Evidence map›Paper›PMID 39848609›Full record

ArticleThe journal of physical chemistry. B2025

Free Energy, Rates, and Mechanism of Transmembrane Dimerization in Lipid Bilayers from Dynamically Unbiased Molecular Dynamics Simulations.

Emil Jackel, Gianmarco Lazzeri, Roberto Covino

Abstract read
In one paragraph

Article in The journal of physical chemistry. B, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. STIM1 transmembrane helix dimerization captured by AI-guided transition path sampling.Proceedings of the National Academy of Sciences of the United States of America · 2025
    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.

Emil JackelInstitute of Biophysics, Goethe University Frankfurt, Frankfurt am Main 60438, Germany.
Gianmarco LazzeriFrankfurt Institute for Advanced Studies, Frankfurt am Main 60438, Germany.ORCID 0000-0002-0593-5572
Roberto CovinoFrankfurt Institute for Advanced Studies, Frankfurt am Main 60438, Germany.ORCID 0000-0003-0884-0402

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The assembly of proteins in membranes plays a key role in many crucial cellular pathways. Despite their importance, characterizing transmembrane assembly remains challenging for experiments and simulations. Equilibrium molecular dynamics simulations do not cover the time scales required to sample the typical transmembrane assembly. Hence, most studies rely on enhanced sampling schemes that steer the dynamics of transmembrane proteins along a collective variable that should encode all slow degrees of freedom. However, given the complexity of the condensed-phase lipid environment, this is far from trivial, with the consequence that free energy profiles of dimerization can be poorly converged. Here, we introduce an alternative approach, which relies only on simulating short, dynamically unbiased paths, avoiding using collective variables or biasing forces. By merging all paths, we obtain free energy profiles, rates, and mechanisms of transmembrane dimerization with the same set of simulations. We showcase our algorithm by sampling the spontaneous association and dissociation of a transmembrane protein in a lipid bilayer, the popular coarse-grained Martini force field. Our algorithm represents a promising way to investigate assembly processes in biologically relevant membranes, overcoming some of the challenges of conventional methods.

Indexed as

Lipid BilayersMembrane ProteinsMolecular Dynamics SimulationAlgorithmsDimerizationProtein MultimerizationThermodynamicsLipid BilayersMembrane Proteins

Identifiers

PMID39848609
PMCPMC11808646

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LicenceCC BY-NC-ND
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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.