Garcia-Sosa, A. T.; Maran, U. Combined Naïve Bayesian, chemical fingerprints, and molecular docking classifiers to model and predict androgen receptor binding activity data for environmentally- and health-sensitive substances. Int. J. Mol. Sci. 2021, 22, 6695.
Compound
| ID: | 37091-65-9 | |
|---|---|---|
| Name: | Azlocillin sodium | |
| Description: | ||
| Labels: | eval | |
| CAS: | 37091-65-9 | |
| InChi Code: | InChI=1S/C20H23N5O6S/c1-20(2)13(17(28)29)25-15(27)12(16(25)32-20)22-14(26)11(10-6-4-3-5-7-10)23-19(31)24-9-8-21-18(24)30/h3-7,11-13,16H,8-9H2,1-2H3,(H,21,30)(H,22,26)(H,23,31)(H,28,29) |
Properties
BindingClass: Activity in Androgen Receptor
| Value | Source or prediction |
|---|---|
| 0 |
experimental value |
| 0 |
Procedure_13: Multivariate Logistic Regression Model (Evaluation set) |