Bibliographic record
Abstract
Kinesins are a diverse group of adenosine triphosphate (ATP)-dependent motor proteins that transport cargos along microtubules (MTs) and change the organization of MT networks. Shared among all kinesins is a ~40 kDa motor domain that has evolved an impressive assortment of motility and MT remodeling mechanisms as a result of subtle tweaks and edits within its sequence. Several elegant studies of different kinesin isoforms have exposed the purpose of structural changes in the motor domain as it engages and leaves the MT. However, few studies have compared the sequences and MT contacts of these kinesins systematically. Along with clever strategies to trap kinesin-tubulin complexes for X-ray crystallography, new advancements in cryo-electron microscopy have produced a burst of high-resolution structures that show kinesin-MT interfaces more precisely than ever. This review considers the MT interactions of kinesin subfamilies that exhibit significant differences in speed, processivity, and MT remodeling activity. We show how their sequence variations relate to their tubulin footprint and, in turn, how this explains the molecular activities of previously characterized mutants. As more high-resolution structures become available, this type of assessment will quicken the pace toward establishing each kinesin's design-function relationship.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.013 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".