Biochemical and In Silico Studies on Triazole Derivatives as TyrosinaseInhibitors: Potential Treatment of Hyperpigmentation Related SkinDisorders
Bibliographic record
Abstract
Introduction:: Tyrosinase is a versatile, glycosylated copper-containing oxidase enzyme that mainly catalyzes the biosynthesis of melanin in mammals. Its overexpression leads to the formation of excess melanin, resulting in hyperpigmentary skin disorders, such as dark spots, melasma, freckles, etc. Therefore, inhibition of tyrosinase is a therapeutic approach for the treatment of hyperpigmentation. Method:: The current study focused on evaluating tyrosinase inhibitory activities of triazole derivatives 1-20, bearing different substituents on the phenyl ring. 17 derivatives have shown a potent tyrosinase inhibition with IC50 values between 1.6 to 13 μM, as compared to the standard drug, i.e., kojic acid (IC50 = 24.1 ± 0.5 μM). Particularly, compounds 11 and 15 displayed 12 times more potent inhibitory effects than the kojic acid. Result:: The structure-activity relationship revealed that substituting halogens at the C-4 position of the benzene ring renders remarkable anti-tyrosinase activities. Compounds 1-3 and 8 showed a competitive type of inhibition, while compounds 5, 11, and 15 showed a non-competitive mode of inhibition. Next, we performed molecular docking analyses to study the binding modes and interactions between the ligands (inhibitors) and the active site of the tyrosinase enzyme (receptor). Besides this, we have assessed the toxicity profile of inhibitors on the BJ human fibroblast cell line. Conclusion:: The majority of the newly identified tyrosinase inhibitors were found to be noncytotoxic. The results presented herein form the basis of further studies on triazole derivatives as potential drug leads against tyrosinase-related diseases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".