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Mechanistic computational modeling of the kinetics and regulation of NADPH oxidase 2 assembly and activation facilitating superoxide production

Abstract Reactive oxygen species (ROS) play a crucial role in many physiological processes. However, ROS overproduction leads to oxidative stress, which plays a critical role in cell injury/death and the pathogenesis of many diseases. Members of NADPH oxidase (NOX) family, most of which are comprised of membrane and cytosolic components, are known to be the major nonmitochondrial sources of ROS in many cells. NOX2 is a widely-expressed and well-studied NOX family member, which is activated upon assembly of its membrane subunits gp91 phox and p22 phox with its cytosolic subunits p40 phox , p47 phox , p67 phox , and Rac, facilitating ROS production. NOX2 activation is also enhanced by GTP and inhibited by GDP. However, there remains a lack of a mechanistic, quantitative, and integrated understanding of the kinetics and regulation of the assembly of these subunits and their relative contributions toward NOX2 activation and ROS production. Toward this end, we have developed a mechanistic computational model, which incorporates a generalized random rapid equilibrium binding mechanism for NOX2 assembly and activation as well as regulations by GTP (activation), GDP (inhibition), and individual subunits enhancing the binding of other subunits (mutual binding enhancement). The resulting model replicates diverse published kinetic data, including subunit concentration-dependent NOX2 activation and ROS production, under different assay conditions, with appropriate estimates of the unknown model parameters. The model provides a mechanistic, quantitative, and integrated framework for investigating the critical roles of NOX2 subunits in NOX2 assembly and activation facilitating ROS production in a variety of physiological and pathophysiological conditions. However, there is also a need for better quantitative kinetic data based on current understanding of NOX2 assembly and activation in order to test and further develop this model.