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Record W4318162772 · doi:10.1038/s41598-023-28026-z

Regulatory mechanisms of the dynein-2 motility by post-translational modification revealed by MD simulation

2023· article· en· W4318162772 on OpenAlexafffund
Shintaroh Kubo, Khanh Huy Bui

Bibliographic record

VenueScientific Reports · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Kidney Cyst Diseases
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaJapan Society for the Promotion of ScienceCanadian Institutes of Health Research
KeywordsDyneinIntraflagellar transportCiliumMicrotubuleCell biologyMotilityFlagellumKinesinChemistryBiophysicsBiologyBiochemistry

Abstract

fetched live from OpenAlex

Intraflagellar transport for ciliary assembly and maintenance is driven by dynein and kinesins specific to the cilia. It has been shown that anterograde and retrograde transports run on different regions of the doublet microtubule, i.e., separate train tracks. However, little is known about the regulatory mechanism of this selective process. Since the doublet microtubule is known to display specific post-translational modifications of tubulins, i.e., "tubulin code", for molecular motor regulations, we investigated the motility of ciliary specific dynein-2 under different post-translational modification by coarse-grained molecular dynamics. Our setup allows us to simulate the landing behaviors of dynein-2 on un-modified, detyrosinated, poly-glutamylated and poly-glycylated microtubules in silico. Our study revealed that poly-glutamylation can play an inhibitory effect on dynein-2 motility. Our result indicates that poly-glutamylation of the B-tubule of the doublet microtubule can be used as an efficient means to target retrograde intraflagellar transport onto the A-tubule.

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)0.001
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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.009
GPT teacher head0.247
Teacher spread0.239 · 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

Citations4
Published2023
Admission routes2
Has abstractyes

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