Density functional theory and enzyme studies support interactions between angiotensin receptor blockers and angiotensin converting enzyme-2: Relevance to coronavirus 2019
Bibliographic record
Abstract
The binding affinities and interactions between eight drug candidates, both commercially available (candesartan; losartan; losartan carboxylic acid; nirmatrelvir; telmisartan) and newly synthesized benzimidazole-N-biphenyltetrazole (ACC519T), benzimidazole bis-N,Nʹ-biphenyltetrazole (ACC519T(2) and 4-butyl-N,N-bis([2-(2H-tetrazol-5-yl)biphenyl-4-yl]) methyl (BV6), and the active site of angiotensin-converting enzyme-2 (ACE2) were evaluated for their potential as inhibitors against SARS-CoV-2 and regulators of ACE2 function through Density Functional Theory methodology and enzyme activity assays, respectively. Notably, telmisartan and ACC519T(2) exhibited pronounced binding affinities, forming strong interactions with ACE2′s active center, favorably accepting proton from the guanidinium group of arginine273. The ordering of candidates by binding affinity and reactivity descriptors, emerged as telmisartan > ACC519T(2) > candesartan > ACC519T > losartan carboxylic acid > BV6 > losartan > nirmatrelvir. Proton transfers among the active center amino acids revealed their interconnectedness, highlighting a chain-like proton transfer involving tyrosine, phenylalanine, and histidine. Furthermore, these candidates revealed their potential antiviral abilities by influencing proton transfer within the ACE2 active site. Furthermore, through an in vitro pharmacological assays we determined that candesartan and the BV6 derivative, 4-butyl-N,N0-bis[20-2Htetrazol-5-yl)bipheyl-4-yl]methyl)imidazolium bromide (BV6(K+)2) also contain the capacity to increase ACE2 functional activity. This comprehensive analysis collectively underscores the promise of these compounds as potential therapeutic agents against SARS-CoV-2 by targeting crucial protein interactions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".