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Record W2136116074 · doi:10.1021/jp310255r

Molecular Dynamic Studies of Transportan Interacting with a DPPC Lipid Bilayer

2012· article· en· W2136116074 on OpenAlexaff
Mohsen Pourmousa, Jirasak Wong-ekkabut, Michael Patra, Mikko Karttunen

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsUniversity of WaterlooWestern University
Fundersnot available
KeywordsPeptideLipid bilayerBilayerMembraneDrug deliveryBiophysicsPenetration (warfare)ChemistryCell-penetrating peptideAntimicrobial peptidesNanotechnologyBiochemistryMaterials scienceBiology

Abstract

fetched live from OpenAlex

Translocation of peptides through cellular membranes is a fundamental problem in developing antimicrobial peptides and in drug delivery. There is a class of peptides, known as cell-penetrating peptides, that are able to penetrate membranes without disrupting them. They can carry pharmacological compounds, thus a promising strategy for drug delivery. The physical mechanisms that facilitate translocation are not known. We have used large-scale molecular dynamics simulations to study the penetration of transportan across a zwitterionic dipalmitoyl-phosphatidyl-choline (DPPC) bilayer. We obtained the free energy profile for one peptide inside the bilayer and discuss the response of the bilayer to the presence of transportan. We also discuss the importance of lysine residues and speculate on the possible penetration mechanism of the peptide and propose a graded-like penetration process.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.287
Teacher spread0.275 · 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

Citations38
Published2012
Admission routes1
Has abstractyes

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Same venueThe Journal of Physical Chemistry BSame topicRNA Interference and Gene DeliveryFrench-language works237,207