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A Robust Method for Assaying the Immunoreactive Fraction in Nonequilibrium Systems
Thibaut Denoël1, Luca Pedrelli1, Giuseppe Pantaleo2
1Department of Nuclear Medicine and Molecular Imaging, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 46, 1011 Lausanne, Switzerland.
The immunoreactive fraction r provides important information on the functional purity of radiolabeled proteins. It is traditionally determined by saturating the radioimmunoconjugate with an increasing excess of antigen, followed by linear extrapolation to infinite antigen excess in a double inverse "Lindmo plot". Although several reports have described shortcomings in the Lindmo plot, a systematic examination is lacking. Using an experimental and simulation-based approach, we compared-for accuracy, precision and robustness-the Lindmo plot with the "rectangular hyperbola" extrapolation method based on the Langmuir model. The differences between the theoretical and extrapolated r values demonstrate that nonequilibrium and antigen depletion are important sources of error. The mathematical distortions resulting from the linearization of the data in the Lindmo plot induce fragility towards stochastic errors and make it necessary to exclude low bound fractions. The rectangular hyperbola provides robust and precise r estimates from raw binding data, even for slow kinetics.
The immunoreactive fraction r provides important information on the functional purity of radiolabeled proteins. It is traditionally determined by saturating the radioimmunoconjugate with an increasing excess of antigen, followed by linear extrapolation to infinite antigen excess in a double inverse "Lindmo plot". Although several reports have described shortcomings in the Lindmo plot, a systematic examination is lacking. Using an experimental and simulation-based approach, we compared-for accuracy, precision and robustness-the Lindmo plot with the "rectangular hyperbola" extrapolation method based on the Langmuir model. The differences between the theoretical and extrapolated r values demonstrate that nonequilibrium and antigen depletion are important sources of error. The mathematical distortions resulting from the linearization of the data in the Lindmo plot induce fragility towards stochastic errors and make it necessary to exclude low bound fractions. The rectangular hyperbola provides robust and precise r estimates from raw binding data, even for slow kinetics.
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