Structural basis for polyglutamate chain initiation and elongation by TTLL family enzymes
Bibliographic record
Abstract
Abstract Glutamylation, introduced by TTLL enzymes, is the most abundant modification of brain tubulin. Essential effector proteins read the tubulin glutamylation pattern, and its misregulation causes neurodegeneration. TTLL glutamylases posttranslationally add glutamates to internal glutamates in tubulin C-terminal tails (branch initiation, through an isopeptide bond), and additional glutamates can extend these (elongation). TTLLs are thought to specialize for initiation or elongation, but the mechanistic basis for regioselectivity is unknown. We present cocrystal structures of murine TTLL6 bound to tetrahedral intermediate analogs that delineate key active-site residues that make this an elongase. We show that TTLL4 is exclusively an initiase, and through combined structural and phylogenetic analyses, engineer TTLL6 into a branch-initiating enzyme. TTLL glycylases add glycines posttranslationally to internal glutamates, and we find that the same active-site residues discriminate between initiase and elongase glycylases. These active-site specializations of TTLL glutamylases and glycylases ultimately yield the chemical complexity of cellular microtubules.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".