In silico Investigations of the Mode of Action of Novel Colchicine Derivatives Targeting β-Tubulin Isotypes: A Search for a Selective and Specific β-III Tubulin Ligand
Why this work is in the frame
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Bibliographic record
Abstract
The cardinal role of microtubules in cell mitosis makes them interesting drug targets for many pharmacological treatments, including those against cancer. Moreover, different expression patterns between cell types for several tubulin isotypes represent a great opportunity to improve the selectivity and specificity of the employed drugs and to design novel compounds with higher activity only on cells of interest. In this context, tubulin isotype βIII represents an excellent target for anti-tumoral therapies since it is overexpressed in most cancer cells and correlated with drug resistance. Colchicine is a well-known antimitotic agent, which is able to bind the tubulin dimer and to halt the mitotic process. However, it shows high toxicity also on normal cells and it is not specific for isotype βIII. In this context, the search for colchicine derivatives is a matter of great importance in cancer research. In this study, homology modeling techniques, molecular docking, and molecular dynamics simulations have been employed to characterize the interaction between 55 new promising colchicine derivatives and tubulin isotype βIII. These compounds were screened and ranked based on their binding affinity and conformational stability in the colchicine binding site of tubulin βIII. Results from this study point the attention on an amide of 4-chlorine thiocolchicine. This colchicine-derivative is characterized by a unique mode of interaction with tubulin, compared to all other compounds considered, which is primarily characterized by the involvement of the α-T5 loop, a key player in the colchicine binding site. Information provided by the present study may be particularly important in the rational design of colchicine-derivatives targeting drug resistant cancer phenotypes.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it