Evidence map›Paper›PMID 41025957›Full record

ArticleJournal of chemical information and modeling2025

A Practical Covariance-Based Method for Efficient Detection of Protein-Protein Attractive and Repulsive Interactions in Molecular Dynamics Simulations.

Mert Golcuk, Mert Gur

Abstract read
In one paragraph

Article in Journal of chemical information and modeling, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Mert GolcukDepartment of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15213, United States.ORCID 0000-0001-5476-8160
Mert GurDepartment of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15213, United States.ORCID 0000-0003-0983-4397

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular dynamics simulations of large protein-protein complexes require scalable analysis. We present a correlation-based workflow that systematically identifies both attractive (stabilizing) interactions, such as salt bridges, and repulsive (destabilizing) interactions, such as same-charge electrostatic repulsions, across extensive interfaces. By constructing an interprotein covariance matrix, filtering residue pairs by distance, and identifying interactions underlying these correlations, our method focuses computational resources on the most relevant regions of the interface while preserving a high level of detail.

Indexed as

Molecular Dynamics SimulationProteinsProtein BindingProtein ConformationStatic ElectricityProteins

Identifiers

PMID41025957
PMCPMC12529755

What OpenQuestion holds

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LicenceCC BY
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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.