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用于超分子结构的共价键合金属的自动力场参数化

: Automated Force-Field Parameterization of Covalently Bound Metals for Supramolecular Structures.

作者信息

Piskorz Tomasz K, Lee Bernadette, Zhan Shaoqi, Duarte Fernanda

机构信息

Department of Chemistry, University of Oxford, Oxford OX1 3QZ, U.K.

Department of Chemistry─Ångström, Ångströmlaboratoriet Box 523, Uppsala S-751 20, Sweden.

出版信息

J Chem Theory Comput. 2024 Oct 22;20(20):9060-9071. doi: 10.1021/acs.jctc.4c00850. Epub 2024 Oct 7.

DOI:10.1021/acs.jctc.4c00850
PMID:39373209
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11500408/
Abstract

Metal ions play a central, functional, and structural role in many molecular structures, from small catalysts to metal-organic frameworks (MOFs) and proteins. Computational studies of these systems typically employ classical or quantum mechanical approaches or a combination of both. Among classical models, only the covalent metal model reproduces both geometries and charge transfer effects but requires time-consuming parameterization, especially for supramolecular systems containing repetitive units. To streamline this process, we introduce , a Python tool designed for efficient force-field parameterization of supramolecular structures. has been tested on diverse systems including supramolecular cages, knots, and MOFs. Our benchmarks demonstrate that parameters accurately reproduce the reference properties obtained from quantum calculations and crystal structures. Molecular dynamics simulations of the generated structures consistently yield stable simulations in explicit solvent, in contrast to similar simulations performed with nonbonded and cationic dummy models. Overall, facilitates the atomistic modeling of supramolecular systems, key for understanding their dynamic properties and host-guest interactions. The tool is freely available on GitHub (https://github.com/duartegroup/metallicious).

摘要

金属离子在许多分子结构中发挥着核心、功能和结构作用,从小型催化剂到金属有机框架(MOF)和蛋白质。对这些系统的计算研究通常采用经典或量子力学方法或两者结合。在经典模型中,只有共价金属模型能够再现几何形状和电荷转移效应,但需要耗时的参数化,特别是对于包含重复单元的超分子系统。为了简化这一过程,我们引入了Metallicious,这是一个用于超分子结构高效力场参数化的Python工具。Metallicious已在包括超分子笼、结和MOF在内的各种系统上进行了测试。我们的基准测试表明,参数能够准确再现从量子计算和晶体结构获得的参考性质。与使用非键合和阳离子虚拟模型进行的类似模拟相比,生成结构的分子动力学模拟在显式溶剂中始终产生稳定的模拟。总体而言,Metallicious促进了超分子系统的原子建模,这对于理解其动态性质和主客体相互作用至关重要。该工具可在GitHub(https://github.com/duartegroup/metallicious)上免费获取。

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