Evidence map›Paper›PMID 32790367›Full record

ArticleThe journal of physical chemistry. B2020

Capturing Biologically Complex Tissue-Specific Membranes at Different Levels of Compositional Complexity.

Helgi I Ingólfsson, Harsh Bhatia, Talia Zeppelin, W F Drew Bennett, Kristy A Carpenter, Pin-Chia Hsu, Gautham Dharuman, Peer-Timo Bremer, Birgit Schiøtt, Felice C Lightstone and 1 more

Open access · bronzeAbstract read
In one paragraph

Article in The journal of physical chemistry. B, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
3.7field-weighted citation impact, top 6% 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

27 citing papers in PubMed, 68 citations in OpenAlex.

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  10. A Minimalist Model Lipid System Mimicking the Biophysical Properties ofLangmuir : the ACS journal of surfaces and colloids · 2025
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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

11 authors at 3 institutions in 2 countries.

Helgi I IngólfssonPhysical and Life Sciences Directorate, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550, United States.ORCID 0000-0002-7613-9143
Harsh BhatiaCenter for Applied Scientific Computing, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550, United States.ORCID 0000-0001-8712-7773
Talia ZeppelinDepartment of Chemistry and the Interdisciplinary Nanoscience Center (iNANO), Aarhus University, Langelandsgade 140, 8000 Aarhus, Denmark.
W F Drew BennettPhysical and Life Sciences Directorate, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550, United States.ORCID 0000-0003-3993-9077
Kristy A CarpenterMassachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.
Pin-Chia HsuDepartment of Chemistry and the Interdisciplinary Nanoscience Center (iNANO), Aarhus University, Langelandsgade 140, 8000 Aarhus, Denmark.
Gautham DharumanPhysical and Life Sciences Directorate, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550, United States.
Peer-Timo BremerCenter for Applied Scientific Computing, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550, United States.
Birgit SchiøttDepartment of Chemistry and the Interdisciplinary Nanoscience Center (iNANO), Aarhus University, Langelandsgade 140, 8000 Aarhus, Denmark.ORCID 0000-0001-9937-1562
Felice C LightstonePhysical and Life Sciences Directorate, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550, United States.
Timothy S CarpenterPhysical and Life Sciences Directorate, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550, United States.ORCID 0000-0001-7848-9983
Lawrence Livermore National Laboratory · USAarhus University · DKMassachusetts Institute of Technology · US

Funding

NCI NIH HHS HHSN261200800001E
6 · The paper itself

Abstract

Plasma membranes (PMs) contain hundreds of different lipid species that contribute differently to overall bilayer properties. By modulation of these properties, membrane protein function can be affected. Furthermore, inhomogeneous lipid mixing and domains of lipid enrichment/depletion can sort proteins and provide optimal local environments. Recent coarse-grained (CG) Martini molecular dynamics efforts have provided glimpses into lipid organization of different PMs: an "Average" and a "Brain" PM. Their high complexity and large size require long simulations (∼80 μs) for proper sampling. Thus, these simulations are computationally taxing. This level of complexity is beyond the possibilities of all-atom simulations, raising the question-what complexity is needed for "realistic" bilayer properties? We constructed CG Martini PM models of varying complexity (63 down to 8 different lipids). Lipid tail saturations and headgroup combinations were kept as consistent as possible for the "tissues'" (Average/Brain) at three levels of compositional complexity. For each system, we analyzed membrane properties to evaluate which features can be retained at lower complexity and validate eight-component bilayers that can act as reliable mimetics for Average or Brain PMs. Systems of reduced complexity deliver a more robust and malleable tool for computational membrane studies and allow for equivalent all-atom simulations and experiments.

Indexed as

Lipid BilayersMolecular Dynamics SimulationCell MembraneMembranesProteinsLipid BilayersProteins

Identifiers

PMID32790367
PMCPMC7553384
OpenAlexW3048515709

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.