Piir, G.; Sild, S.; Maran, U. Interpretable machine learning for the identification of estrogen receptor agonists, antagonists, and binders. Chemosphere 2023.
Compound
| ID: | e6531 | |
|---|---|---|
| Name: | Furafylline | |
| Description: | ||
| Labels: | ||
| CAS: | 80288-49-9 | |
| InChi Code: | InChI=1S/C12H12N4O3/c1-7-13-9-10(14-7)16(6-8-4-3-5-19-8)12(18)15(2)11(9)17/h3-5H,6H2,1-2H3,(H,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) |