Lu You, Sen Kakali, Yong Chin, Gunn David S D, Purton John A, Guan Jingcheng, Desmoutier Alec, Abdul Nasir Jamal, Zhang Xingfan, Zhu Lei, Hou Qing, Jackson-Masters Joe, Watts Sam, Hanson Rowan, Thomas Harry N, Jayawardena Omal, Logsdail Andrew J, Woodley Scott M, Senn Hans M, Sherwood Paul, Catlow C Richard A, Sokol Alexey A, Keal Thomas W
STFC Scientific Computing, Daresbury Laboratory, Keckwick Lane, Daresbury, Warrington, WA4 4AD, UK.
Kathleen Lonsdale Materials Chemistry, Department of Chemistry, University College London, 20 Gordon Street, London, WC1H 0AJ, UK.
Phys Chem Chem Phys. 2023 Aug 23;25(33):21816-21835. doi: 10.1039/d3cp00648d.
Hybrid quantum mechanical/molecular mechanical (QM/MM) methods are a powerful computational tool for the investigation of all forms of catalysis, as they allow for an accurate description of reactions occurring at catalytic sites in the context of a complicated electrostatic environment. The scriptable computational chemistry environment ChemShell is a leading software package for QM/MM calculations, providing a flexible, high performance framework for modelling both biomolecular and materials catalysis. We present an overview of recent applications of ChemShell to problems in catalysis and review new functionality introduced into the redeveloped Python-based version of ChemShell to support catalytic modelling. These include a fully guided workflow for biomolecular QM/MM modelling, starting from an experimental structure, a periodic QM/MM embedding scheme to support modelling of metallic materials, and a comprehensive set of tutorials for biomolecular and materials modelling.
混合量子力学/分子力学(QM/MM)方法是研究各种催化形式的强大计算工具,因为它们能够在复杂的静电环境中准确描述催化位点发生的反应。可编写脚本的计算化学环境ChemShell是用于QM/MM计算的领先软件包,为生物分子和材料催化建模提供了灵活、高性能的框架。我们概述了ChemShell在催化问题上的近期应用,并回顾了重新开发的基于Python的ChemShell版本中引入的支持催化建模的新功能。这些功能包括从实验结构开始的生物分子QM/MM建模的全引导工作流程、支持金属材料建模的周期性QM/MM嵌入方案,以及一套全面的生物分子和材料建模教程。