Piir, G.; Sild, S.; Maran, U. Interpretable machine learning for the identification of estrogen receptor agonists, antagonists, and binders. Chemosphere 2023.
Compound
| ID: | e5862 | |
|---|---|---|
| Name: | Enprofylline | |
| Description: | ||
| Labels: | ||
| CAS: | 41078-02-8 | |
| InChi Code: | InChI=1S/C8H10N4O2/c1-2-3-12-6-5(9-4-10-6)7(13)11-8(12)14/h4H,2-3H2,1H3,(H,9,10)(H,11,13,14) |
Properties
er_ago: Activity in ER agonist pathway
| Value | Source or prediction |
|---|---|
| inactive |
experimental value |
| inactive |
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 |
| inactive |
Tab3.binders: Model for binding in ER (Evaluation set) |