Evidence map›Paper›PMID 39793883›Full record

ReviewJournal of molecular biology2025

The Influence of Phosphoinositide Lipids in the Molecular Biology of Membrane Proteins: Recent Insights from Simulations.

George Hedger, Hsin-Yung Yen

Abstract readReview
In one paragraph

Review in Journal of molecular biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. International journal of molecular sciences · 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

2 authors.

George HedgerDepartment of Life Sciences, Sir Ernst Chain Building, Imperial College London, London, SW7 2AZ, UK. Electronic address: g.hedger@imperial.ac.uk.
Hsin-Yung YenInstitute of Biological Chemistry, Academia Sinica, Taipei 115, Taiwan; Department of Chemistry, University of Oxford, South Parks Road, Oxford, OX1 3QZ, UK.

Funding

Wellcome Trust 301619Wellcome Trust 301619/Z/23/Z
6 · The paper itself

Abstract

The phosphoinositide family of membrane lipids play diverse and critical roles in eukaryotic molecular biology. Much of this biological activity derives from interactions of phosphoinositide lipids with integral and peripheral membrane proteins, leading to modulation of protein structure, function, and cellular distribution. Since the discovery of phosphoinositides in the 1940s, combined molecular biology, biophysical, and structural approaches have made enormous progress in untangling this vast and diverse cellular network of interactions. More recently, in silico approaches such as molecular dynamics simulations have proven to be an asset in prospectively identifying, characterising, explaining the structural basis of these interactions, and in the best cases providing atomic level testable hypotheses on how such interactions control the function of a given membrane protein. This review details a number of recent seminal discoveries in phosphoinositide biology, enabled by advanced biomolecular simulation, and its integration with molecular biology, biophysical, and structural biology approaches. The results of the simulation studies agree well with experimental work, and in a number of notable cases have arrived at the key conclusion several years in advance of the experimental structures. SUMMARY: Hedger and Yen review developments in simulations of phosphoinositides and membrane proteins.

Indexed as

Membrane ProteinsMolecular Dynamics SimulationPhosphatidylinositolsAnimalsHumansMembrane ProteinsPhosphatidylinositolslipid-protein interactionMD simulationmembrane proteinphosphoinositidePIP(2)

Identifiers

PMID39793883
PMCPMC7617384

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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.