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Optimum ligand affinity for competition-based primary screens.
  • Steven Shave,
  • Nhan Pham,
  • Manfred Auer
Steven Shave
The University of Edinburgh
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Nhan Pham
The University of Edinburgh
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Manfred Auer
The University of Edinburgh

Corresponding Author:[email protected]

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Abstract

Background and Purpose A simplistic assumption in setting up a competition assay is that a low affinity labelled ligand can be more easily displaced from a target protein than a high affinity ligand, which in turn produces a sensitive assay. An often-cited paper recommends the use of the highest affinity ligand available for all competition-based screens. We demonstrate that this suggestion can lead to reduced assay sensitivity, increased false negatives and ultimately, the discarding of potentially valuable active compounds. Experimental Approach Using our recently developed PyBindingCurve software for mechanistic understanding of complex biological interaction systems, we have simulated competition experiments using protein, ligand, and inhibitor concentrations common to drug screening campaigns. Key Results Our simulations reveal a labelled ligand affinity range based on assay parameters, rather than a general rule to optimise assay sensitivity. We provide source code to carry out these simulations, a video summarising the key findings, along with a simple lookup table allowing all scientists the ability to identify and visualise optimal dynamic ranges for a competition assay. Conclusion and Implications In primary drug screening the highest assay sensitivity is required to not miss low affinity binders like for protein-protein interactions. Compounds are prioritised for hit to lead phase projects in which more detailed inhibitor affinity determination is achieved. The application of our freely available software and lookup tables will reduce false negative rates and lead to the consistent creation of more performant primary screens identifying valuable compounds.