“… | Title | Datasets used | Repurposed Drugs | Evaluation Criteria | Tools used | Ref. |
1 | Designing a Network Proximity-Based Drug Repurposing Strategy for COVID-19 | BioGRID | – | Network proximity/ Network Diffusion | Cytoscape, VarElect tool | [169] |
2 | Network medicine framework for identifying drug-repurposing opportunities for COVID-19 | 13 Datasets, DrugBank, STRING | 989 Drugs, 77 Validated in VeroE6 Cells, 76/77 validated in Human Cells | Network proximity, network diffusion, Network AI | Experimental, Ensembl algorithmic prediction | [176] |
3 | Drug repurposing for coronavirus (SARS-CoV-2) based on gene co-expression network analysis | DGIDb, gene co-expression, DrugBank | 5 Drugs | Gene enrichment analysis for Genes and miRNA | Node degree and centralities | [195] |
4 | Network-based repurposing identifies anti-alarmins as drug candidates to control severe lung inflammation in COVID-19 | Uniprot, STRING, CMap, LINCS, GEO | – | Gene expression profiling | CMap ranking | [184] |
5 | Integrative In Silico Investigation Reveals the Host-Virus Interactions in Repurposed Drugs Against SARS-CoV-2 | STITCH, KEGG, BioGRID, PubChem, IID, | – | Enrichment analysis, Molecular docking | DAVID, GOplot, AutoDock Vina, Cytoscape, Ligplot+ | [196] |
6 | Discovery of Potential Therapeutic Drugs for COVID-19 Through Logistic Matrix Factorization with Kernel Diffusion | – | 4 Drugs | 5-fold cross validations, AUC, AUPRs, recall, similarity diffusion | Molecular docking | [197] |
7 | HeTDR: Drug repositioning based on heterogeneous networks and text mining | Mesh, DrugBank, PubMed | 10 Drugs | AUPR, AUROC, F1-measure | – | [198] |
8 | ... |
…”