Target and Tissue Selectivity Prediction by Integrated Mechanistic Pharmacokinetic-Target Binding and Quantitative Structure Activity Modeling

Anna H.C. Vlot, Wilhelmus E.A. de Witte, Meindert Danhof, Piet H. van der Graaf, Gerard J.P. van Westen, Elizabeth C.M. de Lange

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

Selectivity is an important attribute of effective and safe drugs, and prediction of in vivo target and tissue selectivity would likely improve drug development success rates. However, a lack of understanding of the underlying (pharmacological) mechanisms and availability of directly applicable predictive methods complicates the prediction of selectivity. We explore the value of combining physiologically based pharmacokinetic (PBPK) modeling with quantitative structure-activity relationship (QSAR) modeling to predict the influence of the target dissociation constant (KD) and the target dissociation rate constant on target and tissue selectivity. The KD values of CB1 ligands in the ChEMBL database are predicted by QSAR random forest (RF) modeling for the CB1 receptor and known off-targets (TRPV1, mGlu5, 5-HT1a). Of these CB1 ligands, rimonabant, CP-55940, and Δ8-tetrahydrocanabinol, one of the active ingredients of cannabis, were selected for simulations of target occupancy for CB1, TRPV1, mGlu5, and 5-HT1a in three brain regions, to illustrate the principles of the combined PBPK-QSAR modeling. Our combined PBPK and target binding modeling demonstrated that the optimal values of the KD and koff for target and tissue selectivity were dependent on target concentration and tissue distribution kinetics. Interestingly, if the target concentration is high and the perfusion of the target site is low, the optimal KD value is often not the lowest KD value, suggesting that optimization towards high drug-target affinity can decrease the benefit-risk ratio. The presented integrative structure-pharmacokinetic-pharmacodynamic modeling provides an improved understanding of tissue and target selectivity.

Original languageEnglish
Article number11
JournalAAPS Journal
Volume20
Issue number1
DOIs
StatePublished - Jan 1 2018
Externally publishedYes

Funding

The authors are part of the K4DD consortium, which is supported by the Innovative Medicines Initiative Joint Undertaking (IMI JU) under grant agreement no 115366. The IMI JU is a project supported by the EU’s Seventh Framework Programme (FP7/2007–2013) and the European Federation of Pharmaceutical Industries and Associations (EFPIA).

Keywords

  • kinetic selectivity
  • physiologically based pharmacokinetic modeling
  • quantitative structure-activity relationship
  • target-mediated drug disposition
  • tissue selectivity

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