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: | t1 | |
|---|---|---|
| Name: | Amoxicillin | |
| Description: | ||
| Labels: | ||
| CAS: | 26787-78-0 | |
| InChi Code: | InChI=1S/C16H19N3O5S/c1-16(2)11(15(23)24)19-13(22)10(14(19)25-16)18-12(21)9(17)7-3-5-8(20)6-4-7/h3-6,9-11,14,20H,17H2,1-2H3,(H,18,21)(H,23,24)/t9-,10-,11+,14-/m1/s1 |
Properties
logS0: Intrinsic aqueous solubility from single source [log(mol/L)]
| Value | Source or prediction |
|---|---|
| -1.97 |
Avdeef, A. Multi-lab intrinsic solubility measurement reproducibility in CheqSol and shake-flask methods. ADMET DMPK 2019, 7, 210–219. https://doi.org/http://doi.org/10.5599/admet.698 |
| -2.858 |
M1: Model with Dragon descriptors from training set 1 (Training set) |
logS0a: Intrinsic aqueous solubility from multiple sources [log(mol/L)]
| Value | Source or prediction |
|---|---|
| -2.03 |
experimental value |
| -2.589 |
M2: Model with RDKit descriptors from training set 2 (Training set) |
| -1.58 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Training set) |
| -2.342 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Training set) |