Novel benzimidazole angiotensin receptor blockers with anti-SARS-CoV-2 activity equipotent to that of nirmatrelvir: computational and enzymatic studies
Bibliographic record
Abstract
BACKGROUND: Hypertension worsens outcomes in SARS-CoV-2 patients. Sartans, a type of antihypertensive angiotensin receptor blocker-(ARB), reduce COVID-19 morbidity and mortality by targeting angiotensin-converting enzyme-2 (ACE2). This study aimed to evaluate the antiviral and antihypertensive effects of nirmatrelvir, commercial sartans (candesartan, losartan, and losartan carboxylic (Exp3174)), and newly synthesized sartans (benzimidazole-N-biphenyl carboxyl (ACC519C) and benzimidazole-N-biphenyl tetrazole (ACC519T)), compared to nirmatrelvir, the antiviral component of Paxlovid. RESEARCH DESIGN AND METHODS: Surface plasmon resonance (SPR) and enzymatic studies assessed drug effects on ACE2. Antiviral abilities were tested with SARS-CoV-2-infected Vero E6 cells, and antihypertensive effects were evaluated using angiotensin II-contracted rabbit iliac arteries. RESULTS: Benzimidazole-based candesartan and ACC519C showed antiviral activity comparable to nirmatrelvir (95% inhibition). Imidazole-based losartan, Exp3174, and ACC519T were less potent (75%-80% and 50%, respectively), with Exp3174 being the least effective. SPR analysis indicated high sartans-ACE2 binding affinity. Candesartan and nirmatrelvir combined had greater inhibitory and cytopathic effects (3.96%) than individually (6.10% and 5.08%). ACE2 enzymatic assays showed varying effects of novel sartans on ACE2. ACC519T significantly reduced angiotensin II-mediated contraction, unlike nirmatrelvir and ACC519T(2). CONCLUSION: This study reports the discovery of a new class of benzimidazole-based sartans that significantly inhibit SARS-CoV-2, likely due to their interaction with ACE2.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".