2020
DOI: 10.26434/chemrxiv.11875446
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Fast Identification of Possible Drug Treatment of Coronavirus Disease -19 (COVID-19) Through Computational Drug Repurposing Study

Abstract: The recent outbreak of novel coronavirus disease -19 (COVID-19) calls for and welcomes possible treatment strategies using drugs on the market. It is very efficient to apply computer-aided drug design techniques to quickly identify promising drug repurposing candidates, especially after the detailed 3D-structures of key virous proteins are resolved. Taking the advantage of a recently released crystal structure of COVID-19 protease in complex with a covalently-bonded inhibitor, N3, 1 I conducted virtual docking… Show more

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Cited by 129 publications
(172 citation statements)
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“…A number of drugs to treat COVID-19 have been suggested, largely based on bioinformatics analyses of genetics or cellular data (Gordon et al, 2020;Li et al, 2020;Wang, 2020). However, for many of these compounds, studies explaining their working mechanisms in the context of SARS-CoV-2 or viral assays to determine their efficacy of blocking viral replication in cell models 230…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…A number of drugs to treat COVID-19 have been suggested, largely based on bioinformatics analyses of genetics or cellular data (Gordon et al, 2020;Li et al, 2020;Wang, 2020). However, for many of these compounds, studies explaining their working mechanisms in the context of SARS-CoV-2 or viral assays to determine their efficacy of blocking viral replication in cell models 230…”
Section: Discussionmentioning
confidence: 99%
“…Thus, repurposing of already available and (ideally) approved drugs might be essential to rapidly treat COVID-19. Many studies for proposing repurposing of specific drugs have been conducted in the last months, but mostly remain computational without tests in infection models (Smith and Smith, 2020;Wang, 2020). In addition, they are hindered by the lack of knowledge about the molecular 40 mechanisms of SARS-CoV-2 infection and the resulting host-cell responses required to allow viral replication.…”
Section: Introductionmentioning
confidence: 99%
“…Next, in our study, the binding affinity of a-ketoamide was further evaluated and compared with the FDA approved anti-HIV protease inhibitors, such as lopinavir and darunavir, which has been reported as potent drugs against 3CL pro of SARS-CoV-2. Recently, the molecular recognition of lopinavir by the COVID-19 3CL pro has been investigated using the MMPBSA scheme (Wang, 2020), and the binding free energy of lopinavir was found to be lesser (-6.63 kcal/mol) than a-ketoamide (-9.05 kcal/mol) (see Table 2). It is further revealed that the electrostatic interaction (-52.46 kcal/mol) favored the complex formation more compared to the van der Waals interactions (-20.09 kcal/mol).…”
Section: Binding Free Energy Analysismentioning
confidence: 99%
“…The availability of the crystal structure of 3CL pro opens up a lot of opportunities to develop new antiviral drugs. This structure is employed to computationally evaluate the repurposing of different FDA approved drugs against COVID-19 (Das, Sarmah, Lyndem & Singha Roy 2020;Islam et al, 2020;Joshi et al, 2020;Wang, 2020). Several studies have predicted the binding strength of darunavir, indinavir, like other HIV protease drugs and some other small molecules against 3CL pro (Alamri et al, 2020;Abdelli et al, 2020;Lin et al, 2020;Muralidharan et al, 2020;Sang et al, 2020;Sarma et al, 2020;Umesh et al, 2020;Wahedi et al, 2020).…”
Section: Introductionmentioning
confidence: 99%
“…Repurposing drugs is a much quicker endeavor than discovering new ones since their chemical optimization, toxicology profiling, clinical trials and bulk manufacturing are already in place [1]. Several research groups have already proposed possible candidates for testing [2][3][4][5][6][7]. The results of this testing could provide a spectrum of outcomes -ranging from a compound that show high promise for use in patient treatment to very little activity.…”
Section: Introductionmentioning
confidence: 99%