Computational analysis of non-competitive enzyme inhibition in microbial and biomedical applications

Abstract

Understanding physiological responses within the human body requires a detailed investigation of enzyme kinetics, a fundamental aspect of biochemical processes. This study employs mathematical modeling to analyze enzyme behavior in living organisms, focusing on the impact of non-competitive inhibitors on catalytic activity. Enzyme inhibitors are known to modify enzyme-substrate interactions, either slowing down or completely halting catalytic reactions. Unlike competitive inhibitors, non-competitive inhibitors bind to enzymes in a way that prevents direct competition with the substrate, altering the reaction dynamics. This work formulates a system of nonlinear differential equations to predict product formation in enzyme-substrate-inhibitor interactions. By computing threshold values, the study examines enzyme efficiency, substrate conversion rates, and complexity in biochemical reactions. Stability analysis is conducted to determine asymptotically stable conditions for optimal enzyme-substrate reactions. Numerical simulations provide insights into the impact of inhibition on biochemical pathways, offering applications in drug design, enzyme regulation, and metabolic engineering. The findings contribute to medical biotechnology and bio-informatics by enhancing our understanding of enzymatic control mechanisms and their relevance in therapeutic interventions.