Bibliographic record
Abstract
Coronavirus disease 2019 (COVID-19), the current global pandemic is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Various pharmaceuticals are being developed to counter the spread of the virus. The strategy of repurposing known drugs and bioactive molecules is a rational approach. A previously described molecule, Ile-Arg-Trp (IRW), is a bioactive tripeptide that exhibits an ability to boost angiotensin converting enzyme-2 (ACE2) expression in animals and cells. Given the importance of SARS-CoV-2 S receptor binding domain (RBD)-ACE2 interaction in SARS-CoV-2 pathophysiology, we synthesized various IRW analogs intending to mitigate the RBD-ACE-2 interaction. Herein, we describe two analogs of IRW, A9 (Acetyl-Ile-Arg-Trp-Amide) and A14 (Formyl-Ile-Arg-Trp-Amide) which lowered the SARS-CoV-2 S RBD-ACE2 (at 50 µM) in vitro. The free energy of binding suggested that A9 and A14 interacted with the SARS-CoV-2 S RBD more favorably than ACE2. The calculated MMGBSA ΔG of spike binding for A9 was -57.22 kcal/mol, while that of A14 was -52.44 kcal/mol. A14 also inhibited furin enzymatic activity at various tested concentrations (25, 50, and 100 µM). We confirmed the effect of the two potent analogs using SARS-CoV-2 spike protein overexpressing cells. Both peptides lowered the protein expression of SARS-CoV-2 spike protein at the tested concentration (50 µM). Similarly, both peptides, A9 and A14 (50 µM), also inhibited pseudotyped lentiviral particles with SARS-CoV-2 Spike in ACE2 overexpressing cells. Further, the molecular dynamics (MD) calculations showed the interaction of A9 and A14 with multiple residues in spike S1 RBD. In conclusion, novel peptide analogs of ACE2 boosting IRW were prepared and confirmed through in vitro, cellular, and computational evaluations to be potential seed candidates for SARS-CoV-2 host cell binding inhibition.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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 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".