Molecular Docking suggests repurposing of Brincidofovir as a potential drug targeting SARS-CoV-2 "COVID-19" ACE2 receptor and main protease
Bibliographic record
Abstract
Abstract The current outbreak of the highly transmittable and life-threatening treme intense respiratory disorder coronavirus 2 (SARS-CoV-2) has advanced rapidly and posed a global health emergency. Many clinical trials are now being conducted to test possible therapies. To assist, the molecular docking was applied on some selected FDA-approved drugs, previously used in epidemics, and the top ten compounds were selected. These ten well-characterized drugs, previously used to treat Malaria and Ebola infections, were screened based on their interactions with the SARS-CoV-2 ACE2 Receptor and 3C-like Protease. Compared to the other nine medicines, Brincidofovir, an ether lipid ester analog of cidofovir with potent antiviral activity, showed the highest docking scores and binding interactions. Therefore, Brincidofovir worth further investigations and clinical trials as a possible therapeutic agent for the COVID-19 disease .
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".