QMMM 2023: A program for combined quantum mechanical and molecular mechanical modeling and simulations

QM/毫米 嵌入 高斯分布 分子动力学 极化率 物理 偶极子 量子 统计物理学 部分电荷 电荷(物理) 计算科学 材料科学 计算物理学 计算机科学 量子力学 分子 人工智能
作者
Hai Lin,Yan Zhang,Soroosh Pezeshki,Adam W. Duster,Bo Wang,Xin‐Ping Wu,Shi-Wen Zheng,Laura Gagliardi,Donald G. Truhlar
出处
期刊:Computer Physics Communications [Elsevier]
卷期号:295: 108987-108987 被引量:13
标识
DOI:10.1016/j.cpc.2023.108987
摘要

Combined quantum mechanical and molecular mechanical (QM/MM) methods play an important role in multiscale modeling and simulations. QMMM 2023 is a general-purpose program for single-point calculations, geometry optimizations, transition-state optimizations, and molecular dynamics (MD) at the QM/MM level. It calls a QM package and an MM package to perform the required single-level calculations and combines them into a QM/MM energy by a variety of schemes. QMMM 2023 supports GAMESS-US, Gaussian, and ORCA as QM packages and Tinker as the MM package. Four types of treatments are available for embedding the QM subsystem in the MM environment: mechanical embedding with gas-phase calculations of the QM region, electronic embedding that allows polarization of the QM region by the MM environment, polarizable embedding for mutual polarization of the QM and MM regions, and flexible embedding for both mutual polarization and partial charge transfer between the QM and MM regions. Boundaries between QM and MM regions that pass through covalent bonds can be treated by several methods, including the redistributed charge (RC) scheme, redistributed charge and dipole (RCD) scheme, balanced-RC scheme, balanced-RCD scheme, screened charge scheme that takes account of charge penetration effects, and smeared charge scheme that delocalizes the MM charges near the QM–MM boundary. Geometry optimization can be done using the optimizer implemented in QMMM 2023 or the Berny optimizer in Gaussian through external calls to Gaussian. Molecular dynamics simulations can be performed at the pure-MM level, pure-QM level, fixed-partitioning QM/MM level, and adaptive-partitioning QM/MM level. The adaptive-partitioning treatments permit on-the-fly relocation of the QM–MM boundary by dynamically reclassifying atoms or groups into the QM or MM subsystems. Program Title: QMMM 2023. CPC Library link to program files: https://doi.org/10.17632/zmkc9db4zj.1. Licensing provisions: Apache-2.0 for the program and CC-BY-4.0 for the manual. Programming languages: Fortran90, Perl, and shell scripting. Nature of problem: Multiscale modeling and simulations by the combined quantum mechanical and molecular mechanical (QM/MM) method. Solution method: The program performs single-point calculations, geometry optimizations, transition state optimizations, and molecular dynamics (MD) by the QM/MM method by interfacing calls to binary executables in a QM package (GAMESS-US, Gaussian, or ORCA) and an MM package (TINKER) for the required calculations. QMMM 2023 supports various types of embedding schemes and multiple ways of treating a QM-MM boundary passing through a covalent bond. Additional comments including restrictions and unusual features: (1) QMMM 2023 supports polarizable-embedding and flexible-embedding schemes based on the electronegativity equalization principle and allowing charge transfer between the QM and MM regions. (2) For a QM-MM boundary passing through covalent bonds, all link-atom-based treatments preserve the charge of the MM region (and MM bond dipoles if desired) while effectively avoiding the over-polarization of the QM region. Further tuning is available to account for the charge penetration effects at the QM-MM boundary. (3) For dynamics simulations, Hamiltonian-based adaptive-partitioning algorithms allow on-the-fly reclassification of atoms or groups into the QM or MM regions without abrupt changes in the energy of the entire system or in the forces on all atoms.
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