An introduction to multiway modeling of fluorescence excitation-emission measurements to estimate the interaction of maprotiline hydrochloride and DNA, and quantify the drug-DNA binding constant

Abstract

A novel spectrofluorimetric multiway analysis method was introduced to estimate the interaction between maprotiline hydrochloride (MAP) and calf thymus deoxyribonucleic acid (DNA) and quantify the binding constant of the MAP-DNA complex. This innovative approach combines the high sensitivity and specificity of spectrofluorimetry with an advanced multiway data analysis algorithm, enabling detailed characterization of the binding process in this study. This exemplary application is to elucidate MAP-DNA interactions using a multiway data analysis model applied to fluorescence excitation-emission measurements. After the reaction between MAP and DNA fluorescence spectra were recorded to generate a three-dimensional data tensor. This tensor was decomposed using parallel factor analysis (PARAFAC) to extract distinct excitation spectra, emission spectra, and concentration profiles. This PARAFAC decomposition effectively isolated the individual fluorescence signals of free MAP and the MAP-DNA complex. In the PARAFAC application, the binding constants were calculated at 288, 298, and 310 K as (10.64 ± 0.025) × 10⁴, 1.90 ± 0.050) × 10⁴, and (0.42 ± 0.004) × 10⁴ M⁻¹, respectively. Thermodynamic parameters (ΔS⁰ = −282.19 J mol⁻¹ K⁻¹, ΔH⁰ = −108.83 kJ/mol and ΔG⁰ = −27.70, −24.40, and −21.49 kJ/mol at 288, 298, and 310 K, respectively) were calculated. Negative ΔG° values indicated that, under standard conditions, the binding process was thermodynamically favorable at equilibrium. The negative ΔS° and ΔH° values revealed that van der Waals forces and hydrogen bonding were the primary contributors to MAP-DNA binding. This comprehensive analysis demonstrated the utility of the PARAFAC approach in distinguishing free drug (MAP) from the MAP-DNA complex and elucidating the binding mechanisms. Compared to traditional techniques, the multiway data analysis approach has high potential as an alternative and powerful tool to evidence the drug-DNA interaction even in complex reaction mixtures.