In silico identification of widely used and well-tolerated drugs as potential SARS-CoV-2 3C-like protease and viral RNA-dependent RNA polymerase inhibitors for direct use in clinical trials

Abstract

<p></p><p>Despite strict measures taken by many countries, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to be an issue of global concern. Currently, there are no clinically proven pharmacotherapies for coronavirus disease 2019, despite promising initial results obtained from drugs such as azithromycin and hydroxyquinoline. Therefore, the repurposing of clinically approved drugs for use against SARS-CoV-2 has become a viable strategy. Here, we searched for drugs that target SARS-CoV-2 3C-like protease (3CL<sup>pro</sup>) and viral RNA-dependent RNA polymerase (RdRp) by in silico screening of the U.S. Food and Drug Administration approved drug library. Well-tolerated and widely used drugs were selected for molecular dynamics (MD) simulations to evaluate drug-protein interactions and their persistence under physiological conditions. Tetracycline, dihydroergotamine, ergotamine, dutasteride, nelfinavir, and paliperidone formed stable interactions with 3CL<sup>pro</sup> based on MD simulation results. Similar analysis with RdRp showed that eltrombopag, tipranavir, ergotamine, and conivaptan bound to the enzyme with high binding free energies. Docking results suggest that ergotamine, dihydroergotamine, bromocriptine, dutasteride, conivaptan, paliperidone, and tipranavir can bind to both enzymes with high affinity. As these drugs are well tolerated, cost-effective, and widely used, our study suggests that they could potentially to be used in clinical trials for the treatment of SARS-CoV-2-infected patients.</p><br><p></p>

An in-silico study on selected organosulfur compounds as potential drugs for SARS-CoV-2 infection via binding multiple drug targets

“…No. Compound name Binding energy (kcal/mol) against SARS-CoV-2 proteins Mpro [24] (6Y84) PLpro [25] (6W9C) Spro [26] (6LZG) RdRp [27] (6M71) Helicase * [28] (6JYT/6ZSL) 1 Metacycline -9.1 2 Dutasteride -8.9 -9.9 # 3 Dihydroergotamine -8.6 -9.3 # 4 Nelfinavir -8.6 5 Tetracycline -8.1 6 Cryptophycin 1 -7.7 7 Cryptophycin 52 -8.3 ** -7.6 8 Deoxycylindrospermopsin -8.6 ** -7.9 9 Famotidine -6.0 ## -7.9 -6.8 ## -5.9 ## 10 Tegobuvir -8.1 11 Bromocriptin -7.7 12 Baicalin -7.6 13 Deleobuvir -7.6 14 Dantrolene -7.6 ...…”

In Silico Drug Repositioning Against Human NRP1 to Block SARS-CoV-2 Host Entry

“…A To discover an antiviral drug diverse targets are available from viral replication enzymes to host proteins facilitating the virus entry and to proteins responsible for the virus release (Boopathi et al, 2020;Lo et al, 2020;Wu C and Zheng M, 2020). Several in silico and in vivo drug repurposing studies are carried out using proteases (3CL pro and PL pro ) and RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 as targets (Bharadwaj et al, 2020;Ghosh et al, 2020;Gul et al, 2020;Li et al, 2020c;Wang, 2020). In addition, host proteins TMPRSS2 and ACE2 which primes protein S and mediates SARS-CoV-2 entry to host, respectively, are targeted for drug repositioning as well (Bagheri and Niavarani, 2020;Busnadiego et al, 2020;Carino et al, 2020;Choudhary et al, 2020;Durdagi, 2020;Kumar et al, 2020;Singh et al, 2020b).…”

“…During the MD simulations interacting residues of EG01377 and eltrombopag with NRP1 are very similar to each other ( Figure 4B). A previous drug-repurposing study against 3CL pro and RdRp of SARS-CoV-2 from our group showed that eltrombopag may bind to the active site of 3CL pro and nsp8 binding site of RdRp which may attenuate the virus activity (Gul et al, 2020). Eltrombopag exhibits in vitro antiviral properties with IC50 lower than 10µM (Jeon et al, 2020).…”

“…High-resolution human NRP1 structure (PDB ID: 6FMC) was retrieved from The Protein Data Bank (www.rcsb.org) (Powell et al, 2018). Protein was prepared for docking simulations via Dock Prep module of UCSF Chimera as described previously (Doruk et al, 2020;Gul et al, 2020;Tardu et al, 2016). Water molecules were removed and if alternate locations are available for residues, the ones with the higher occupancies were selected.…”

“…AutoDock Vina program was used to calculate binding energy and predict the binding mode of drugs to the target pocket as described before (Gul et al, 2020;Tardu et al, 2016). During the docking simulations, receptor (NRP1) was treated as a rigid body and drugs were allowed to sample different conformations in the CendR binding pocket.…”