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Cited by 433

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Free Energies of Chemical Reactions in Solution and in Enzymes with Ab Initio Quantum Mechanics/Molecular Mechanics Methods

Open access
Hu, Hao, Yang, Weitao·2008·Annual Review of Physical Chemistry

Abstract

Combined quantum mechanics/molecular mechanics (QM/MM) methods provide an accurate and efficient energetic description of complex chemical and biological systems, leading to significant advances in the understanding of chemical reactions in solution and in enzymes. Here we review progress in QM/MM methodology and applications, focusing on ab initio QM-based approaches. Ab initio QM/MM methods capitalize on the accuracy and reliability of the associated quantum-mechanical approaches, however, at a much higher computational cost compared with semiempirical quantum-mechanical approaches. Thus reaction-path and activation free-energy calculations based on ab initio QM/MM methods encounter unique challenges in simulation timescales and phase-space sampling. This review features recent developments overcoming these challenges and enabling accurate free-energy determination for reaction processes in solution and in enzymes, along with applications.

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Crossref · 10.1146/annurev.physchem.59.032607.093618

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Metadata

Authors
Hu, H., & Yang, W.
Venue
Annual Review of Physical Chemistry
Published
2008-05-01
Volume
59
Issue
1
Pages
573-601
ISSN
  • 0066-426X (ISSN-L)
  • 1545-1593
OpenAlex
W2152220941
Cited by
433
References
6
FWCI
1.87
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Free Energies of Chemical Reactions in Solution and in Enzymes with Ab Initio Quantum Mechanics/Molecular Mechanics Methods. https://app.cochat.ai/papers/10.1146/annurev.physchem.59.032607.093618
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Hu, H., & Yang, W. (2008). Free Energies of Chemical Reactions in Solution and in Enzymes with Ab Initio Quantum Mechanics/Molecular Mechanics Methods. Annual Review of Physical Chemistry. https://doi.org/10.1146/annurev.physchem.59.032607.093618

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.