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An Integrative in silico Drug Repurposing Approach for Identification of Potential Inhibitors of SARS‐CoV‐2 Main Protease
Author(s) -
Djokovic Nemanja,
Ruzic Dusan,
Djikic Teodora,
Cvijic Sandra,
Ignjatovic Jelisaveta,
Ibric Svetlana,
Baralic Katarina,
Buha Djordjevic Aleksandra,
Curcic Marijana,
DjukicCosic Danijela,
Nikolic Katarina
Publication year - 2021
Publication title -
molecular informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.481
H-Index - 68
eISSN - 1868-1751
pISSN - 1868-1743
DOI - 10.1002/minf.202000187
Subject(s) - drug repositioning , in silico , repurposing , context (archaeology) , computational biology , drug , covid-19 , drug discovery , physiologically based pharmacokinetic modelling , drug development , pharmacology , medicine , bioinformatics , biology , pharmacokinetics , gene , infectious disease (medical specialty) , ecology , paleontology , biochemistry , disease , pathology
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.