Piir, G.; Sild, S.; Maran, U. Interpretable machine learning for the identification of estrogen receptor agonists, antagonists, and binders. Chemosphere 2023.
Compound
| ID: | t101 | |
|---|---|---|
| Name: | Glycoluril | |
| Description: | ||
| Labels: | ||
| CAS: | 496-46-8 | |
| InChi Code: | InChI=1S/C4H6N4O2/c9-3-5-1-2(7-3)8-4(10)6-1/h1-2H,(H2,5,7,9)(H2,6,8,10) |
Properties
er_ago: Activity in ER agonist pathway
| Value | Source or prediction |
|---|---|
| agonist |
experimental value |
| agonist |
Tab3.agonists: Model for ER activity on agonists pathway (Training set) |
| inactive |
Tab3.agonists: Model for ER activity on agonists pathway (Out of bag) |
er_ant: Activity in ER antagonist pathway
| Value | Source or prediction |
|---|---|
| antagonist |
experimental value |
| antagonist |
Tab3.antagonists: Model for ER activity on antagonists pathway (Test set) |
er_bin: Binding activity in estrogen receptor
| Value | Source or prediction |
|---|---|
| binder |
experimental value |
| binder |
Tab3.binders: Model for binding in ER (Training set) |
| inactive |
Tab3.binders: Model for binding in ER (Out of bag) |