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: | sc83 | |
|---|---|---|
| Name: | Repaglinide | |
| Description: | ||
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C27H36N2O4/c1-4-33-25-17-20(12-13-22(25)27(31)32)18-26(30)28-23(16-19(2)3)21-10-6-7-11-24(21)29-14-8-5-9-15-29/h6-7,10-13,17,19,23H,4-5,8-9,14-16,18H2,1-3H3,(H,28,30)(H,31,32)/t23-/m0/s1 |
Properties
logS0: Intrinsic aqueous solubility from single source [log(mol/L)]
| Value | Source or prediction |
|---|---|
| -4.77 |
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 |
| -5.818 |
M1: Model with Dragon descriptors from training set 1 (Tight test set) |
| -5.818 |
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 |
|---|---|
| -4.77 |
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 |
| -6.103 |
M2: Model with RDKit descriptors from training set 2 (Tight test set) |
| -6.103 |
M2: Model with RDKit descriptors from training set 2 (Test sets together) |
| -5.802 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Tight test set) |
| -5.802 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Test sets together) |
| -5.908 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Tight test set) |
| -5.908 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Test sets together) |