Modeling the Colchicum autumnale Tubulin and a Comparison of Its Interaction with Colchicine to Human Tubulin
Bibliographic record
Abstract
Tubulin is the target for many small-molecule natural compounds, which alter microtubules dynamics, and lead to cell cycle arrest and apoptosis. One of these compounds is colchicine, a plant alkaloid produced by Colchicum autumnale. While C. autumnale produces a potent cytotoxin, colchicine, and expresses its target protein, it is immune to colchicine’s cytotoxic action and the mechanism of this resistance is hitherto unknown. In the present paper, the molecular mechanisms responsible for colchicine resistance in C. autumnale are investigated and compared to human tubulin. To this end, homology models for C. autumnale α-β tubulin heterodimer are created and molecular dynamics (MD) simulations together with molecular mechanics Poisson–Boltzmann calculations (MM/PBSA) are performed to determine colchicine’s binding affinity for tubulin. Using our molecular approach, it is shown that the colchicine-binding site in C. autumnale tubulin contains a small number of amino acid substitutions compared to human tubulin. However, these substitutions induce significant reduction in the binding affinity for tubulin, and subsequently fewer conformational changes in its structure result. It is suggested that such small conformational changes are insufficient to profoundly disrupt microtubule dynamics, which explains the high resistance to colchicine by C. autumnale.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".