TABLE 2.
Published reports on multi‐omics discovery of natural drug targets.
| Methods | Compounds | Targets | Type of disease or model study | Potential applications | Ref |
|---|---|---|---|---|---|
| Transcriptomics and proteomics (DARTS) | Arctigenin | PP2A | Diabetic kidney disease | Hypertension; inflammation | 243 |
| Genomics and proteomics (DARTS) | Ecumicin | ClpC1 | Tuberculosis | Lead compounds for antituberculosis drugs | 241 |
| Chemical proteomics and bioinformatics (gene ontology) | Baicalin | CPT1 | Obesity and hepatic steatosis | Inflammation; antibacterial; obesity | 242 |
| Metabolomics and chemical proteomics (ABPP) | Perfluorooctanoic acid | Acaca, Acacb | PFOA‐induced liver toxicity | No | 239 |
| Proteomics (DARTS) and bioinformatics (gene docking) | Bithionol | NAD‐dependent dehydrogenases | Cryptococcus neoformans | Antifungal | 237 |
| ShRNA | Aurilide B | ATP1A1 | Mitochondria‐mediated apoptosis | No | 244 |
| SiRNA | QS11 | ARFGAP1 | Breast cancer | No | 245 |
| CRISPR | Ispinesib | Kinesin‐5 | Human cancer cells | Cancer | 246 |
| AI (machine learning) | β‐Lapachone | 5‐lipoxygenase | Human cancer cells | Cancer | 247 |
| AI (deep learning) | Ziprasidone | 5‐hydroxytryptamine receptor | No | No | 248 |