Considerations for improved performance of competition association assays analysed with the Motulsky-Mahan's "kinetics of competitive binding" model.

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ID: 15990
2019
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Abstract
Target engagement dynamics can influence drugs' pharmacological effects. The kinetic parameters for drug:target interactions are often quantified by evaluating competition association experiments - measuring simultaneous protein binding of labelled tracers and unlabelled test compounds over time - with Motulsky-Mahan's 'kinetics of competitive binding' model. Despite recent technical improvements, the current assay formats impose practical limitations to this approach. This study aims at the characterization, understanding and prevention of these experimental constraints and associated analytical challenges.Monte Carlo simulations were used to run virtual kinetic and equilibrium tracer binding- and competition experiments in both normal and perturbed assay conditions. Data were fitted to standard equations derived from the mass action law (including Motulsky-Mahan's), and to extended versions aiming to cope with frequently observed deviations of the canonical traces. Results were compared to assess the precision and accuracy of these models and identify experimental factors influencing their performance.Factors influencing the precision and accuracy of the Motulsky-Mahan model: Interplay between compound dissociation rates, measurement time and interval frequency. Tracer concentration and binding kinetics. Relative abundance of equilibrium complexes in vehicle controls. Recommendations for better design of tracer characterization experiments. New strategies to deal with systematic signal decay.This work advances our comprehension of the Motulsky-Mahan kinetics of competitive binding model; providing experimental design recommendations, data analysis tools, and general guidelines for its practical application in the in vitro pharmacology and drug screening laboratory settings.
Reference Key
georgi2019considerationsbritish Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Georgi, Victoria;Dubrovskiy, Alexey;Steigele, Stephan;Fernández-Montalván, Amaury E;
Journal british journal of pharmacology
Year 2019
DOI
10.1111/bph.14841
URL
Keywords Keywords not found

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