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本文引用的文献

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2
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J Chem Theory Comput. 2019 Oct 8;15(10):5543-5562. doi: 10.1021/acs.jctc.9b00401. Epub 2019 Sep 17.
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Molecules. 2018 Oct 19;23(10):2695. doi: 10.3390/molecules23102695.
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论蛋白质分子力学表征对量子力学能量表面的忠实性。

On the faithfulness of molecular mechanics representations of proteins towards quantum-mechanical energy surfaces.

作者信息

König Gerhard, Riniker Sereina

机构信息

Max-Planck-Institut für Kohlenforschung, Kaiser-Wilhelm-Platz 1, 45470 Mülheim an der Ruhr, Germany.

Laboratory of Physical Chemistry, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland.

出版信息

Interface Focus. 2020 Dec 6;10(6):20190121. doi: 10.1098/rsfs.2019.0121. Epub 2020 Oct 16.

DOI:10.1098/rsfs.2019.0121
PMID:33184586
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7653345/
Abstract

Force fields based on molecular mechanics (MM) are the main computational tool to study the relationship between protein structure and function at the molecular level. To validate the quality of such force fields, high-level quantum-mechanical (QM) data are employed to test their capability to reproduce the features of all major conformational substates of a series of blocked amino acids. The phase-space overlap between MM and QM is quantified in terms of the average structural reorganization energies over all energy minima. Here, the structural reorganization energy is the MM potential-energy difference between the structure of the respective QM energy minimum and the structure of the closest MM energy minimum. Thus, it serves as a measure for the relative probability of visiting the QM minimum during an MM simulation. We evaluate variants of the AMBER, CHARMM, GROMOS and OPLS biomolecular force fields. In addition, the two blocked amino acids alanine and serine are used to demonstrate the dependence of the measured agreement on the QM method, the phase, and the conformational preferences. Blocked serine serves as an example to discuss possible improvements of the force fields, such as including polarization with Drude particles, or using tailored force fields. The results show that none of the evaluated force fields satisfactorily reproduces all energy minima. By decomposing the average structural reorganization energies in terms of individual energy terms, we can further assess the individual weaknesses of the parametrization strategies of each force field. The dominant problem for most force fields appears to be the van der Waals parameters, followed to a lesser degree by dihedral and bonded terms. Our results show that performing a simple QM energy optimization from an MM-optimized structure can be a first test of the validity of a force field for a particular target molecule.

摘要

基于分子力学(MM)的力场是在分子水平上研究蛋白质结构与功能关系的主要计算工具。为了验证此类力场的质量,采用高级量子力学(QM)数据来测试它们再现一系列受阻氨基酸所有主要构象亚态特征的能力。MM和QM之间的相空间重叠根据所有能量极小值的平均结构重组能进行量化。这里,结构重组能是相应QM能量极小值的结构与最接近的MM能量极小值的结构之间的MM势能差。因此,它可作为衡量在MM模拟过程中访问QM极小值相对概率的指标。我们评估了AMBER、CHARMM、GROMOS和OPLS生物分子力场的变体。此外,使用两种受阻氨基酸丙氨酸和丝氨酸来证明所测得的一致性对QM方法、相和构象偏好的依赖性。受阻丝氨酸作为一个例子来讨论力场可能的改进,例如包括使用德鲁德粒子的极化,或使用定制的力场。结果表明,所评估的力场中没有一个能令人满意地再现所有能量极小值。通过将平均结构重组能按单个能量项进行分解,我们可以进一步评估每个力场参数化策略的个体弱点。大多数力场的主要问题似乎是范德华参数,其次是二面角和键合项,但程度较轻。我们的结果表明,从MM优化结构进行简单的QM能量优化可以作为对特定目标分子力场有效性的首次测试。