RT Journal Article SR Electronic T1 Investigating the Influence of Tracer Kinetics on Competition-Kinetic Association Binding Assays: Identifying the Optimal Conditions for Assessing the Kinetics of Low-Affinity Compounds JF Molecular Pharmacology JO Mol Pharmacol FD American Society for Pharmacology and Experimental Therapeutics SP 378 OP 392 DO 10.1124/mol.119.116764 VO 96 IS 3 A1 David A. Sykes A1 Palash Jain A1 Steven J. Charlton YR 2019 UL http://molpharm.aspetjournals.org/content/96/3/378.abstract AB 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., koff = 10 minute−1 low-affinity “hits” through to slowly dissociating e.g., koff = 0.01 minute−1 high-affinity “candidates”). For more rapidly dissociating ligands (e.g., koff = 10 minute−1), the key to obtaining accurate kinetic parameters was to employ a tracer with a relatively fast off-rate (e.g., koff = 1 minute−1) 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.