
Referring to the optimization algorithm previously developed for atomic clusters, the present author develops an efficient method for geometry optimization of a coarse-grained protein model expressed with two kinds of beads (hydrophilic and hydrophobic ones). In the method, two types of geometrical perturbations, center-directed bead move and one bead rotation, are used to explore new configurations and local optimizations are performed after the perturbations. The center-directed bead move is used for hydrophobic beads and the one bead rotation is performed for both hydrophobic and hydrophilic beads. The optimization method was applied to protein models consisting of 13, 20, 21, and 34 beads. The present method produced the global minima of the 13-, 21-, and 34-bead models reported in the literature and updated the lowest energies of the protein models with 20 beads. These results indicate that the present method is efficient for searching for optimal structures of proteins.
Models, Molecular, Protein Conformation, global optimization, Proteins, 431, potential energy, Workflow, protein model, Amino Acid Sequence, Hydrophobic and Hydrophilic Interactions, Monte Carlo Method, Algorithms
Models, Molecular, Protein Conformation, global optimization, Proteins, 431, potential energy, Workflow, protein model, Amino Acid Sequence, Hydrophobic and Hydrophilic Interactions, Monte Carlo Method, Algorithms
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