DFT, Molecular Docking, and ADME/Tox Screening Investigations of Market‑Available Drugs against SARS‑CoV‑2
Bibliographic record
Abstract
A series of drugs was investigated to determine structural, electronic and pharmacological properties, as well as the molecular affinity for the main protease of severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2). The drugs were submitted to density functional theory calculations to optimize structures and predict binding preferences. The optimized geometries were used in molecular docking simulations. In the docking study, the receiver was considered rigid and the drugs flexible. The Lamarckian genetic algorithm with global search and Pseudo-Solis and Wets with local search were adopted for docking. Absorption, distribution, metabolism, excretion and toxicological properties were obtained from the Pre-ADMET online server. In this series, the antiviral atazanavir showed the potential to inhibit the main protease of SARS‑CoV‑2, based on the free binding energy, inhibition constant, binding interactions and its favorable pharmacological properties. Therefore, we recommend carrying out further studies with in vitro tests and subsequent clinical tests to analyze its effectiveness in the treatment of SARS‑CoV‑2.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".