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. As a result, 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.
Lin, Hai, et al. "QMMM 2023: A program for combined quantum mechanical and molecular mechanical modeling and simulations." Computer Physics Communications, vol. 295, Oct. 2023. https://doi.org/10.1016/j.cpc.2023.108987
Lin, Hai, Zhang, Yan, Pezeshki, Soroosh, Duster, Adam W., Wang, Bo, Wu, Xin-Ping, Zheng, Shi-Wen, Gagliardi, Laura, & Truhlar, Donald G. (2023). QMMM 2023: A program for combined quantum mechanical and molecular mechanical modeling and simulations. Computer Physics Communications, 295. https://doi.org/10.1016/j.cpc.2023.108987
Lin, Hai, Zhang, Yan, Pezeshki, Soroosh, et al., "QMMM 2023: A program for combined quantum mechanical and molecular mechanical modeling and simulations," Computer Physics Communications 295 (2023), https://doi.org/10.1016/j.cpc.2023.108987
@article{osti_2404529,
author = {Lin, Hai and Zhang, Yan and Pezeshki, Soroosh and Duster, Adam W. and Wang, Bo and Wu, Xin-Ping and Zheng, Shi-Wen and Gagliardi, Laura and Truhlar, Donald G.},
title = {QMMM 2023: A program for combined quantum mechanical and molecular mechanical modeling and simulations},
annote = {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. As a result, 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.},
doi = {10.1016/j.cpc.2023.108987},
url = {https://www.osti.gov/biblio/2404529},
journal = {Computer Physics Communications},
issn = {ISSN 0010-4655},
volume = {295},
place = {United States},
publisher = {Elsevier},
year = {2023},
month = {10}}
