Redoxyme: a lightweight graphical user interface for standardized calculation of antioxidant enzyme activities

Redox imbalance results from excessive accumulation of reactive oxygen species (ROS) due to either a low removal or higher production. This imbalance plays a central role in numerous physiological and pathological processes. Accurate quantification and report of antioxidant enzyme activities are therefore essential in redox biology research. However, data analysis for commonly used antioxidant enzyme activity assays, such as superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx), are frequently performed using spreadsheets or manual calculations, which are time-consuming and prone to error. In this study, we systematically evaluated the reporting practices for SOD, GPx, and CAT across the literature. We identified substantial heterogeneity in the reporting of CAT, SOD, and GPx activities, characterized by inconsistencies in unit definitions and normalization approaches that frequently preclude direct cross-study comparability. To address this, we developed, a free, open-source, Python-based graphical user interface (Redoxyme) designed to standardize and automate the calculation of antioxidant enzyme activities. The software integrates protein normalization, enzyme-specific calculation routines, data visualization, and Excel export within an intuitive interface that does not require programming expertise. Redoxyme was validated using experimental data obtained from animal tissues (mice and rats), demonstrating excellent agreement with manual calculations and established analytical methods. Redoxyme provides a practical solution for improving reproducibility and efficiency in antioxidant enzyme activity analysis. The software is currently distributed as a standalone executable for Windows (locally installed), and an interactive web-based calculator implemented in Streamlit, enabling direct use without local installation. The source code and version-controlled development history are openly accessible via GitHub, promoting transparency, reproducibility, community-driven improvements, and can, in principle, be adapted for other operating systems.