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Succinate dehydrogenase is an inner mitochondrial membrane protein complex that links the tricarboxylic acid cycle to the electron transport system. It catalyzes the reaction between succinate and ubiquinone to produce fumarate and ubiquinol. In addition, it can produce significant amounts of superoxide and hydrogen peroxide under the right conditions. While the flavin adenine dinucleotide (FAD) is the putative site of reactive oxygen species production, free radical production from other sites are less certain. Herein, we developed a computational model to analyze free radical production data from complex II and identify the mechanism of superoxide and hydrogen peroxide production. The model includes the major redox centers consisting of the FAD, three iron-sulfur clusters, and a transiently catalytic bound semi quinone. The model consists of five-states that represent oxidation status of the enzyme complex. Each step in the reaction scheme is thermodynamically constrained, and transitions between each state involve either one-electron or two-electron redox reactions. The model parameters were simultaneously fit using data consisting of enzyme kinetics and free radical production rates under a range of conditions. In the absence of respiratory chain inhibitors, model analysis revealed that the 3Fe-4S iron-sulfur cluster is the primary source of superoxide production followed by the FAD radical. However, when the quinone reductase site of complex II is inhibited or the quinone pool is highly reduced, superoxide production from the FAD site dominates at low succinate concentrations. In addition, hydrogen peroxide formation from the complex is only significant when these one of these conditions is met and the fumarate concentrations is in the low micromolar range. From the model simulations, the redox state of the quinone pool was found to be the primary determinant of free radical production from complex II. This study highlights the importance of evaluating enzyme kinetics and associated side-reactions in a consistent, quantitative and biophysical detailed manner. By incorporating the results from a diverse set of experiments, this computational approach can be used to interpret and explain key differences among the observations from a single, unified perspective. |
