Evidence map›Paper›PMID 41652162›Full record

ReviewAdvances in experimental medicine and biology2026

Quantum Mechanical/Molecular Mechanical (QM/MM) Studies of Enzymes.

Ramanathan Rajesh, Nadia Elghobashi-Meinhardt

Abstract readReview
PubMed Publisher
In one paragraph

Review in Advances in experimental medicine and biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ramanathan RajeshSchool of Chemistry, University College Dublin, Dublin, Ireland.
Nadia Elghobashi-MeinhardtSchool of Chemistry, University College Dublin, Dublin, Ireland. nadia.elghobashi-meinhardt@ucd.ie.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Computational methods are presented for modeling the catalytic center of an enzyme and calculating the energy associated with given molecular geometry. First, an introduction to general theory is given, including a brief discussion of quantum mechanics (QM), molecular mechanics (MM), and hybrid QM/MM, a standard approach that divides the system into a region requiring a description of the electronic structure (QM) and a remainder that can be considered a perturbation (MM) to the system. Next, the nitrogenase enzyme will be used as a sample system to explain in detail how modeling is carried out. This discussion will review the broken symmetry (BS) approach within DFT, a computational approach that describes the spin states of multiple Fe centers. The review concludes with a discussion of machine learning (ML) and the training of a neural network (NN) potential based on QM calculations.

Indexed as

EnzymesMolecular Dynamics SimulationNitrogenaseQuantum MechanicsQuantum TheoryCatalytic DomainMachine LearningModels, MolecularNeural Networks, ComputerEnzymesNitrogenaseBroken symmetry (BS)Density function theory (DFT)Machine learning (ML)Neural network potential (NNP)NitrogenaseQuantum mechanics (QM)/molecular mechanics (MM)

Identifiers

PMID41652162

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.