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:sc29
Name:Daidzein
Description:
Labels:
CAS:
InChi Code:InChI=1S/C15H10O4/c16-10-3-1-9(2-4-10)13-8-19-14-7-11(17)5-6-12(14)15(13)18/h1-8,16-17H

Properties

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

ValueSource or prediction
-5.23

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

-3.552

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

-3.552

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
-5.23

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

-3.972

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

-3.972

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

-3.824

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

-3.824

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

-3.782

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

-3.782

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