Biginelli dihydropyrimidines and their acetylated derivatives as L‐/T‐type calcium channel blockers: Synthesis, enantioseparation, and molecular modeling studies
Bibliographic record
Abstract
Abstract Biginelli dihydropyrimidines (DHPMs) are considered superior over 1,4‐dihydropyridines (DHPs) in terms of both light and metabolic stabilities. Nevertheless, DHPs dominate the market as the most prescribed calcium channel blockers with strong therapeutic potential in managing cardiovascular ailments. To overcome the restrictions that complicate the formulation and postadministration of DHPs, employing bioisosteric replacement by exchanging the DHP ring with DHPM appears as a logical approach for the improved formulations of new calcium channel blockers. In this study, we obtained DHPM derivatives via Biginelli synthesis and acetylated their N‐3 position by heating them in acetic anhydride (GD1–GD12). We also incorporated the DHPM scaffold into a condensed ring system (GD13 and GD14). These DHPMs were evaluated for their ability to block both L‐ (Cav1.2) and T‐ (Cav3.2) type calcium channels. Compounds carrying acetyl moiety on the N‐3 position of the DHPM scaffold appeared to be more effective inhibitors of both channels. Retesting GD4 enantiomers, separated using high‐performance liquid chromatography (HPLC) on a chiral stationary phase, revealed that the (R)‐isomer predominantly contributes to the outstanding inhibitory activity of GD4 on calcium channels. Molecular modeling studies, including docking, molecular dynamics simulations, and dynophore analysis, provided insights into the binding mechanism of DHPMs to Cav1.2 and Cav3.2, for the first time.
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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".