Exploring the Mechanisms of Indole-Oxadiazole Benzamide Hybrids as Tyrosinase Inhibitors: Insights from Lineweaver-Burk Plot Analysis and Computational Studies
Bibliographic record
Abstract
Abstract Objective: This study aimed to synthesize hybrid compounds incorporating indole, oxadiazole, and benzamide moieties, leveraging their known biological activities, to evaluate their potential as tyrosinase inhibitors. Methods: A convergent synthetic approach was employed to develop the hybrid compounds. Structural confirmation was achieved through infrared spectroscopy (IR), proton nuclear magnetic resonance (1H NMR), carbon nuclear magnetic resonance (13C NMR), and elemental analysis (CHN). The inhibitory effects on tyrosinase were assessed using enzyme kinetics, with Lineweaver-Burk plots utilized to determine the mechanism of inhibition. Results and Discussion: The synthesized bi-heterocyclic benzamides demonstrated excellent inhibitory activities against tyrosinase compared to the standard control. Compound (VIIIf) exhibited non-competitive inhibition, forming an enzyme-inhibitor complex, with an inhibition constant (Ki) of 0.0033 µM. Computational analysis indicated favorable binding energy values for these compounds. The study highlights the promising potential of these hybrid molecules as effective tyrosinase inhibitors. The structure-activity relationship analysis suggests that the incorporation of indole, oxadiazole, and benzamide moieties enhances the inhibitory efficacy against tyrosinase, which is crucial for developing treatments for skin disorders. Conclusions: The synthesized indole-oxadiazole-benzamide hybrids are identified as potent tyrosinase inhibitors with significant potential as medicinal scaffolds for treating skin conditions. Further investigations into their therapeutic applications are warranted.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".