Piir, G.; Sild, S.; Maran, U. Interpretable machine learning for the identification of estrogen receptor agonists, antagonists, and binders. Chemosphere 2023.
Compound
| ID: | e2593 | |
|---|---|---|
| Name: | Propyphenazone | |
| Description: | ||
| Labels: | ||
| CAS: | 479-92-5 | |
| InChi Code: | InChI=1S/C14H18N2O/c1-10(2)13-11(3)15(4)16(14(13)17)12-8-6-5-7-9-12/h5-10H,1-4H3 |
Properties
er_ago: Activity in ER agonist pathway
| Value | Source or prediction |
|---|---|
| inactive |
experimental value |
| agonist |
Tab3.agonists: Model for ER activity on agonists pathway (Evaluation set) |
er_ant: Activity in ER antagonist pathway
| Value | Source or prediction |
|---|---|
| inactive |
experimental value |
| inactive |
Tab3.antagonists: Model for ER activity on antagonists pathway (Evaluation set) |
er_bin: Binding activity in estrogen receptor
| Value | Source or prediction |
|---|---|
| inactive |
experimental value |
| binder |
Tab3.binders: Model for binding in ER (Evaluation set) |