Network Bioinformatics Analysis Provides Insight into Drug Repurposing for COVID-2019

Abstract

The COVID-2019 disease caused by the SARS-CoV-2 virus (aka 2019-nCoV) has raised significant health concerns in China and worldwide. While novel drug discovery and vaccine studies are long, repurposing old drugs against the COVID-2019 epidemic can help identify treatments, with known preclinical, pharmacokinetic, pharmacodynamic, and toxicity profiles, which can rapidly enter Phase 3 or 4 or can be used directly in clinical settings. In this study, we presented a novel network based drug repurposing platform to identify potential drugs for the treatment of COVID-2019. We first analysed the genome sequence of SARS-CoV-2 and identified SARS as the closest disease, based on genome similarity between both causal viruses, followed by MERS and other human coronavirus diseases. Using our AutoSeed pipeline (text mining and database searches), we obtained 34 COVID-2019-related genes. Taking those genes as seeds, we automatically built a molecular network for which our module detection and drug prioritization algorithms identified 24 disease-related human pathways, five modules and finally suggested 78 drugs to repurpose. Following manual filtering based on clinical knowledge, we re-prioritized 30 potential repurposable drugs against COVID-2019 (including pseudoephedrine, andrographolide, chloroquine, abacavir, and thalidomide) . We hope that this data can provide critical insights into SARS-CoV-2 biology and help design rapid clinical trials of treatments against COVID-2019.

Growth factor receptor signaling inhibition prevents SARS-CoV-2 replication

“…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…”

Novel Coronavirus: Current Understanding of Clinical Features, Diagnosis, Pathogenesis, and Treatment Options

“…One method for effectively selecting drugs for repurposing purposes is the use of bioinformatics to analyze the interactions of drugs with the proteins of the target organism, in this case SARS-CoV-2. Bioinformatics was recently used to identify drugs that could target SARS-CoV-2 and 78 drugs were identified as possible repurposed drugs [52]. After refining the list of drugs by removing drugs found unfit for repurposing, based on the effects of the drugs on the symptoms of SARS-CoV-2, and their side effects, 30 drugs were identified [52].…”

“…Bioinformatics was recently used to identify drugs that could target SARS-CoV-2 and 78 drugs were identified as possible repurposed drugs [52]. After refining the list of drugs by removing drugs found unfit for repurposing, based on the effects of the drugs on the symptoms of SARS-CoV-2, and their side effects, 30 drugs were identified [52]. Pseudoephedrine, andrographolide, atiprimod, YSIL6, tapinarof, etanercept, adalimumab, infliximab, chloroquine, epinephrine, thalidomide, clenbuterol, pranlukast, afelimomab, golimumab, siltuximab, olsalazine, ibalizumab, cefazolin, abacavir, myricetin, N-formylmethionine, ruplizumab, framycetin, ketoprofen, maraviroc, vicriviroc, proline, quercetin and artenimol are the 30 drugs that were identified as possible drugs to repurpose for use against SARS-CoV-2.…”

Differential expression of COVID-19-related genes in European Americans and African Americans

“…We drew from in silico studies 48 and experimental analyses especially human responses to infection by SARS-CoV-2 and other coronaviruses [49][50][51][52] to identify ten genes implicated in cellular responses to SARS-CoV-2 infection that are among those differentially expressed in African American and European American populations. Molecular functions of these genes include receptor kinases, cytokines, other signal transduction molecules, and antioxidants.…”

“…We focus on the differential expression of genes implicated in response to SARS-CoV-2 infection, drawing from in silico studies 48 and experimental analyses especially human responses to infection by SARS-CoV-2 and other coronaviruses [49][50][51][52] . , KS test significant (p-value ă 0.05);˚, Mann--Whitney U test significant (BH corrected p-value ă 0.05).…”