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用于蛋白质结构与动力学模拟的UNRES力场的最大似然校准

Maximum Likelihood Calibration of the UNRES Force Field for Simulation of Protein Structure and Dynamics.

作者信息

Krupa Paweł, Hałabis Anna, Żmudzińska Wioletta, Ołdziej Stanisław, Scheraga Harold A, Liwo Adam

机构信息

Faculty of Chemistry, University of Gdańsk , ul. Wita Stwosza 63, 80-308 Gdańsk, Poland.

Baker Laboratory of Chemistry and Chemical Biology, Cornell University , Ithaca, New York 14853-1301, United States.

出版信息

J Chem Inf Model. 2017 Sep 25;57(9):2364-2377. doi: 10.1021/acs.jcim.7b00254. Epub 2017 Sep 5.

Abstract

By using the maximum likelihood method for force-field calibration recently developed in our laboratory, which is aimed at achieving the agreement between the simulated conformational ensembles of selected training proteins and the corresponding ensembles determined experimentally at various temperatures, the physics-based coarse-grained UNRES force field for simulations of protein structure and dynamics was optimized with seven small training proteins exhibiting a variety of secondary and tertiary structures. Four runs of optimization, in which the number of optimized force-field parameters was gradually increased, were carried out, and the resulting force fields were subsequently tested with a set of 22 α-, 12 β-, and 12 α + β-proteins not used in optimization. The variant in which energy-term weights, local, and correlation potentials, side-chain radii, and anisotropies were optimized turned out to be the most transferable and outperformed all previous versions of UNRES on the test set.

摘要

通过使用我们实验室最近开发的用于力场校准的最大似然法,该方法旨在使选定训练蛋白的模拟构象集合与在不同温度下通过实验确定的相应集合达成一致,我们用七种具有各种二级和三级结构的小训练蛋白对用于蛋白质结构和动力学模拟的基于物理的粗粒度UNRES力场进行了优化。进行了四轮优化,其中优化的力场参数数量逐渐增加,随后用一组未用于优化的22种α蛋白、12种β蛋白和12种α + β蛋白对所得力场进行了测试。结果表明,能量项权重、局部和相关势、侧链半径以及各向异性均得到优化的变体具有最强的可转移性,并且在测试集上优于所有先前版本的UNRES。

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