Effective rate models for the analysis of transport-dependent biosensor data.

Area of Science:

• Biomolecular interaction analysis
• Biosensor technology
• Physical chemistry

Background:

• Optical biosensors, such as the BIACORE system, are widely used for studying biomolecular reaction kinetics.
• Accurately determining intrinsic reaction rates requires distinguishing them from mass transport effects within the biosensor.
• Existing models often use ordinary differential equations with effective rate coefficients, but their accuracy and theoretical underpinnings need further investigation.

Purpose of the Study:

• To investigate the theoretical basis of models used for analyzing biomolecular reactions in optical biosensors.
• To assess the numerical accuracy of existing and related models for separating reaction rates from transport phenomena.
• To provide a robust modeling framework for scientists using biosensors to study biomolecular interactions.

Main Methods:

• Theoretical analysis of ordinary differential equation models for biosensor systems.
• Numerical evaluation of model accuracy in representing reaction and transport kinetics.
• Comparison of different modeling approaches for biosensor data analysis.

Main Results:

• The study examines the theoretical foundations of biosensor models.
• Numerical accuracy of models incorporating reaction and transport parameters is assessed.
• The research provides insights into the suitability of different models for BIACORE data analysis.

Conclusions:

• Accurate modeling is crucial for separating intrinsic reaction rates from transport effects in optical biosensors.
• The theoretical basis and numerical accuracy of proposed models are critical for reliable biomolecular analysis.
• This work contributes to refining the interpretation of kinetic data obtained from biosensor experiments.