Metabolites of Vinca Alkaloid Vinblastine: Tubulin Binding and Activation of Nausea-Associated Receptors
Bibliographic record
Abstract
Abstract Vinblastine (VLB) is an antimitotic drug that binds to the vinca site of tubulin. The molecule possesses a high molecular weight and a complex chemical structure with many possibilities of metabolization. Despite advances in drug discovery research in reducing drug toxicity, the cause and mechanism of VLB-induced adverse drug reactions (ADRs) remains poorly understood. VLB is metabolized to at least 35 known metabolites, which have been identified and collected in this present work. This study also explores how VLB metabolites affect nausea-associated receptors such as muscarinic, dopaminergic, and histaminic. The metabolites have stronger binding interactions than acetylcholine (ACh) for muscarinic M1, M4, and M5 receptors and demonstrate similar binding profiles to that of the natural substrate, ACh. The affinities of VLB metabolites to dopaminergic and histaminic receptors, their absorption, distribution, metabolism, excretion, toxicity properties, and the superiority of VLB to ACh for binding to M5R, indicate their potential to trigger activation of nausea-associated receptors during chemotherapy with VLB. It has been shown that metabolite 20-hydroxy-VLB (metabolite 10) demonstrates a stronger binding affinity to the vinca site of tubulin than VLB; however, they have similar modes of action. VLB and metabolite 10 have similar gastric solubility (FaSSGF), intestinal solubility (FeSSIF), and log P values. Metabolite 10 has a more acceptable pharmacokinetic profile than VLB, a better gastric and intestinal solubility. Furthermore, metabolite 10 was found to be less bound to plasma proteins than VLB. These are desired and essential features for effective drug bioavailability. Metabolite 10 is not a substrate of CYP2D6 and thus is less likely to cause drug–drug interactions and ADRs compared to its parent drug. The hydroxyl group added upon metabolism of VLB suggests that it can also be a reasonable starting compound for designing the next generation of antimitotic drugs to overcome P-glycoprotein-mediated multidrug resistance, which is often observed with vinca alkaloids.
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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) | 0.009 | 0.001 |
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".