Synthesis and Antiviral and Antitumor Activities of Novel 18β-Glycyrrhetinic Acid Derivatives
Bibliographic record
Abstract
A series of novel derivatives of 18β-glycyrrhetinic acid (GA) were synthesized by introducing aromatic or heterocyclic structures to extend the side chain, thereby enhancing their interaction with amino acid residues in the active pocket of the target protein. These compounds were structurally characterized using 1H NMR, 13C NMR, and HRMS. The compounds were subsequently evaluated for their inhibitory effects on HIV-1 protease and cell viability in the human cancer cell lines K562 and HeLa and the mouse cancer cell line CT26. Towards HIV-1 protease, compounds 28 and 32, which featured the introduction of heterocyclic moieties at the C3 position of GA, exhibited the highest inhibition, with inhibition rates of 76% and 70.5%, respectively, at 1 mg/mL concentration. Further molecular docking suggests that a 3-substituted polar moiety would be likely to enhance the inhibitory activity against HIV-1 protease. As for the anti-proliferative activities of the GA derivatives, incorporation of a thiazole heterocycle at the C3- position in compound 29 significantly enhanced the effect against K562 cells with an IC50 value of 8.86 ± 0.93 µM. The introduction of electron-withdrawing substituents on the C3-substituted phenyl ring augmented the anti-proliferative activity against Hela and CT26 cells. Compound 13 exhibited the highest inhibitory activity against Hela cells with an IC50 value of 9.89 ± 0.86 µM, whereas compound 7 exerted the strongest inhibition against CT26 cells with an IC50 value of 4.54 ± 0.37 µM. These findings suggest that further modification of GA is a promising path for developing potent novel anti-HIV and anticancer therapeutics.
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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) | 0.001 | 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".