10967/235 - QDB Compounds

QsarDB Repository

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:127-77-5
Name:Sulfabenz
Description:
Labels:eval
CAS:127-77-5
InChi Code:InChI=1S/C12H12N2O2S/c13-10-6-8-12(9-7-10)17(15,16)14-11-4-2-1-3-5-11/h1-9,14H,13H2

Properties

BindingClass: Activity in Androgen Receptor

ValueSource or prediction
0

experimental value

0

Procedure_13: Multivariate Logistic Regression Model (Evaluation set)