Fluorescence modeling in a multicomponent system.

Area of Science:

• Biochemistry
• Analytical Chemistry
• Spectroscopy

Background:

• Fluorescence spectroscopy is crucial for analyzing biological molecules like tyrosine and tryptophan.
• Quantifying mixtures of these amino acids presents challenges due to overlapping signals.
• Existing models may not universally apply across different experimental setups.

Purpose of the Study:

• To develop a generalized fluorescence model for binary tyrosine-tryptophan mixtures.
• To establish a model applicable across diverse experimental configurations.
• To improve the accuracy of fluorescence-based concentration measurements.

Main Methods:

• Collected an extensive fluorescence database for tyrosine-tryptophan mixtures (10⁻⁶ M–10⁻³ M) using 280 nm excitation.
• Derived a generalized model incorporating a geometric integral for various setups.
• Introduced a correction factor for signal linearization and modeled water Raman effects.

Main Results:

• The generalized model accurately described multicomponent fluorescence signals.
• The model demonstrated applicability across an NADH probe, laser-induced fluorescence, and a commercial spectrofluorometer.
• A proposed correction factor linearized fluorescence signals concerning fluorophore concentrations.
• Average prediction errors ranged from 10-20%, largely due to experimental uncertainties.

Conclusions:

• The developed generalized fluorescence model provides a robust framework for analyzing tyrosine-tryptophan mixtures.
• The model's adaptability to different configurations enhances its utility in biochemical analysis.
• Further refinement could minimize experimental uncertainties and improve predictive accuracy.