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Quantifying the Interactions between Biomolecules: Guidelines for Assay Design and Data Analysis.

Peter J Tonge1

  • 1Center for Advanced Study of Drug Action, Departments of Chemistry and Radiology , Stony Brook University , John S. Toll Drive , Stony Brook , New York 11794-3400 , United States.

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|March 13, 2019
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Summary
This summary is machine-generated.

Accurate determination of binding interactions is crucial for drug discovery. This perspective reminds researchers of basic assumptions in data analysis for binding assays to improve assay design and interpretation.

Keywords:
ICbindingconcentration (dose)−response curvesnonlinear regressionreplicatesreproducibility

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Area of Science:

  • Biochemistry
  • Chemical Biology
  • Drug Discovery

Background:

  • Accurate determination of binding interactions is essential in drug discovery for optimizing drug leads.
  • Binding assays are assessed by monitoring responses or quantifying free/bound ligand concentrations.
  • Alternative methods quantify property changes (e.g., mass, spectroscopic signals) upon binding.

Purpose of the Study:

  • To remind researchers of the fundamental assumptions underlying data analysis in binding interaction studies.
  • To provide guidelines for designing robust binding assays and analyzing their data.
  • To ensure rigorous scientific reporting in journals, including ACS Infectious Diseases.

Main Methods:

  • This perspective reviews the theoretical basis of data analysis for various binding assay techniques.
  • It emphasizes the importance of understanding the underlying mathematical models and their assumptions.
  • Guidelines are provided for assay design and data interpretation.

Main Results:

  • The analysis of binding data relies on nonlinear multiparameter equations.
  • Understanding the assumptions of these equations is critical for accurate interpretation.
  • Proper assay design and data analysis prevent erroneous conclusions.

Conclusions:

  • Adherence to basic assumptions in binding assay data analysis is vital for reliable results.
  • This perspective offers guidance for researchers to improve the quality and reproducibility of their binding studies.
  • Following these guidelines will enhance the rigor of scientific publications in the field.