Guiding Lead Optimization for Solubility Improvement with Physics-Based Modeling.
Mol Pharm
; 17(2): 666-673, 2020 02 03.
Article
em En
| MEDLINE
| ID: mdl-31928011
ABSTRACT
Although there are a number of computational approaches available for the aqueous solubility prediction, a majority of those models rely on the existence of a training set of thermodynamic solubility measurements or/and fail to accurately account for the lattice packing contribution to the solubility. The main focus of this study is the validation of the application of a physics-based aqueous solubility approach, which does not rely on any prior knowledge and explicitly describes the solid-state contribution, in order to guide the improvement of poor solubility during the lead optimization. A superior performance of a quantum mechanical (QM)-based thermodynamic cycle approach relative to a molecular mechanical (MM)-based one in application to the optimization of two pharmaceutical series was demonstrated. The QM-based model also provided insights into the source of poor solubility of the lead compounds, allowing the selection of the optimal strategies for chemical modification and formulation. It is concluded that the application of that approach to guide solubility improvement at the late discovery and/or early development stages of the drug design proves to be highly attractive.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Termodinâmica
/
Composição de Medicamentos
/
Descoberta de Drogas
/
Chumbo
/
Modelos Químicos
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Mol Pharm
Assunto da revista:
BIOLOGIA MOLECULAR
/
FARMACIA
/
FARMACOLOGIA
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Estados Unidos