Evidence map›Paper›PMID 37955428›Full record

ArticleJournal of chemical information and modeling2023

Calculation of Protein Folding Thermodynamics Using Molecular Dynamics Simulations.

Juan J Galano-Frutos, Francho Nerín-Fonz, Javier Sancho

Abstract read
In one paragraph

Article in Journal of chemical information and modeling, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Differentiable Thermodynamic Phase-Equilibria for Machine Learning.Journal of chemical information and modeling · 2026
    Article
  2. Thermophysical Properties of a tRNA Isodecoder.The journal of physical chemistry. B · 2026
    Article
  3. Article
  4. Review
  5. Review
  6. 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

3 authors.

Juan J Galano-FrutosDepartment of Biochemistry, Molecular and Cell Biology, Faculty of Science, University of Zaragoza, 50009 Zaragoza, Spain.ORCID 0000-0002-1896-7805
Francho Nerín-FonzDepartment of Biochemistry, Molecular and Cell Biology, Faculty of Science, University of Zaragoza, 50009 Zaragoza, Spain.ORCID 0000-0002-5548-7608
Javier SanchoDepartment of Biochemistry, Molecular and Cell Biology, Faculty of Science, University of Zaragoza, 50009 Zaragoza, Spain.ORCID 0000-0002-2879-9200

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite advances in artificial intelligence methods, protein folding remains in many ways an enigma to be solved. Accurate computation of protein folding energetics could help drive fields such as protein and drug design and genetic interpretation. However, the challenge of calculating the state functions governing protein folding from first-principles remains unaddressed. We present here a simple approach that allows us to accurately calculate the energetics of protein folding. It is based on computing the energy of the folded and unfolded states at different temperatures using molecular dynamics simulations. From this, two essential quantities (Δ

Indexed as

Artificial IntelligenceMolecular Dynamics SimulationProtein FoldingProteinsThermodynamicsProteins

Identifiers

PMID37955428
PMCPMC10751793

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.