Translating Enzymology into Metabolic Regulation: The Case of the 2- Oxoglutarate Dehydrogenase Multienzyme Complex

Enzymes are catalysts designed to function in the metabolic networks of biological systems. This review shows mechanisms underlying chemical contribution to the biological system performance and adaptations in permanently changing environment. The catalyst is exemplified by the 2-oxoglutarate dehydrogenase complex irreversibly degrading a branch point metabolite 2-oxoglutarate at the crossroad of carbon, nitrogen and fat metabolism. According to the key metabolic position and multienzyme structure, the complex exhibits rich regulation, demonstrating main principles governing the catalysis within metabolic network. First, the catalyst kinetics is changed through the enzyme-ligand interactions affecting the catalyst structure. The ligands include both small molecules and proteins, affecting catalysis by binding either to active (coenzymes, substrates, products or inhibitors) or allosteric sites. Allostery enables enzymatic sensitivity to general cellular signals, transmitted, in particular, by second messengers (Ca2+), adenine nucleotide phosphorylation status or redox potential. Regulation of catalysis by heterologous protein-protein interactions helps organization of metabolic pathways. Secondly, different regulators may interact through the protein structure effecting synergistic or antagonistic relationships through combined conformational stabilization or competitive binding. The latter is supported by common structural elements, e.g. adenine moiety, present in a number of biologically essential molecules. Thirdly, cellular systems may control the enzymatic catalysis by posttranslational modifications which may either effect or disable catalysis. The inactivation may protect catalyst itself and/or surrounding medium under conditions of metabolic impairment. Thus, enzymology enables our predictive capacity regarding both the enzyme impact on general metabolism and response to the metabolic changes within cellular network. This paves the way to the knowledge-based design of pharmacological tools to perform metabolic regulation required for solving medical and bioengineering problems.