Investigating the Influence of Tracer Kinetics on Competition-Kinetic Association Binding Assays: Identifying the Optimal Conditions for Assessing the Kinetics of Low-Affinity Compounds.

Mol Pharmacol

School of Life Sciences, Queen's Medical Centre, University of Nottingham, Nottingham, United Kingdom (D.A.S., P.J., S.J.C.); Centre of Membrane and Protein and Receptors (COMPARE), University of Birmingham and University of Nottingham, Midlands, United Kingdom (D.A.S., P.J., S.J.C.); and Excellerate Bioscience Ltd, Discovery Building, BioCity, Nottingham, United Kingdom (S.J.C.)

Published: September 2019

An increased appreciation of the importance of optimizing drug-binding kinetics has lead to the development of various techniques for measuring the kinetics of unlabeled compounds. One approach is the competition-association kinetic binding method first described in the 1980s. The kinetic characteristics of the tracer employed greatly affects the reliability of estimated kinetic parameters, a barrier to successfully introducing these kinetic assays earlier in the drug discovery process. Using a modeling and Monte Carlo simulation approach, we identify the optimal tracer characteristics for determining the kinetics of the range of unlabeled ligands typically encountered during the different stages of a drug discovery program (i.e., rapidly dissociating, e.g., = 10 minute low-affinity "hits" through to slowly dissociating e.g., = 0.01 minute high-affinity "candidates"). For more rapidly dissociating ligands (e.g., = 10 minute), the key to obtaining accurate kinetic parameters was to employ a tracer with a relatively fast off-rate (e.g., = 1 minute) or, alternatively, to increase the tracer concentration. Reductions in assay start-time ≤1second and read frequency ≤5 seconds significantly improved the reliability of curve fitting. Timing constraints are largely dictated by the method of detection, its inherent sensitivity (e.g., TR-FRET versus radiometric detection), and the ability to inject samples online. Furthermore, we include data from TR-FRET experiments that validate this simulation approach, confirming its practical utility. These insights into the optimal experimental parameters for development of competition-association assays provide a framework for identifying and testing novel tracers necessary for profiling unlabeled competitors, particularly rapidly dissociating low-affinity competitors.

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http://dx.doi.org/10.1124/mol.119.116764DOI Listing

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