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Hamiltonian Reweighing To Refine Protein Backbone Dihedral Angle Parameters in the GROMOS Force Field.
Journal of Chemical Information and Modeling ( IF 5.6 ) Pub Date : 2020-01-09 , DOI: 10.1021/acs.jcim.9b01034
Matthias Diem 1 , Chris Oostenbrink 1
Affiliation  

Molecular dynamics simulations of proteins depend critically on the underlying force field, which may be parameterized against experimental data or high-quality quantum calculations. Here, we develop search algorithms based on Monte Carlo and steepest descent calculations to optimize the backbone dihedral angle parameters from a single reference simulation. We apply these tools to improve the agreement between simulations of single, capped amino acids and experimentally determined J values and secondary structure propensities of these molecules. The parameters are further refined based on simulations of a set of seven proteins and finally validated in simulations on a large set of 52 protein structures. Improvements in the dihedral angle distributions are observed, and structural propensities of the proteins are reproduced very well. Overall, the GROMOS 54A8_bb parameter set forms an improvement to previous parameter sets, both for small molecules and for protein simulations.

中文翻译:

哈密​​顿量重,以完善GROMOS力场中的蛋白质骨架二面角参数。

蛋白质的分子动力学模拟主要取决于潜在的力场,该力场可以根据实验数据或高质量的量子计算进行参数化。在这里,我们开发基于Monte Carlo和最速下降计算的搜索算法,以从单个参考仿真中优化主干二面角参数。我们应用这些工具来改善单个,带帽氨基酸的模拟与实验确定的这些分子的J值和二级结构倾向之间的一致性。根据一组七个蛋白质的模拟对参数进行进一步完善,最后在一组52种蛋白质结构的模拟中进行验证。观察到二面角分布的改善,并且很好地再现了蛋白质的结构倾向。全面的,
更新日期:2020-01-10
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