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Record W4385716166 · doi:10.1042/bst20221238

New insights into the mechanochemical coupling mechanism of kinesin–microtubule complexes from their high-resolution structures

2023· review· en· W4385716166 on OpenAlexafffund
Matthieu P. M. H. Benoit, Byron Hunter, John S. Allingham, Hernando Sosa

Bibliographic record

VenueBiochemical Society Transactions · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsQueen's University
FundersNational Institute of General Medical SciencesCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsMicrotubuleKinesinMotor proteinATP hydrolysisBiophysicsChemistryCoupling (piping)TubulinCytoskeletonCell biologyMotilityMolecular motorDepolymerizationBiologyBiochemistryCellMaterials scienceEnzyme

Abstract

fetched live from OpenAlex

Kinesin motor proteins couple mechanical movements in their motor domain to the binding and hydrolysis of ATP in their nucleotide-binding pocket. Forces produced through this 'mechanochemical' coupling are typically used to mobilize kinesin-mediated transport of cargos along microtubules or microtubule cytoskeleton remodeling. This review discusses the recent high-resolution structures (<4 Å) of kinesins bound to microtubules or tubulin complexes that have resolved outstanding questions about the basis of mechanochemical coupling, and how family-specific modifications of the motor domain can enable its use for motility and/or microtubule depolymerization.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.351
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.269
Teacher spread0.246 · 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 teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreReview

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

Citations21
Published2023
Admission routes2
Has abstractyes

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