Molecular Docking Reveals Ivermectin and Remdesivir as Potential Repurposed Drugs Against SARS-CoV-2
SARS-CoV-2 is a newly emerged coronavirus that causes a respiratory disease with variable severity and fatal consequences. It was first reported in Wuhan and subsequently caused a global pandemic. The viral spike protein binds with the ACE-2 cell surface receptor for entry, while TMPRSS2 triggers its membrane fusion. In addition, RNA dependent RNA polymerase (RdRp), 3′–5′ exoribonuclease (nsp14), viral proteases, N, and M proteins are important in different stages of viral replication. Accordingly, they are attractive targets for different antiviral therapeutic agents. Although many antiviral agents have been used in different clinical trials and included in different treatment protocols, the mode of action against SARS-CoV-2 is still not fully understood. Different potential repurposed drugs, including, chloroquine, hydroxychloroquine, ivermectin, remdesivir, and favipiravir, were screened in the present study. Molecular docking of these drugs with different SARS-CoV-2 target proteins, including spike and membrane proteins, RdRp, nucleoproteins, viral proteases, and nsp14, was performed. Moreover, the binding affinities of the human ACE-2 receptor and TMPRSS2 to the different drugs were evaluated. Molecular dynamics simulation and MM-PBSA calculation were also conducted. Ivermectin and remdesivir were found to be the most promising drugs. Our results suggest that both these drugs utilize different mechanisms at the entry and post-entry stages and could be considered potential inhibitors of SARS-CoV-2 replication.
SARS-CoV-2 emerged in 2019 as the causative agent of a pneumonia outbreak in Wuhan, Hubei Province, China (Zhu et al., 2020). The disease outbreak spread globally, causing a pandemic with dozens of millions laboratory-confirmed cases (WHO, 2020) with more folds of the infections could be passed undetected (Hosein et al., 2020). The disease has resulted in more than 1,500,000 deaths as of 12 December 2020 (WHO, 2020).
SARS-CoV-2 belongs to the subgenus Sarbecovirus, genus Betacoronavirus and family Coronaviridae. The virus uses the angiotensin-converting enzyme 2 (ACE-2) cell receptor to enter cells (Hoffmann et al., 2020). The SARS-CoV-2 genome consists of ∼29.8 kb nucleotides; it possesses 14 open reading frames (ORFs) encoding 27 proteins (Wu A. et al., 2020). The 5′ two-thirds of the viral genome encodes the replicase gene. It contains two ORFs: ORF1a and ORF1b. ORF1a/b encodes two polyproteins by polymerase frameshifting; these are then post-translationally cleaved into 15 non-structural proteins (nsps): nsp1–10 and nsp12–16. The rest of the genome encodes four structural proteins [spike protein (S protein), envelope protein (E protein), membrane protein (M protein), and nucleocapsid protein (N protein)], in addition to eight accessory proteins (3a/3b, p6, 7a/7b, 8b, 9b, and ORF14) (Wu A. et al., 2020).
The S protein is proteolytically cleaved by type-II transmembrane serine protease (TMPRSS2) into S1 and S2 subunits (Hoffmann et al., 2020). The former subunit binds to the host cell surface receptor, while the latter is responsible for the fusion of the viral envelope and the cell membrane. The M protein is one of the most abundant envelope proteins. It plays an important role in determining the morphology of the virus. The E protein is present in a small amount on the envelope; however, it is important for the assembly and release of the virus. The N protein binds to the viral genome and forms the nucleocapsid of the virus (Abdel-Moneim and Abdelwhab, 2020). The replicase proteins encode the papain-like protease (PLpro) and the serine-type protease or main protease (Mpro) (Ziebuhr et al., 2000; Mielech et al., 2014). In addition, many other nsps, including RNA-dependent RNA polymerase (RdRp; nsp12) (Xu et al., 2003), RNA helicase (nsp13) (Ivanov et al., 2004), N7 MTase and 3′–5′ exoribonuclease (nsp14) (Eckerle et al., 2010), form the replicase–transcriptase complex (RTC), which is essential for RNA replication and transcription. The accessory proteins are also involved in viral replication and pathogenesis (Zhao et al., 2012; Fehr and Perlman, 2015).
Protein Retrieval and Preparation
The 3D structures of recently identified SARS-CoV-2 proteins, namely the S glycoprotein (PDB ID = 6VXX) (Walls et al., 2020), RdRp (PDB ID = 67M1) (Gao et al., 2020), Mpro (PDB ID = 6Y2E) (Zhang et al., 2020), PLpro (PDB ID = 6W9C) (Osipiuk et al., 2020), and the N protein (PDB ID = 6VYO) (Kang et al., 2020), were obtained from the RCSB Protein Data Bank1. On the other hand, the 3D structure of the viral M protein was not available; therefore, structural protein sequences of SARS-CoV-2 were downloaded from the NCBI Protein database (Accession No. QJA17755). Homology modeling of the viral proteins was performed using the SWISS-MODEL server2 with default settings. The M protein sequence of SARS-CoV-2 was entered in FASTA format, and the 3D homology model was retrieved from the SWISS-MODEL server as a PDB file and used for the docking process. Similarly, because of the lack of experimental 3D structure of the non-structural protein Nsp14 the sequence of SARS-CoV-2 ExoN/nsp14 (P0DTD1) was used to build a 3D homology model in the SWISS-MODEL web server based on the x-ray structure of Nsp14 from SARS-CoV (PDB ID: 5C8S, chain B) (Gurung, 2020).
The 3D structure of human ACE-2 was downloaded from the RCSB Protein Data Bank (see text footnote 1) (PDB ID = 1R42). However, 3D x-ray crystallographic data of TMPRSS2 were not available; therefore, the sequence of human TMPRSS2 (O15393) was retrieved from UniProt (UniProt Consortium, 2019), and loaded into the SWISS-MODEL server (see text footnote 2) with default settings to create three different 3D homology models of the protein. The top-ranked homology model built using the serine protease hepsin as the template (PDB ID = 5CE1) was subjected to protein preparation and optimization using the default protein preparation protocol in the Molegro Virtual Docker (MVD) software. Finally, the verified homology model of TMPRSS2 with good quality was used for molecular docking studies.
The 3D protein structures of all the proteins being studied were loaded onto the MVD 6.0 (2013) platform for the docking process. Potential binding sites (referred to as cavities) were identified using the built-in cavity detection algorithm of MVD. For each PDB file, protein preparation was performed using the default parameters in MVD before conducting the docking experiment. Subsequently, the docking process between different ligands and active sites of different protein structures was performed using the MolDock score as the scoring function of MVD with a grid resolution of 0.30 Å. The number of runs for each docking process was 10. Moreover, the maximum iterations were 2000, with an energy threshold of 100 Kcal/mol. The best conformations for each docking process were selected on the basis of the lowest docked binding energy.
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