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Population-based local search for protein folding simulation in the MJ energy model and cubic lattices

机译:基于人口的局部搜索在MJ能量模型和立方晶格中的蛋白质折叠模拟

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摘要

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.
机译:我们使用Miyazawa-Jernigan能量函数针对利用拉动集合的两个局部搜索过程提供了有关3D立方晶格结构中基准问题的实验结果:(ⅰ)贪婪地遍历能量格局的基于人口的局部搜索(PLS)朝(潜在的)局部极小值迈进,然后逐步上升到目标功能的某个水平; (ⅱ)使用对数冷却时间表(LSA)进行模拟退火。 PLS的参数设置来自在预处理中执行的简短LSA运行,并且该过程利用为总体中的每个成员生成的禁忌列表。就能量函数评估的总数而言,两种方法的性能均相当好,但是,PLS具有与人口规模范围内的预期加速并行的潜力。此外,与带有扭结跳跃运动的蒙特卡洛模拟相比,这两种方法都需要大量更少的功能评估。

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