Piir, G.; Sild, S.; Maran, U. Interpretable machine learning for the identification of estrogen receptor agonists, antagonists, and binders. Chemosphere 2023.
Compound
| ID: | t93 | |
|---|---|---|
| Name: | Triamcinolone | |
| Description: | ||
| Labels: | ||
| CAS: | 124-94-7 | |
| InChi Code: | InChI=1S/C21H27FO6/c1-18-6-5-12(24)7-11(18)3-4-13-14-8-15(25)21(28,17(27)10-23)19(14,2)9-16(26)20(13,18)22/h5-7,13-16,23,25-26,28H,3-4,8-10H2,1-2H3 |
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 (Test 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 (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) |
| binder |
Tab3.binders: Model for binding in ER (Out of bag) |