Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 522

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

AB INITIO QUANTUM CHEMICAL AND MIXED QUANTUM MECHANICS/MOLECULAR MECHANICS (QM/MM) METHODS FOR STUDYING ENZYMATIC CATALYSIS

Friesner, Richard A., Guallar, Victor·2005·Annual Review of Physical Chemistry

Abstract

▪ Abstract We describe large scale ab initio quantum chemical and mixed quantum mechanics/molecular mechanics (QM/MM) methods for studying enzymatic reactions. First, technical aspects of the methodology are reviewed, including the hybrid density functional theory (DFT) methods that are typically employed for the QM aspect of the calculations, and various approaches to defining the interface between the QM and MM regions in QM/MM approaches. The modeling of the enzymatic catalytic cycle for three examples—methane monooxygenase, cytochrome P450, and triose phosphate isomerase—are discussed in some depth, followed by a brief summary of other systems that have been investigated by ab initio methods over the past several years. Finally, a discussion of the qualitative and quantitative conclusions concerning enzymatic catalysis that are available from modern ab initio approaches is presented, followed by a conclusion briefly summarizing future prospects.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1146/annurev.physchem.55.091602.094410

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 3 references

Cited by

See all 522

Metadata

Authors
Friesner, R. A., & Guallar, V.
Venue
Annual Review of Physical Chemistry
Published
2005-05-05
Volume
56
Issue
1
Pages
389-427
ISSN
  • 0066-426X (ISSN-L)
  • 1545-1593
OpenAlex
W2101217381
Cited by
522
References
3
FWCI
2.32
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: AB INITIO QUANTUM CHEMICAL AND MIXED QUANTUM MECHANICS/MOLECULAR MECHANICS (QM/MM) METHODS FOR STUDYING ENZYMATIC CATALYSIS. https://app.cochat.ai/papers/10.1146/annurev.physchem.55.091602.094410
The paper
Friesner, R. A., & Guallar, V. (2005). AB INITIO QUANTUM CHEMICAL AND MIXED QUANTUM MECHANICS/MOLECULAR MECHANICS (QM/MM) METHODS FOR STUDYING ENZYMATIC CATALYSIS. Annual Review of Physical Chemistry. https://doi.org/10.1146/annurev.physchem.55.091602.094410

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.