In silico Drug Repurposing for COVID‐19: Targeting SARS‐CoV‐2 Proteins through Docking and Consensus Ranking

Abstract

In December 2019, an infectious disease caused by the coronavirus SARS-CoV-2 appeared in Wuhan, China. This disease (COVID-19) spread rapidly worldwide, and on March 2020 was declared a pandemic by the World Health Organization (WHO). Today, over 21 million people have been infected, with more than 750.000 casualties. Today, no vaccine or antiviral drug is available. While the development of a vaccine might take at least a year, and for a novel drug, even longer; finding a new use to an old drug (drug repurposing) could be the most effective strategy. We present a docking-based screening using a quantum mechanical scoring of a library built from approved drugs and compounds undergoing clinical trials, against three SARS-CoV-2 target proteins: the spike or S-protein, and two proteases, the main protease and the papain-like protease. The S-protein binds directly to the Angiotensin Converting Enzyme 2 receptor of the human host cell surface, while the two proteases process viral polyproteins. Following the analysis of our structure-based compound screening, we propose several structurally diverse compounds (either FDA-approved or in clinical trials) that could display antiviral activity against SARS-CoV-2. Clearly, these compounds should be further evaluated in experimental assays and clinical trials to confirm their actual activity against the disease. We hope that these findings may contribute to the rational drug design against COVID-19.

Drug Design and Repurposing with DockThor-VS Web Server: Virtual Screening focusing on SARS-CoV-2 Therapeutic Targets and their Non-Synonym Variants

“…We believe that the DockThor-VS web server is an excellent alternative for the development of drug repositioning research against COVID-19, not only for constructing drug libraries and therapeutic target structures available through the webserver, but also for allowing studies involving new targets structures provided by the users and virtual screening experiments involving in-house ligand libraries. Moreover, the results obtained using the docking methodologies provided by DockThor-VS can be used in conjunction with the results of other docking programs in methodological approaches known in the literature as consensus scoring 99 and consensus ranking 16 . The DockThor-VS web server is freely available at www.dockthor.lncc.br and utilizes the computational facilities of the Brazilian high-performance platform and the supercomputer SDumont (https://sdumont.lncc.br/).…”

“…The estimated mutation rate underlying the global diversity of SARS-CoV-2 is approximately 6×10 −4 nucleotides/genome/year 62 , which is considered moderate for coronaviruses that have the Nsp14 proofreading correction mechanism. Currently, the genomic analysis of more than 55 thousand circulating genomes from patient samples showed that there are more than 16 NSVs with low alleles frequency (~11% to 0.002%). Ultimately, this can be explained by the positive selection that acts at a higher rate after the zoonotic transfer, suggesting an increasing mutant load in the circulating strains of SARS-CoV-2 in the epidemiological scenario 64 .…”

Essential interpretations of bioinformatics in COVID-19 pandemic

“…The potentiality of CADD has been exploited to the fullest in finding a solution for this COVID-19 outbreak. Researchers have taken the privilege of CADD including structure-based drug design, network-based drug design towards the identification of potential drug candidates against the identified viral proteins including Spike (S) protein ( Prasanth et al, 2020 ; Hall Jr and Ji, 2020 ; Wei et al, 2020 ; Fantini et al, 2020 ; BR et al, 2020 ; Cavasotto and Di Filippo, 2020 ; Vardhan and Sahoo, 2020 ; Panda et al, 2020 ), Nucleocapsid (N) protein ( Sarma et al, 2020 ; Ray et al, 2020a ; Bhowmik et al, 2020 ; Lavecchia and Fernandez, 2020 ), Envelop protein ( Bhowmik et al, 2020 ; Lavecchia and Fernandez, 2020 ; Gupta et al, 2020 ), Membrane (M) Protein ( Bhowmik et al, 2020 ), Main protease (M pro) ( Prasanth et al, 2020 ; Cavasotto and Di Filippo, 2020 ; Vardhan and Sahoo, 2020 ; Panda et al, 2020 ; Kumar et al, 2020 ), 3CL protease ( Hall Jr and Ji, 2020 ; Vardhan and Sahoo, 2020 ; Jo et al, 2020 ) of SARS-CoV-2 by using the bioinformatics tools and software ( Table 6 ). This immediate and effective action has not only predicted novel putative natural inhibitors but also re-experimented some previously used ancient synthetic drugs with antiviral activities like chloroquine (malaria), hydroxylchloroquine (maalaria), zanamivir (influenza A & B virus), indinavir (HIV), saquinavir (HIV), remdesivir (SARS-CoV), ralterravin (HIV), strptomycine, ciprofloxacin, zanamivir (influenza virus), glycyrrhizic acid (anti inflammation) etc.…”

Identification of naphthyridine and quinoline derivatives as potential Nsp16-Nsp10 inhibitors: a pharmacoinformatics study

“…The above observations strongly suggested that Nsp16-Nsp10 may be a crucial drug target for highly specific anti-coronavirus drugs in comparison to the viral MTase active site (Rosas-Lemus et al, 2020). Several interesting studies have already been done by considering Nsp16-Nsp10 as an effective drug target for SARS-CoV-2 inhibition (Cavasotto & Di Filippo, 2020;Culletta et al, 2020;Kadioglu et al, 2020;Kandwal & Fayne, 2020;Tazikeh-Lemeski et al, 2020).…”