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:sc82
Name:Promethazine
Description:
Labels:
CAS:
InChi Code:InChI=1/C17H20N2S/c1-13(18(2)3)12-19-14-8-4-6-10-16(14)20-17-11-7-5-9-15(17)19/h4-11,13H,12H2,1-3H3

Properties

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

ValueSource or prediction
-4.38

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

-4.541

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

-4.541

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
-4.38

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

-4.066

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

-4.066

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

-4.236

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

-4.236

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

-4.281

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

-4.281

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