Free-solution label-free detection of alpha-crystallin chaperone interactions by back-scattering interferometry

Area of Science:

• Biochemistry
• Biophysics
• Analytical Chemistry

Background:

• Understanding protein-protein interactions is crucial for deciphering biological processes.
• Accurate quantification of binding kinetics and affinity is essential for drug discovery and disease research.
• Existing methods often require large sample volumes or labeling, limiting their application.

Purpose of the Study:

• To introduce and validate backscatter interferometry (BSI) for quantitative, label-free analysis of protein-protein interactions.
• To demonstrate the capability of BSI in characterizing binding kinetics (forward and reverse rate constants) and affinity (dissociation constants).
• To showcase BSI's application in analyzing interactions involving small heat-shock proteins and disease-related mutants.

Main Methods:

• Utilized backscatter interferometry (BSI) on a PDMS microchip for label-free analysis of molecular interactions in free solution.
• Measured changes in refractive index to determine binding kinetics and affinity.
• Applied global analysis to fit time-dependent BSI traces for kinetic parameter determination.
• Characterized the binding of alpha-Crystallin with T4 lysozyme mutants and betaB1-Crystallin.

Main Results:

• Successfully quantified forward and reverse rate constants for two-mode binding using BSI.
• Demonstrated BSI's ability to recapitulate the selectivity of alphaB-Crystallin binding based on substrate properties.
• Showed that an alphaA-Crystallin mutant associated with hereditary cataract exhibits altered binding to betaB1-Crystallin.
• Obtained meaningful dissociation constants from binding isotherms, validating BSI's accuracy.

Conclusions:

• Backscatter interferometry (BSI) is established as a novel tool for rapid, quantitative, label-free analysis of protein-protein interactions.
• BSI requires exceedingly small sample quantities and operates under physiological conditions, making it suitable for diverse applications.
• BSI can be extended to screen libraries of disease-related mutants, enabling the quantification of affinity and kinetic changes crucial for understanding disease mechanisms.