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Record W2169980354 · doi:10.1021/jp0348981

Methodological Issues in Lipid Bilayer Simulations

2003· article· en· W2169980354 on OpenAlexafffund
Céline Anézo, Alex H. de Vries, Hans‐Dieter Höltje, D. Peter Tieleman, ‪Siewert J. Marrink

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsUniversity of Calgary
FundersFondation pour la Recherche MédicaleNatural Sciences and Engineering Research Council of CanadaKoninklijke Nederlandse Akademie van Wetenschappen
KeywordsMolecular dynamicsDipalmitoylphosphatidylcholineElectrostaticsForce field (fiction)Lipid bilayerBilayerStatistical physicsCoupling (piping)CoulombRange (aeronautics)ChemistryChemical physicsPhysicsComputational chemistryMaterials sciencePhysical chemistryPhosphatidylcholineMembraneQuantum mechanics

Abstract

fetched live from OpenAlex

Methodological issues in molecular dynamics (MD) simulations, such as the treatment of long-range electrostatic interactions or the type of pressure coupling, have important consequences for the equilibrium properties observed. We report a series of long (up to 150 ns) MD simulations of dipalmitoylphosphatidylcholine (DPPC) bilayers in which the methodology of simulation is systematically varied. Comparisons of simulations with truncation schemes, Ewald summations, and modified Coulomb interactions, either by shift functions or reaction field models, to describe long-range electrostatics point out the artifacts inherent in each of these methods and above all those of straight cutoff methods. We further show that bilayer properties are less sensitive to the details of the pressure-coupling algorithm and that an increased integration time step of 5 fs can be safely used in simulations of phosphatidylcholine lipid bilayers.

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)0.022
metaresearch head score (Gemma)0.084
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.022
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.084
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.047
GPT teacher head0.351
Teacher spread0.303 · 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
GenreMethods

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

Citations367
Published2003
Admission routes2
Has abstractyes

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Same venueThe Journal of Physical Chemistry BSame topicLipid Membrane Structure and BehaviorFrench-language works237,207