In silico <b>induced</b> effect of <i>N‐ε‐</i><b>lysine acetylation</b> on microtubule stability and <i>subsequent</i> interaction of microtubule‐associated proteins
Bibliographic record
Abstract
Plant systems have been considered valuable models for addressing fundamental questions of microtubule (MT) organization due to their considerable practical utility. Protein acetylation is a very common protein modification, and therate of acetylation can be modulated in cells in different biological states, and these changes can be detected at a molecular level. Here, we focused on K40, K112, and K394 residues as putative acetylation sites, which were shown to exist in both plants and mammals. Such residual effect of acetylation causes critical but unclear effect on MT stability. In turn, it was shown that acetylation indirectly affects the probability of interaction with different MAPs (Microtubule-associated proteins). In a multiscale study using an all-atom force field to reproduce several lattice-forming elements found on the surface the microtubule, we assembled a fragment of a plant microtubule composed of nine tubulins and used it as a model object along with the existing human complex. Triplets of tubulins assembled in a lattice cell were then simulated for both human and plant protein complexes, using a coarse-grained force field. We then analyzed the trajectories and identified some critical deformations of the MAP interaction surface. The initial coordinates were used to investigate the structural scenario in which autophagy-related protein 8 (ATG8) was able to interact with the MT fragment.
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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) | 0.002 | 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".