Received for publication December 26, 2007.
Revised July 2, 2008.
Accepted for publication July 3, 2008.

In Silico Modeling of Non-specific Binding to Human Liver Microsomes

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 including 27 marketed drug molecules cover a much broader range of physiochemical properties such as hydrophobicity, molecular weight, ionization state, and degree of binding than 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 ADME structural keys used for our in-house ADMET modeling. Hydrophobicity is the most important molecular property contributing to the non-specific 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 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.

Key words: computational models, drug clearance, drug discovery, in vitro-in vivo prediction, liver microsomes, mass spectrometry, protein binding

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