10967/257 - QDB Compounds

QsarDB Repository

Oja, M.; Sild, S.; Piir, G.; Maran, U. Intrinsic aqueous solubility: mechanistically transparent data-driven modeling of drug substances. Pharmaceutics 2022, 14, 2248.

Compound

ID:sc73
Name:Perphenazine
Description:
Labels:
CAS:
InChi Code:InChI=1S/C21H26ClN3OS/c22-17-6-7-21-19(16-17)25(18-4-1-2-5-20(18)27-21)9-3-8-23-10-12-24(13-11-23)14-15-26/h1-2,4-7,16,26H,3,8-15H2

Properties

logS0: Intrinsic aqueous solubility from single source [log(mol/L)]

ValueSource or prediction
-4.48

Avdeef, A. Prediction of aqueous intrinsic solubility of druglike molecules using Random Forest regression trained with Wiki-pS0 database. ADMET DMPK 2020, 8, 29–77. https://doi.org/http://doi.org/10.5599/admet.766

-4.596

M1: Model with Dragon descriptors from training set 1 (Tight test set)

-4.596

M1: Model with Dragon descriptors from training set 1 (Test sets together)

logS0a: Intrinsic aqueous solubility from multiple sources [log(mol/L)]

ValueSource or prediction
-4.48

Avdeef, A. Prediction of aqueous intrinsic solubility of druglike molecules using Random Forest regression trained with Wiki-pS0 database. ADMET DMPK 2020, 8, 29–77. https://doi.org/http://doi.org/10.5599/admet.766

-4.205

M2: Model with RDKit descriptors from training set 2 (Tight test set)

-4.205

M2: Model with RDKit descriptors from training set 2 (Test sets together)

-3.999

M3: Model with PaDEL and XLOGS descriptors from training set 2 (Tight test set)

-3.999

M3: Model with PaDEL and XLOGS descriptors from training set 2 (Test sets together)

-4.267

M_cons: Consensus model (average of predictions from M1, M2 and M3) (Tight test set)

-4.267

M_cons: Consensus model (average of predictions from M1, M2 and M3) (Test sets together)