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基于最小经验校准的生物分子构建基块的可极化力场的推导。

Deriving a Polarizable Force Field for Biomolecular Building Blocks with Minimal Empirical Calibration.

机构信息

AIMMS Division of Molecular Toxicology, De Boelelaan 1108, 1081 HV Amsterdam, The Netherlands.

出版信息

J Phys Chem B. 2020 Mar 5;124(9):1628-1636. doi: 10.1021/acs.jpcb.9b10903. Epub 2020 Feb 19.

Abstract

Force field parametrization involves a complex set of linked optimization problems, with the goal of describing complex molecular interactions by using simple classical potential-energy functions that model Coulomb interactions, dispersion, and exchange repulsion. These functions comprise a set of atomic (and molecular) parameters and together with the bonded terms they constitute the molecular mechanics force field. Traditionally, many of these parameters have been fitted in a calibration approach in which experimental measures for thermodynamic and other relevant properties of small-molecule compounds are used for fitting and validation. As these approaches are laborious and time-consuming and represent an underdetermined optimization problem, we study methods to fit and derive an increasing number of parameters directly from electronic structure calculations, in order to greatly reduce possible parameter space for the remaining free parameters. In the current work we investigate a polarizable model with a higher order dispersion term for use in biomolecular simulation. Results for 49 biochemically relevant molecules are presented including updated parameters for hydrocarbon side chains. We show that our recently presented set of QM/MM derived atomic polarizabilities can be used in direct conjunction with partial charges and a higher order dispersion model that are quantum-mechanically determined, to freeze nearly all (i.e., 132 out of 138) nonbonded parameters to their quantum determined values.

摘要

力场参数化涉及一组复杂的链接优化问题,其目的是通过使用简单的经典势能函数来描述复杂的分子相互作用,这些势能函数模拟库仑相互作用、色散和交换排斥。这些函数包含一组原子(和分子)参数,与键合项一起构成分子力学力场。传统上,这些参数中的许多都是通过校准方法来拟合的,在这种方法中,使用小分子化合物的热力学和其他相关性质的实验测量值来进行拟合和验证。由于这些方法既繁琐又耗时,并且代表一个欠定的优化问题,我们研究了从电子结构计算中直接拟合和推导出越来越多参数的方法,以便大大减少剩余自由参数的可能参数空间。在目前的工作中,我们研究了一种具有高阶色散项的极化模型,用于生物分子模拟。我们提出了 49 种生物化学相关分子的结果,包括更新的烃侧链参数。我们表明,我们最近提出的一组基于 QM/MM 的原子极化率可以与部分电荷和量子力学确定的高阶色散模型直接结合使用,从而将几乎所有(即 138 个中的 132 个)非键参数冻结到它们的量子确定值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3375/7061328/fd4c6f03dfda/jp9b10903_0001.jpg

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