TY - JOUR
T1 - A fragment based approach for the computational prediction of the nonspecific binding of drugs to hepatic microsomes
AU - Nair, Pramod
AU - McKinnon, Ross
AU - Miners, John
PY - 2016/11
Y1 - 2016/11
N2 - Correction for the nonspecific binding (NSB) of drugs to liver microsomes is essential for the accurate measurement of the kinetic parameters Km and Ki, and hence in vitro-in vivo extrapolation to predict hepatic clearance and drug-drug interaction potential. Although a number of computational approaches for the estimation of drug microsomal NSB have been published, they generally rely on compound lipophilicity and charge state at the expense of other physicochemical and chemical properties. In this work, we report the development of a fragment-based hologram quantitative structure activity relationship (HQSAR) approach for the prediction ofNSB using a database of 132 compounds. The model has excellent predictivity, with a noncross-validated r2 of 0.966 and cross-validated r2 of 0.680, with a predictive r2 of 0.748 for an external test set comprising 34 drugs. The HQSAR method reliably predicted the fraction unbound in incubations of 95% of the training and test set drugs, excluding compounds with a steroid or morphinan 4,5-epoxide nucleus. Using the same data set of compounds, performance of the HQSAR method was superior to a model based on logP/D as the sole descriptor (predictive 2 for the test set compounds, 0.534). Thus, the HQSAR method provides an alternative approach to laboratory-based procedures for the prediction of the NSB of drugs to liver microsomes, irrespective of the drug charge state (acid, base, or neutral).
AB - Correction for the nonspecific binding (NSB) of drugs to liver microsomes is essential for the accurate measurement of the kinetic parameters Km and Ki, and hence in vitro-in vivo extrapolation to predict hepatic clearance and drug-drug interaction potential. Although a number of computational approaches for the estimation of drug microsomal NSB have been published, they generally rely on compound lipophilicity and charge state at the expense of other physicochemical and chemical properties. In this work, we report the development of a fragment-based hologram quantitative structure activity relationship (HQSAR) approach for the prediction ofNSB using a database of 132 compounds. The model has excellent predictivity, with a noncross-validated r2 of 0.966 and cross-validated r2 of 0.680, with a predictive r2 of 0.748 for an external test set comprising 34 drugs. The HQSAR method reliably predicted the fraction unbound in incubations of 95% of the training and test set drugs, excluding compounds with a steroid or morphinan 4,5-epoxide nucleus. Using the same data set of compounds, performance of the HQSAR method was superior to a model based on logP/D as the sole descriptor (predictive 2 for the test set compounds, 0.534). Thus, the HQSAR method provides an alternative approach to laboratory-based procedures for the prediction of the NSB of drugs to liver microsomes, irrespective of the drug charge state (acid, base, or neutral).
UR - http://www.scopus.com/inward/record.url?scp=84990866805&partnerID=8YFLogxK
U2 - 10.1124/dmd.116.071852
DO - 10.1124/dmd.116.071852
M3 - Article
SN - 0090-9556
VL - 44
SP - 1794
EP - 1798
JO - Drug Metabolism and Disposition
JF - Drug Metabolism and Disposition
IS - 11
ER -