Target activity models trained on measured data
Each model is trained on measured activity data (IC50 and similar) for one target. Give it compounds and it predicts their activity. Validation r is the correlation between predicted and measured values on compounds held out of training; we show the higher of the two workflows. If you have your own data, you can train a new target model in TSAP.
| Target | Area | PDB | Training compounds | Available in | Validation r | Actions |
|---|---|---|---|---|---|---|
| EGFR P00533 | Oncology | 1M17 | 58–66 | TSAP (Boltz-2)TSAP (AI-QSAR) | 0.90 | Details |
| MDM2 Q00987 | Oncology | 5C5A | 116 | TSAP (Boltz-2)TSAP (AI-QSAR) | 0.96 | Details |
| TNKS2 Q9H2K2 | Oncology | 4HKI | 60–61 | TSAP (Boltz-2)TSAP (AI-QSAR) | 0.85 | Details |
| GLP1R P43220 | Metabolic | 6X1A | 75–84 | TSAP (Boltz-2)TSAP (AI-QSAR) | 0.88 | Details |
| RORC P51449 | Immunology | 4WLB | 81–140 | TSAP (Boltz-2)TSAP (AI-QSAR) | 0.76 | Details |
| LRRK2 Q5S007 | Neuroscience | 8TZC | 120 | TSAP (Boltz-2)TSAP (AI-QSAR) | 0.90 | Details |
| MAP4K1 Q92918 | Immuno-oncology | 8CIJ | 120 | TSAP (Boltz-2)TSAP (AI-QSAR) | 0.88 | Details |
| CBLB Q13191 | Immuno-oncology | 8GCY | 104 | TSAP (Boltz-2)TSAP (AI-QSAR) | 0.86 | Details |
Don't see your target?
If you have activity data, you can train one yourself with TSAP. Read the TSAP guide