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Distinct in vivo target occupancy by bivalent‐ and induced‐fit‐like binding drugs
Author(s) -
Vauquelin Georges
Publication year - 2017
Publication title -
british journal of pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.432
H-Index - 211
eISSN - 1476-5381
pISSN - 0007-1188
DOI - 10.1111/bph.13989
Subject(s) - in vivo , occupancy , bivalent (engine) , pharmacokinetics , dissociation constant , chemistry , pharmacology , pharmacodynamics , drug , drug discovery , computational biology , medicine , biochemistry , biology , ecology , receptor , microbiology and biotechnology , organic chemistry , metal
Background and Purpose Optimal drug therapy often requires long‐lasting target occupancy While this attribute was usually linked to the drug's pharmacokinetic properties, the dissociation rate is now increasingly recognized to contribute as well. Nearly all the earlier pharmacokinetic‐pharmacodynamic (PK‐PD) simulations encompassed single‐step binding drugs and focused on k off . However, ‘micro’‐PK mechanisms and more complex binding mechanisms like bivalent‐ and induced‐fit binding may contribute as well. Corresponding binding models are presently explored. Experimental Approach We compared the 24 h in vivo occupancy over time profiles of prototype bivalent‐ and induced‐fit‐like binding drugs (A and B) after one or repeated daily dosings, both without and with rebinding. Special attention was focused on the effect of each of the microscopic rate constants on the occupancy profiles and on the metrics to represent those profiles. Key Results Although both models can be represented by the same mathematical formulation, drugs A and B display quite different occupancy profiles, even though they have the same potency. These differences can be attributed to the different effects of their microscopic rate constants on their composite k off and also on their susceptibility to experience rebinding. This also affects how the occupancy profiles of bivalent‐ and induced‐fit‐like binders progress when repeating the dosings and by changing the dosage. Conclusions and Implications Closer attention should be paid to more complex binding models in PK‐PD simulations. This may help pharmacologists and medicinal chemists to improve the translation of in vitro kinetic measurements from preclinical screening programmes into clinical efficiency.