Abstract
Considering the urgent need for novel therapeutics in ongoing COVID-19 pandemic, drug repurposing approach might offer rapid solutions comparing to de novo drug design. In this study, we designed an integrative in silico drug repurposing approach for rapid selection of potential candidates against SARS-CoV-2 Main Protease (M pro ). To screen FDA-approved drugs, we implemented structure-based molecular modelling techniques, physiologically-based pharmacokinetic (PBPK) modelling of drugs disposition and data mining analysis of drug-gene-COVID-19 association. Through presented approach, we selected the most promising FDA approved drugs for further COVID-19 drug development campaigns and analysed them in context of available experimental data. To the best of our knowledge, this is unique in silico study which integrates structure-based molecular modeling of M pro inhibitors with predictions of their tissue disposition, drug-gene-COVID-19 associations and prediction of pleiotropic effects of selected candidates.
Keywords: COVID-19; PBPK modeling; drug repurposing; drug-gene-disease associations; pleiotropic effects.
【저자키워드】 COVID-19, Drug repurposing, PBPK modeling, drug-gene-disease associations, pleiotropic effects., 【초록키워드】 Drug repurposing, SARS-CoV-2, drug design, knowledge, COVID-19 pandemic, drug, in silico, FDA-approved drugs, SARS-CoV-2 main protease, FDA approved drug, molecular, inhibitor, association, pharmacokinetic, Pleiotropic effects, Analysis, best, Candidates, tissue, M pro, candidate, de novo, offer, approach, selected, analysed, unique, pleiotropic effect, 【제목키워드】 SARS-CoV-2, repurposing, drug, in silico, identification, Potential,