Evidence map›Paper›PMID 41863443›Full record

ArticleJournal of chemical theory and computation2026

Comprehensive Comparison of Molecular Fragmentation Schemes for Proteins.

Katharina Rüther, Ken Bunge, Lasse M Hilmer, Janine Hellmers, Carolin König

Abstract readComparative Study
In one paragraph

Article in Journal of chemical theory and computation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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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

5 authors.

Katharina RütherInstitute of Physical Chemistry and Electrochemistry, Leibniz University Hannover, Callinstr. 3A, 30167 Hannover, Germany.ORCID 0009-0006-3686-6262
Ken BungeInstitute of Physical Chemistry and Electrochemistry, Leibniz University Hannover, Callinstr. 3A, 30167 Hannover, Germany.
Lasse M HilmerInstitute of Physical Chemistry and Electrochemistry, Leibniz University Hannover, Callinstr. 3A, 30167 Hannover, Germany.
Janine HellmersInstitute of Physical Chemistry and Electrochemistry, Leibniz University Hannover, Callinstr. 3A, 30167 Hannover, Germany.ORCID 0000-0002-3488-310X
Carolin KönigInstitute of Physical Chemistry and Electrochemistry, Leibniz University Hannover, Callinstr. 3A, 30167 Hannover, Germany.ORCID 0000-0001-8931-4337

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Conventional quantum chemical (QC) methods exhibit a steep computational scaling with respect to the number of atoms in the investigated system. Hence, working with larger systems like peptides or even proteins becomes computationally unfeasible with traditional QC methods. One way to overcome this challenge is through molecular fragmentation methods. Many different flavours of molecular fragmentation schemes based on different partitionings have been suggested in the literature, but have hardly been compared numerically. Our group has recently reported a common formalism for molecular fragmentation schemes, which enables a consistent benchmark of different approaches. Here, we assess the performance of the molecular fractionation with hydrogen caps (MFHC), the pair-pair approximation to the generalized many-body expansion (pp-GMBE), the molecules-in-molecules (MIM) approach, and the kernel energy method (KEM) within this general framework. Our benchmark includes single- and multilevel schemes as well as an electrostatic embedding of the fragments in point charges of the whole system. The energies and computational demand of a chosen set of proteins are evaluated with the different methods within the framework. This enables a rare numerical comparison between the different schemes. Of the compared methods, our implementation of pp-GMBE yields the best agreement with supermolecular QC reference calculations, while MFHC with additional pair couplings offers a good cost-accuracy ratio.

Indexed as

ProteinsQuantum TheoryStatic ElectricityThermodynamicsProteins

Identifiers

PMID41863443
PMCPMC13085253

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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.