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:sc123
Name:Procaine
Description:
Labels:
CAS:
InChi Code:InChI=1S/C13H20N2O2/c1-3-15(4-2)9-10-17-13(16)11-5-7-12(14)8-6-11/h5-8H,3-4,9-10,14H2,1-2H3

Properties

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

ValueSource or prediction
-2.3

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

-2.142

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

-2.142

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
-2.3

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

-2.783

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

-2.783

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

-2.293

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

-2.293

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

-2.406

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

-2.406

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