Evidence map›Paper›PMID 24158802›Full record

ArticleAdvances in experimental medicine and biology2014

Coarse-grained molecular dynamics provides insight into the interactions of lipids and cholesterol with rhodopsin.

Joshua N Horn, Ta-Chun Kao, Alan Grossfield

Abstract read
In one paragraph

Article in Advances in experimental medicine and biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
4.6field-weighted citation impact, top 5% of its field
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

18 citing papers in PubMed, 28 citations in OpenAlex.

  1. The Evolution of Lipids from Solvents to Substrates.Annual review of biophysics · 2026
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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 at 1 institution in 1 country.

Joshua N HornDepartment of Biochemistry and Biophysics, University of Rochester Medical Center, 601 Elmwood Ave, 712, Rochester, NY, 14642, USA.
Ta-Chun Kao
Alan Grossfield
University of Rochester Medical Center · US

Funding

Multiscale modeling of G protein-coupled receptorsR01GM095496 · NIGMS · UNIVERSITY OF ROCHESTER · PI GROSSFIELD, ALAN · 2011 to 2015
$1.3M
NIGMS NIH HHS 1R01GM095496NIGMS NIH HHS R01 GM095496
6 · The paper itself

Abstract

Protein function is a complicated interplay between structure and dynamics, which can be heavily influenced by environmental factors and conditions. This is particularly true in the case of membrane proteins, such as the visual receptor rhodopsin. It has been well documented that lipid headgroups, polyunsaturated tails, and the concentration of cholesterol in membranes all play a role in the function of rhodopsin. Recently, we used all-atom simulations to demonstrate that different lipid species have preferential interactions and possible binding sites on rhodopsin's surface, consistent with experiment. However, the limited timescales of the simulations meant that the statistical uncertainty of these results was substantial. Accordingly, we present here 32 independent 1.6 μs coarse-grained simulations exploring lipids and cholesterols surrounding rhodopsin and opsin, in lipid bilayers mimicking those found naturally. Our results agree with those found experimentally and in previous simulations, but with far better statistical certainty. The results demonstrate the value of combining all-atom and coarse-grained models with experiment to provide a well-rounded view of lipid-protein interactions.

Indexed as

CholesterolLipid BilayersLipidsMembrane LipidsMembrane ProteinsModels, BiologicalMolecular Dynamics SimulationOpsinsRhodopsinCholesterolLipid BilayersLipidsMembrane LipidsMembrane ProteinsOpsinsRhodopsin

Identifiers

PMID24158802
PMCPMC4034522
OpenAlexW171886678

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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.