Piir, G.; Sild, S.; Maran, U. Interpretable machine learning for the identification of estrogen receptor agonists, antagonists, and binders. Chemosphere 2023.
Compound
| ID: | e4022 | |
|---|---|---|
| Name: | Nicotinic acid 1-oxide | |
| Description: | ||
| Labels: | ||
| CAS: | 2398-81-4 | |
| InChi Code: | InChI=1S/C6H5NO3/c8-6(9)5-2-1-3-7(10)4-5/h1-4H,(H,8,9) |
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) |