Plant-Based Bioactive Phthalates Derived from<i>Hibiscus rosa-sinensis</i>: As In Vitro and In Silico Enzyme Inhibition
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Hibiscus rosa-sinensis is an attractive, ever-blossoming, and effortlessly available plant around the globe. The fabulous flowers of H. rosa-sinensis enjoy a significant status in folk medicine throughout the world and comprise a range of phyto constituents due to which this splendid flower owns numerous biological and pharmaceutical activities like antioxidant, antifungal, antimicrobial, anti-inflammatory, antipyretic, antidiabetic, and antifertility activity. Considering this, column chromatographic isolation of the phytoconstituents of ethyl acetate fraction of the flowers of H. rosa-sinensis was performed. A series of five phthalates including Di- n -octyl phthalate ( HR1 ), ditridecyl phthalate ( HR2 ), 1-allyl 2-ethyl phthalate ( HR3 ), diethyl phthalate ( HR4 ), and bis (6-methylheptyl) phthalate ( HR5 ) were isolated. The structures of the isolated phthalates were elucidated by gas chromatography–mass spectrometry, 1 H NMR, and 13 C NMR. In silico and in vitro antidiabetic and antioxidant potential and DFT studies of isolated phthalates were carried out. In our study, isolated ligands were explored as potent antidiabetic as well as antioxidant agents as they exhibited good binding affinity (in in vitro and in silico experiments) against all selected protein targets. Compounds HR1–HR5 showed that the binding affinity value ranged from −5.9 to −5.2 kcal/mol, −5.5 to −4.3 kcal/mol, and −5.0 to −4.1 kcal/mol for target proteins 1HNY, 2I3Y, and 5O40, respectively. Among all isolated phthalates, HR5 can be a lead compound as it showed the best binding affinity with human pancreatic α-amylase (Δ G = −5.9 kcal/mol) and displayed a minimum inhibition concentration (IC 50 ) of 11.69 μM among all phthalates. Compound HR1 was the best docked and scored compound for inhibiting glutathione peroxidase; however, HR2 possessed the lowest binding score of −5.0 kcal/mol, thus indicating the highest potential among isolated phthalates for inhibiting the superoxide dismutase. Furthermore, the top-ranked docked ligand–protein complex for each protein was assessed for stability of protein and complex mobility by molecular dynamics simulation using the IMOD server.
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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) | 0.002 | 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".