Toward Physics-Based Solubility Computation for Pharmaceuticals to Rival Informatics.

ABSTRACT: We demonstrate that physics-based calculations of intrinsic aqueous solubility can rival cheminformatics-based machine learning predictions. A proof-of-concept was developed for a physics-based approach via a sublimation thermodynamic cycle, building upon previous work that relied upon several thermodynamic approximations, notably the 2RT approximation, and limited conformational sampling. Here, we apply improvements to our sublimation free-energy model with the use of crystal phonon mode calculations to capture the contributions of the vibrational modes of the crystal. Including these improvements with lattice energies computed using the model-potential-based Ψ_mol method leads to accurate estimates of sublimation free energy. Combining these with hydration free energies

SUBMITTER: Fowles DJ 

PROVIDER: S-EPMC8190954 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature