Molecular Modeling Approaches for the Prediction of the Nonspecific Binding of Drugs to Hepatic Microsomes

Molecular modeling approaches for the prediction of the nonspecific binding of drugs to hepatic microsomes were examined using a published database of 56 compounds. Models generated were evaluated using an independent test set of 13 compounds. A pharmacophore approach identified structural features of drugs associated with nonspecific binding. A side-chain amino group and complementary hydrophobic domain were the principal features noted. The use of shape overlays, based on the pharmacophore, in conjunction with a chemical force field in the program ROCS, yielded discrimination between molecules classified as strong binders (experimental fraction unbound in microsomes<0.50) and those with a lower degree of binding (experimental fraction unbound in microsomes>0.50). In the initial data set of 56 molecules, 18 were classified as strong binders (on the basis of the above criteria), and all of those were recovered in the top 22 molecular hits from ROCS. Additionally, computationally generated values of log P were shown to provide a reasonable estimate of the fraction unbound in microsomes, providing the compounds were in their basic form at physiological pH.

[1]  Jan Williams SciFinder from CAS: information at the desktop for scientists , 1995 .

[2]  Scott L Cockroft,et al.  The influence of nonspecific microsomal binding on apparent intrinsic clearance, and its prediction from physicochemical properties. , 2002, Drug metabolism and disposition: the biological fate of chemicals.

[3]  Kiyomi Ito,et al.  Database analyses for the prediction of in vivo drug-drug interactions from in vitro data. , 2004, British journal of clinical pharmacology.

[4]  Metabolism of ezlopitant, a nonpeptidic substance P receptor antagonist, in liver microsomes: enzyme kinetics, cytochrome P450 isoform identity, and in vitro-in vivo correlation. , 2000, Drug metabolism and disposition: the biological fate of chemicals.

[5]  R. Obach,et al.  Prediction of human clearance of twenty-nine drugs from hepatic microsomal intrinsic clearance data: An examination of in vitro half-life approach and nonspecific binding to microsomes. , 1999, Drug metabolism and disposition: the biological fate of chemicals.

[6]  J. Miners,et al.  Quantitative prediction of in vivo inhibitory interactions involving glucuronidated drugs from in vitro data: the effect of fluconazole on zidovudine glucuronidation. , 2006, British journal of clinical pharmacology.

[7]  Y. Sugiyama,et al.  Quantitative prediction of in vivo drug clearance and drug interactions from in vitro data on metabolism, together with binding and transport. , 1998, Annual review of pharmacology and toxicology.

[8]  J. Miners,et al.  Quantitative prediction of macrolide drug-drug interaction potential from in vitro studies using testosterone as the human cytochrome P4503A substrate , 2006, European Journal of Clinical Pharmacology.

[9]  Y. Sugiyama,et al.  Prediction of human hepatic clearance from in vivo animal experiments and in vitro metabolic studies with liver microsomes from animals and humans. , 2001, Drug metabolism and disposition: the biological fate of chemicals.

[10]  T. Maurer,et al.  Influence of microsomal concentration on apparent intrinsic clearance: implications for scaling in vitro data. , 2001, Drug metabolism and disposition: the biological fate of chemicals.

[11]  D. Greenblatt,et al.  Microsomal binding of amitriptyline: effect on estimation of enzyme kinetic parameters in vitro. , 2000, The Journal of pharmacology and experimental therapeutics.

[12]  R. Austin,et al.  A UNIFIED MODEL FOR PREDICTING HUMAN HEPATIC, METABOLIC CLEARANCE FROM IN VITRO INTRINSIC CLEARANCE DATA IN HEPATOCYTES AND MICROSOMES , 2005, Drug Metabolism and Disposition.

[13]  Bruno Boulanger,et al.  Towards a new age of virtual ADME/TOX and multidimensional drug discovery , 2004, Molecular Diversity.

[14]  D. Greenblatt,et al.  In vitro approaches to predicting drug interactions in vivo. , 1998, Biochemical pharmacology.

[15]  A. Avdeef,et al.  pH-Metric logP 10. Determination of Liposomal Membrane-Water Partition Coefficients of lonizable Drugs , 1998, Pharmaceutical Research.

[16]  J B Houston,et al.  Utility of in vitro drug metabolism data in predicting in vivo metabolic clearance. , 1994, Biochemical pharmacology.

[17]  A. Katz,et al.  Comparisons of the interaction of propranolol and timolol with model and biological membrane systems. , 1983, Molecular pharmacology.

[18]  T Lavé,et al.  Prediction of Hepatic Metabolic Clearance Based on Interspecies Allometric Scaling Techniques and In Vitro-In Vivo Correlations , 1999, Clinical pharmacokinetics.

[19]  J Brian Houston,et al.  In vitro-in vivo correlation for drugs and other compounds eliminated by glucuronidation in humans: pitfalls and promises. , 2006, Biochemical pharmacology.

[20]  R. Obach,et al.  Nonspecific binding to microsomes: impact on scale-up of in vitro intrinsic clearance to hepatic clearance as assessed through examination of warfarin, imipramine, and propranolol. , 1997, Drug metabolism and disposition: the biological fate of chemicals.

[21]  A. D. Rodrigues,et al.  Use of in vitro human metabolism studies in drug development. An industrial perspective. , 1994, Biochemical pharmacology.

[22]  R. Obach,et al.  Impact of nonspecific binding to microsomes and phospholipid on the inhibition of cytochrome P4502D6: implications for relating in vitro inhibition data to in vivo drug interactions. , 2003, Drug metabolism and disposition: the biological fate of chemicals.

[23]  Jonas Boström,et al.  Reproducing the conformations of protein-bound ligands: A critical evaluation of several popular conformational searching tools , 2001, J. Comput. Aided Mol. Des..

[24]  D. Greenblatt,et al.  Microsomal protein concentration modifies the apparent inhibitory potency of CYP3A inhibitors. , 2002, Drug metabolism and disposition: the biological fate of chemicals.

[25]  J. Miners,et al.  Nonspecific binding of drugs to human liver microsomes. , 2000, British journal of clinical pharmacology.

[26]  H. van de Waterbeemd,et al.  ADMET in silico modelling: towards prediction paradise? , 2003, Nature reviews. Drug discovery.

[27]  M. Wenlock,et al.  The Thermodynamics of the Partitioning of Ionizing Molecules Between Aqueous Buffers and Phospholipid Membranes , 2005, Pharmaceutical Research.

[28]  J. A. Grant,et al.  A fast method of molecular shape comparison: A simple application of a Gaussian description of molecular shape , 1996, J. Comput. Chem..

[29]  Jonas Boström,et al.  Assessing the performance of OMEGA with respect to retrieving bioactive conformations. , 2003, Journal of molecular graphics & modelling.

[30]  J. Miners,et al.  Predicting human drug glucuronidation parameters: application of in vitro and in silico modeling approaches. , 2004, Annual review of pharmacology and toxicology.

[31]  Thierry Langer,et al.  Comparative Performance Assessment of the Conformational Model Generators Omega and Catalyst: A Large-Scale Survey on the Retrieval of Protein-Bound Ligand Conformations. , 2006 .