Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2

Abstract

Human coronaviruses (HCoVs), including severe acute respiratory syndrome coronavirus (SARS-CoV) and 2019 novel coronavirus (2019-nCoV, also known as SARS-CoV-2), lead global epidemics with high morbidity and mortality. However, there are currently no effective drugs targeting 2019-nCoV/SARS-CoV-2. Drug repurposing, representing as an effective drug discovery strategy from existing drugs, could shorten the time and reduce the cost compared to de novo drug discovery. In this study, we present an integrative, antiviral drug repurposing methodology implementing a systems pharmacology-based network medicine platform, quantifying the interplay between the HCoV-host interactome and drug targets in the human protein-protein interaction network. Phylogenetic analyses of 15 HCoV whole genomes reveal that 2019-nCoV/SARS-CoV-2 shares the highest nucleotide sequence identity with SARS-CoV (79.7%). Specifically, the envelope and nucleocapsid proteins of 2019-nCoV/SARS-CoV-2 are two evolutionarily conserved regions, having the sequence identities of 96% and 89.6%, respectively, compared to SARS-CoV. Using network proximity analyses of drug targets and HCoV-host interactions in the human interactome, we prioritize 16 potential anti-HCoV repurposable drugs (e.g., melatonin, mercaptopurine, and sirolimus) that are further validated by enrichment analyses of drug-gene signatures and HCoV-induced transcriptomics data in human cell lines. We further identify three potential drug combinations (e.g., sirolimus plus dactinomycin, mercaptopurine plus melatonin, and toremifene plus emodin) captured by the "Complementary Exposure" pattern: the targets of the drugs both hit the HCoV-host subnetwork, but target separate neighborhoods in the human interactome network. In summary, this study offers powerful network-based methodologies for rapid identification of candidate repurposable drugs and potential drug combinations targeting 2019-nCoV/SARS-CoV-2.

Comparative genomics suggests limited variability and similar evolutionary patterns between major clades of SARS-CoV-2

“…A total of 1113 complete, high quality SARS-CoV-2 genomic sequences, as well as of 2 SARS-CoV-2 like viruses isolated from non-human hosts (bats and pangolins (Zhou et al 2020, Matthew et al 2020, were retrieved from the GISAID EpiCoV portal on March 24th 2020. Associated metadata ( Supplementary Table S1) show that these isolates included in cover more than 45 countries in 5 continents.…”

“…The SARS-CoV-2 pandemic (Poon and Peiris, 2020) poses the greatest global health and socioeconomic threat since the second world war. Complete genomic sequences of viral isolates from diverse geographic sites, have rapidly been made available through dedicated resources (Shu andMcCauley, 2017, Goodacre et al,2018) facilitating comparative genomics studies, identification of putative therapeutic targets (Zhou et al, 2020, Chen et al 2020, Robson 2020) and the development of effective prevention and monitoring strategies (Qiang et al 2020). Analyses of available genomic sequences, according to GISAID EpiCoV, suggest major viral clades, S, V and G which, collectively, circumscribe more than 69% of the characterised isolates.…”

Cancer patients and research during COVID-19 pandemic: A systematic review of current evidence

“…Moreover, a group of researchers used network proximity analyses of drug targets and virushost interactions in the human interactome to identify repurposable drugs and potential drug combinations for the treatment of SARS-CoV-2. Three combinations were deemed effective: sirolimus plus dactinomycin, mercaptopurine plus melatonin, and toremifene plus emodin, all of which consisting of at least one anti-cancer agent (an immunosuppressant, an antineoplastic agent and a selective estrogen receptor modulator respectively) (11).…”

Boosting the arsenal against COVID-19 through computational drug repurposing

“…The number of studies on in silico drug repurposing against COVID-19 is growing rapidly -among others, worth citing is an interesting approach generating a systems-pharmacology-based network medicine platform that identified the interplay between the HCoV-host interactome and drug targets in the human protein-protein interaction network and that has identified potential drug repurposing treatments against such interactions [6]. Moreover, a virtual screening approach was used to investigate the FDA-approved LOPAC library and to predict drugs able to minimize the interaction between the viral spike (S)-protein and ACE2 host cell receptor [7]; in an additional report, a novel deep learning platform was used to identify top potential inhibitors of the SARS-CoV-2 main protease by screening 1.3 billion compounds [8].…”