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Record W2514689639 · doi:10.1021/acs.jpcb.6b07142

Ganglioside-Lipid and Ganglioside-Protein Interactions Revealed by Coarse-Grained and Atomistic Molecular Dynamics Simulations

2016· article· en· W2514689639 on OpenAlexafffund
Ruo‐Xu Gu, Helgi I. Ingólfsson, Alex H. de Vries, ‪Siewert J. Marrink, D. Peter Tieleman

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsUniversity of Calgary
FundersEuropean Research CouncilNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchAlberta Innovates - Health SolutionsAlberta Innovates - Technology Futures
KeywordsGangliosideMolecular dynamicsChemistryPotential of mean forceBiophysicsPolarizabilityCeramideHydrogen bondChemical physicsMoleculeComputational chemistryBiochemistryBiology

Abstract

fetched live from OpenAlex

Gangliosides are glycolipids in which an oligosaccharide headgroup containing one or more sialic acids is connected to a ceramide. Gangliosides reside in the outer leaflet of the plasma membrane and play a crucial role in various physiological processes such as cell signal transduction and neuronal differentiation by modulating structures and functions of membrane proteins. Because the detailed behavior of gangliosides and protein-ganglioside interactions are poorly known, we investigated the interactions between the gangliosides GM1 and GM3 and the proteins aquaporin (AQP1) and WALP23 using equilibrium molecular dynamics simulations and potential of mean force calculations at both coarse-grained (CG) and atomistic levels. In atomistic simulations, on the basis of the GROMOS force field, ganglioside aggregation appears to be a result of the balance between hydrogen bond interactions and steric hindrance of the headgroups. GM3 clusters are slightly larger and more ordered than GM1 clusters due to the smaller headgroup of GM3. The different structures of GM1 and GM3 clusters from atomistic simulations are not observed at the CG level based on the Martini model, implying a difference in driving forces for ganglioside interactions in atomistic and CG simulations. For protein-ganglioside interactions, in the atomistic simulations, GM1 lipids bind to specific sites on the AQP1 surface, whereas they are depleted from WALP23. In the CG simulations, the ganglioside binding sites on the AQP1 surface are similar, but ganglioside aggregation and protein-ganglioside interactions are more prevalent than in the atomistic simulations. Using the polarizable Martini water model, results were closer to the atomistic simulations. Although experimental data for validation is lacking, we proposed modified Martini parameters for gangliosides to more closely mimic the sizes and structures of ganglioside clusters observed at the atomistic level.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.236
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations98
Published2016
Admission routes2
Has abstractyes

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