vydání: | 2009 |
| Předmět: |
Protein Folding
Mathematical optimization Protein Conformation Molecular Sequence Data Monte Carlo method Population Models Biological Biochemistry Structural Biology Computer Simulation Local search (optimization) Amino Acid Sequence education Mathematics education.field_of_study business.industry Organic Chemistry Proteins Energy landscape Function (mathematics) Tabu search Maxima and minima Computational Mathematics Simulated annealing Thermodynamics business Algorithm |
| Zdroj: | Computational Biology and Chemistry. 33:283-294 |
| ISSN: | 1476-9271 |
| DOI: | 10.1016/j.compbiolchem.2009.06.006 |
| Popis: | We present experimental results on benchmark problems in 3D cubic lattice structures with the Miyazawa-Jernigan energy function for two local search procedures that utilise the pull-move set: (i) population-based local search (PLS) that traverses the energy landscape with greedy steps towards (potential) local minima followed by upward steps up to a certain level of the objective function; (ii) simulated annealing with a logarithmic cooling schedule (LSA). The parameter settings for PLS are derived from short LSA-runs executed in pre-processing and the procedure utilises tabu lists generated for each member of the population. In terms of the total number of energy function evaluations both methods perform equally well, however, PLS has the potential of being parallelised with an expected speed-up in the region of the population size. Furthermore, both methods require a significant smaller number of function evaluations when compared to Monte Carlo simulations with kink-jump moves. |
| Databáze: | OpenAIRE |
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