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: | sc2 | |
|---|---|---|
| Name: | Acetylsalicylic Acid | |
| Description: | ||
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C9H8O4/c1-6(10)13-8-5-3-2-4-7(8)9(11)12/h2-5H,1H3,(H,11,12) |
Properties
logS0: Intrinsic aqueous solubility from single source [log(mol/L)]
| Value | Source or prediction |
|---|---|
| -1.67 |
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 |
| -2.025 |
M1: Model with Dragon descriptors from training set 1 (Tight test set) |
| -2.025 |
M1: Model with Dragon descriptors from training set 1 (Test sets together) |
logS0a: Intrinsic aqueous solubility from multiple sources [log(mol/L)]
| Value | Source or prediction |
|---|---|
| -1.67 |
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 |
| -2.528 |
M2: Model with RDKit descriptors from training set 2 (Tight test set) |
| -2.528 |
M2: Model with RDKit descriptors from training set 2 (Test sets together) |
| -1.889 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Tight test set) |
| -1.889 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Test sets together) |
| -2.147 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Tight test set) |
| -2.147 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Test sets together) |