Pharmacokinetics, Pharmacodynamics and Drug MetabolismHow Well Do Lipophilicity Parameters, MEEKC Microemulsion Capacity Factor, and Plasma Protein Binding Predict CNS Tissue Binding?
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INTRODUCTION
Brain unbound concentration is generally accepted as free-drug concentration at the site of action for central nervous system (CNS) drugs.1,2 The free-drug hypothesis states that in the absence of active processes in a tissue, such as transport and metabolism, the steady-state unbound concentration in plasma and tissue is the same. Therefore, steady-state unbound plasma concentrations are generally representative of the free-drug concentrations responsible for drug activity at the site of
Materials
The diversity set of 94 proprietary Eli Lilly and Company compounds was selected to encompass the entire range of brain tissue binding. The diversity set represented 38 unique targets and included 34 neutral compounds, 17 zwitterions, 41 cations, and two anions. Calculated PSA and pKa values were considered in the selection of the diversity set due to the impact of these parameters on microemulsion partitioning. The distribution of clogP, clogD7.4, cPSA, molecular weight, brain Fu, and plasma
RESULTS
Correlations between MEEKC k′, clogP, clogD7.4, and cPSA in a set of 94 diverse molecules are presented in Figure 2 and Table 1. MEEKC logk′ was more strongly correlated with clogP (r2 ∼0.6) than clogD7.4 (r2 ∼0.4) or cPSA (r2 ∼0.3).
In the 94-compound diversity set, MEEKC k′ was a relatively better predictor of brain Fu (r2 = 0.74) than calculated lipophilicity parameters (clogP r2 = 0.54, clogD7.4 r2 = 0.44) and cPSA r2 = 0.19, but of the examined parameters, correlation between brain Fu and
DISCUSSION
In the present study, correlations between MEEKC k′, brain Fu, plasma Fu, calculated lipophilicity parameters (clogP and clogD7.4), and cPSA were evaluated within a set of 94 diverse molecules. These correlations, with the exception of MEEKC k′, were further extended to the complete Fu dataset of 587 compounds. The study for the first time enabled a direct head-to-head comparison of MEEKC k′, plasma Fu, and lipophilicity parameters as predictors of brain Fu within large sets of compounds.
ACKNOWLEDGEMENTS
Dr. Prashant V. Desai is acknowledged for his assistance with data mining.
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