A Methodological Comparison of Linear and Non-Linear Regression for Kinetic Analysis of Hydrogen Peroxide Decomposition by Catalase

Abstract

TThis study presents a comprehensive kinetic analysis of hydrogen peroxide decomposition by bovine liver catalase, with particular emphasis on methodological evaluation of parameter estimation techniques. Kinetic analysis revealed that under the experimental conditions employed, the decomposition exhibited apparent second-order behavior (R²>0.993), with rate constants of 0.13 L·mmol⁻¹·min⁻¹ at 24°C and 0.064 L·mmol⁻¹·min⁻¹ at 6°C. The apparent activation energy was estimated as 28.5 kJ/mol from Arrhenius behavior. A critical comparison of regression methods revealed striking discrepancies: linear transformation approaches (Lineweaver-Burk, Eadie-Hofstee, and Hanes-Woolf methods) produced statistically problematic results, including physiologically implausible negative values for Michaelis-Menten kinetic parameters, V_m and K_m. In contrast, non-linear regression, which minimizes the residual sum of squares (RSS), yielded robust, meaningful parameters (V_m = 659 and 25.6 mmol/L.min; K_m = 962 and 69.9 mmol/L at 24°C and 6°C, respectively) and a significantly better fit to the experimental data. However, the analysis also highlights the necessity for cautious interpretation of regression-derived parameters due to inherent correlation between V_m and K_m, experimental design limitations, and model simplification constraints. This work demonstrates that while non-linear regression is indispensable for accurate kinetic analysis, its outputs must be interpreted within appropriate statistical and experimental contexts to ensure biologically relevant conclusions.