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General, Label-Free Method for Determining K(d) and Ligand Concentration Simultaneously.

Farzad Jalali-Yazdi1, Terry T Takahashi1, Richard W Roberts1

  • 1Mork Family Department of Chemical Engineering and Materials Science, ‡Department of Chemistry, §Department of Molecular Computational Biology, and ∥USC Norris Comprehensive Cancer Center, University of Southern California , Los Angeles, California 90089-2905, United States.

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|October 21, 2015
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Summary

This study introduces a novel method to simultaneously determine the unknown input concentrations and affinities of affinity reagents like antibodies. The approach ensures accurate and reproducible measurements, overcoming limitations in current techniques.

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Area of Science:

  • Biochemistry
  • Immunology
  • Analytical Chemistry

Background:

  • Affinity reagents, such as antibodies, are crucial in biological research and diagnostics.
  • Their precise characterization, including input concentrations and binding affinities (K(d)), is often challenging due to unknown initial conditions ([L]0).

Purpose of the Study:

  • To develop a general and accurate method for simultaneously determining both the initial concentration ([L]0) and affinity (K(d)) of various affinity reagents.
  • To provide a reliable quantitative approach for antibody-based assays.

Main Methods:

  • Quantitative equilibrium exclusion immunoassays were performed using two different target concentrations.
  • Data from these assays were simultaneously fitted to determine K(d) and [L]0 values.
  • A divalent antibody binding model was employed for analysis.

Main Results:

  • The developed method accurately and reproducibly determines both K(d) and [L]0 values for affinity reagents.
  • Error analysis confirmed the uniqueness and reliability of the determined parameters.
  • The divalent model successfully yielded accurate K(d) and [L]0 in both forward and reverse assay formats.

Conclusions:

  • This approach offers a robust solution for quantifying affinity reagents when initial concentrations and affinities are unknown.
  • It addresses a significant limitation in obtaining quantitative data, particularly from reverse immunoassays.
  • The method enhances the reliability and accuracy of data generated using affinity reagents in diverse applications.