Abstract
Since the inception of COVID-19 pandemic in December 2019, socio-economic crisis begins to rise globally and SARS-CoV-2 was responsible for this outbreak. With this outbreak, currently, world is in need of effective and safe eradication of COVID-19. Hence, in this study anti-SAR-Co-2 potential of FDA approved marine drugs (Biological macromolecules) data set is explored computationally using machine learning algorithm of Flare by Cresset Group, Field template, 3D-QSAR and activity Atlas model was generated against FDA approved M-pro SARS-CoV-2 repurposed drugs including Nafamostat, Hydroxyprogesterone caporate, and Camostat mesylate. Data sets were categorized into active and inactive molecules on the basis of their structural and biological resemblance with repurposed COVID-19 drugs. Then these active compounds were docked against the five different M-pro proteins co-crystal structures. Highest LF VS score of Holichondrin B against all main protease co-crystal structures ranked it as lead drug. Finally, this new technique of drug repurposing remained efficient to explore the anti-SARS-CoV-2 potential of FDA approved marine drugs.
Keywords: Activity atlas model; Activity cliff; COVID-19; Field template; Holichondrin B; Marine drugs.
【저자키워드】 COVID-19, Marine drugs., Holichondrin B, Field template, Activity cliff, Activity atlas model, 【초록키워드】 Structure, SARS-CoV-2, COVID-19 pandemic, drugs, drug, protease, FDA, anti-SARS-CoV-2, activity, Repurposed drug, Protein, outbreak, Algorithm, nafamostat, camostat, group, macromolecules, structures, Biological, Safe, data set, Compound, flare, field, FIVE, effective, responsible, remained, approved, inactive, Atla, Cresset, docked, 【제목키워드】 drug, protease, FDA, anti-SARS-CoV-2, Predictive, approved,