Examples of PPI network-based analysis for COVID-19.
| Study | Cava et al.41 | Hazra et al.42 | Karakurt et al.43 | Zhou et al.44 |
|---|---|---|---|---|
| Source of network | Human PPI network subnetwork from the genes, which are co-expressed with ACE2. Human PPIs were obtained using SpidermiR tool (PMID: 28134831) | Human PPI network from STRING (https://string-db.org) | Metabolic network of bronchus respiratory epithelial cell based on Recon2 (PMID: 23455439), human PPI network from STRING (https://string-db.org) | SARS-CoV-2-human PPIs,41 viral-human PPIs for other coronaviruses, human PPIs from 18 public databases. |
| Source of compound-target interactions | Drug-target interactions were obtained from Matador (http://matador.embl.de) and DGIdb (https://www.dgidb.org) databases | STITCH (http://stitch.embl.de) | NAa | Drug–target associations from DrugBank (https://www.drugbank.com), Therapeutic Target Database (http://db.idrblab.net/ttd), ChEMBL (https://www.ebi.ac.uk/chembl), PharmGKB (https://www.pharmgkb.org), BindingDB (https://www.bindingdb.org/bind/index.jsp), Guide To Pharmacology (https://www.guidetopharmacology.org) |
| Transcription dataset | Data on transcription in normal lungs was obtained from Cancer Genome Atlas (https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga), Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo) and Genotype-Tissue Expression (https://gtexportal.org) databases. | Transcription profiles of peripheral blood mononuclear cells from SARS-CoV-1 infected patients (GEO ID: GSE1739) | Transcription profiles from SARS-CoV-2 infected human lung epithelial cells (GEO ID: GSE147507) | Transcription profiles from SARS-CoV-2 infected human lung epithelial cells (GEO ID: GSE147507). Protein expression profile from human Caco-2 cells infected with SARS-CoV-2 (PRIDE ID: PXD017710) |
| Pathways and biological processes | Genes correlated with ACE2 are mainly enriched in the sterol biosynthetic process, aryldialkylphosphatase activity, adenosylhomocysteinase activity, trialkylsulfonium hydrolase activity, acetate-CoA and CoA ligase activity | MMP9 showed functional annotations associated with neutrophil mediated immune-inflammation | Matrix metalloproteinase 2 (MMP2) and matrix metalloproteinase 9 (MMP9) with keratan sulfate synthesis pathway may play a key role in the infection. | Co-expression of ACE2 and TMPRSS2 was elevated in absorptive enterocytes from the inflamed ileal tissues of Crohn's disease patients compared to uninflamed tissues, revealing shared pathobiology by COVID-19 and inflammatory bowel disease. COVID-19 shared intermediate inflammatory endophenotypes with asthma (including IRAK3 and ADRB2) |
| Potential targets | NAa | Hub-bottleneck node MMP9 | IL-6, IL6R, IL6ST, MMP2, MMP9 | NAa |
| Potential drugs | 36 potential anti-COVID drugs. Among possible interesting 36 drugs for COVID-19 treatment, the authors found Nimesulide, Fluticasone Propionate, Thiabendazole, Photofrin, Didanosine and Flutamide | Chloroquine and melatonin targeting MMP9. Melatonin appears to be more promising repurposed drug against MMP9 for better immune-compromising action in COVID-19 | MMP9 inhibitors may have potential to prevent “cytokine storm” in severely affected patients | 34 potential anti-COVID drugs. Among them melatonin was confirmed by observational study of 18,118 patients from a COVID-19 registry. Melatonin was associated with 64% reduced likelihood of a positive laboratory test result for SARS-CoV-2 |
a
NA – Not applicable.