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Determination of High-affinity Antibody-antigen Binding Kinetics Using Four Biosensor Platforms
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Modelling random antibody adsorption and immunoassay activity.

D Mackey1, E Kelly, R Nooney

  • 1School of Mathematical Sciences, Dublin Institute of Technology, Kevin Street, Dublin 8, Ireland.

Mathematical Biosciences and Engineering : MBE
|October 25, 2016
PubMed
Summary

This study introduces a mathematical model to optimize antibody concentration in immunoassays. The model predicts the ideal antibody coverage for maximum sensitivity and detection limits in diagnostic assays.

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Area of Science:

  • Biotechnology
  • Biophysics
  • Immunology

Background:

  • Immunoassay sensitivity relies on optimal capture antibody concentration and orientation on solid surfaces.
  • Antibody immobilization affects antigen-binding site accessibility due to orientation and packing density.

Purpose of the Study:

  • To develop a mathematical model predicting correctly oriented antibody concentration during immobilization.
  • To determine optimal antibody surface coverage for maximizing assay sensitivity and limit of detection.

Main Methods:

  • Utilized random sequential adsorption (RSA) theory to model antibody deposition.
  • Analyzed the evolution of correctly oriented antibody concentration under varying conditions.

Main Results:

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  • The model predicts how antibody concentration and orientation change during immobilization.
  • Identified competing effects of high antibody concentration (denaturation vs. upright orientation).
  • Demonstrated the existence of an optimal surface coverage for maximum active antibody concentration.

Conclusions:

  • The developed mathematical model aids in optimizing antibody concentration for enhanced immunoassay performance.
  • Understanding antibody orientation and coverage is crucial for improving assay sensitivity and detection limits.