In Silico Modeling of Nonspecific Binding to Human Liver Microsomes

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Abstract
Estimation of unbound fraction of substrate in microsomal incubation media is important in accurately predicting hepatic intrinsic clearance and drug-drug interactions. In this study, the unbound fraction of 1223 drug-like molecules in human liver microsomal incubation media has been determined using equilibrium dialysis. These compounds, which include 27 marketed drug molecules, cover a much broader range of physiochemical properties such as hydrophobicity, molecular weight, ionization state, and degree of binding than those examined in previous work. In developing the in silico model, we have used two-dimensional molecular descriptors including cLogP, Kier connectivity, shape, and E-state indices, a subset of MOE descriptors, and a set of absorption, disposition, metabolism, and excretion structural keys used for our in-house absorption, disposition, metabolism, excretion, and toxicity modeling. Hydrophobicity is the most important molecular property contributing to the nonspecific binding of substrate to microsomes. The prediction accuracy of the model is validated using a subset of 100 compounds, and 92% of the variance is accounted for by the model with a root mean square error (RMSE) of 0.10. For the training set of compounds, 99% of variance is accounted for by the model with a RMSE of 0.02. The performance of the developed model has been further tested using the 27 marketed drug molecules with a RMSE of 0.10 between the observed and the predicted unbound fraction values.

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