Quantitative Modeling of Optimal Physicochemical Parameters of Insect β-glucosidases from Graphical Data

Abstract

β-glucosidases are essential insect hydrolases that facilitate the digestion of polysaccharide, secondary metabolite detoxification, and chemical defense adaptation. Understanding their physicochemical behaviour is crucial for elucidating catalytic mechanisms and exploring their potential in industrial biotechnology. Traditional methods for determining optimal enzymatic parameters, such as pHopt and Topt, often rely on labor-intensive experiments. This study employed a mathematical modeling approach grounded in graphical data analysis to determine the ideal parameters of insect β-glucosidases. Activity–pH and activity–temperature profiles were recreated from existing data using WebPlotDigitizer and then matched to both empirical and mechanistic models through nonlinear regression. The best-fitting models were chosen based on various statistical metrics, such as the coefficient of determination (R² ≥ 0.85), the AICc, PRESS, and Fisher's test. The estimated optimal pH (pHopt) ranged from 4.74 to 6.15, whereas the optimal temperature (Topt) varied from 302.9 to 319.6 K, confirming the slightly acidic and mesophilic nature of insect β-glucosidases. Activation energies (Ea) between 30.67 and 41.19 kJ mol-1 and denaturation energies (Ed) between 66 and 299 kJ mol-1 were calculated, indicating moderate thermal stability and functional adaptability. This novel approach provides a comprehensive framework for characterizing and optimizing enzymes by completing existing data and offering accurate predictions, ultimately highlighting the potential for insect β-glucosidases to serve as effective biocatalysts in sustainable biomass conversion.