Accessing lipophilicity of drugs with biomimetic models: A comparative study using liposomes and micelles

Lipophilicity is a physicochemical property of crucial importance in drug discovery and drug design. Biomimetic models, such as liposomes and micelles, constitute a valuable tool for the assessment of lipophilicity through the determination of partition coefficients (log Kp). However, the lack of standardization hampers the judgment about which model or method has the best and broadest passive drug permeation predictive capacity. This work provides a comparative analysis between the methodologies based on biomimetic models to determine the partition coefficient (log Kp). For that purpose, a set of reference substances preconized by the Organization for Economic Cooperation and Development (OECD) guidelines was used. The biomimetic models employed were liposomes and micelles composed by 1,2-dimyristoyl-sn-glycero-3-phosphorylcholine (DMPC) and hexadecylphosphocholine (HePC), respectively. Both lipids were used as representative phospholipids of natural membranes. The partition coefficients between biomimetic models and aqueous phases were determined by derivative spectroscopy at physiological conditions (37 °C and pH 7.4). The partition coefficients obtained using biomimetic models are quite different and more reliable than the ones obtained using an octanol/water system. Comparing the performance of the two biomimetic models, micelles revealed to be suitable only for substances with high molar absorption coefficient and log Kp > 3, but in general liposomes are the best model for accessing lipophilicity of drugs. Furthermore, a comparison between experimental data and the partition coefficients determined by the computational method COSMOmic is also provided and discussed. As a final summarizing result, a decision tree is provided in order to guide the selection of a tool for assessing the lipophilicity of drugs. © 2018 Elsevier

This work was supported by European Union (FEDER funds POCI/01/0145/FEDER/007265 ) and National Funds (FCT/MEC, Fundação para a Ciência e Tecnologia and Ministério da Educação e Ciência) under the Partnership Agreement PT2020 UID/QUI/50006/2013 ; through the FCT PhD Programmes and by Programa Operacional Capital Humano (POCH), specifically by the BiotechHealth Programme (Doctoral Programme on Cellular and Molecular Biotechnology Applied to Health Sciences), reference PD/00016/2012; through the FCT and POCH for the PhD grants (SFRH/BD/98105/2013 and PD/BD/105957/2014, respectively) and for the Investigator grant (IF/00293/2015); and through the financial support of the German Academic Exchange Service (DAAD). The authors would also like to thank Sara Cravo and Gisela Adriano for the technical support. Appendix A