Periodic Reporting for period 1 - MetaQ (When enzymes join forces: unmasking a mitochondrial biosynthetic engine)
Okres sprawozdawczy: 2023-10-01 do 2026-03-31
The MetaQ project addresses these questions through the investigation of coenzyme Q (ubiquinone), a lipid-soluble redox-active molecule that plays a pivotal role in cellular metabolism. While coenzyme Q is widely recognized in commercial contexts, particularly in cosmetic and nutraceutical formulations, it is fundamentally a ubiquitous and indispensable component of biological systems. It functions as an essential electron carrier within the mitochondrial respiratory chain, enabling ATP production through oxidative phosphorylation. In addition, coenzyme Q acts as a potent antioxidant, protecting cellular membranes from oxidative stress. Perturbations in its biosynthetic pathway or cellular distribution have been implicated in a variety of pathological conditions, including neurodegenerative diseases, mitochondrial disorders, and cardiovascular dysfunctions. Given its biochemical complexity, essential physiological functions, and clinical relevance, the biosynthesis of coenzyme Q constitutes an exemplary model for investigating the spatial and temporal coordination of enzymatic processes. The MetaQ project aims to answer key mechanistic questions: How do enzymes within this pathway ensure efficient substrate channelling and minimize metabolic leakage? What molecular interactions prevent premature degradation of intermediates? And by what principles are specific enzymes selectively recruited to distinct metabolic networks?
These findings challenge the traditional perception of the cell as a homogeneous “soup of enzymes,” in which each catalytic protein functions independently. Instead, MetaQ has provided compelling evidence that metabolic processes are governed by higher-order organizational principles. Enzymes can physically associate, co-localize within subcellular domains, and coordinate their activities to achieve enhanced catalytic efficiency while minimizing wasteful or deleterious by-products. This concept offers important insights into how cellular metabolism attains both precision and adaptability, even under fluctuating physiological conditions. The results being obtained are also demonstrating that this fundamental knowledge on biochemical processes can advance the discovery of drugs and therapeutics. Using modern AI-based computational tools, our data have enabled the discovery of molecules able to interfere with coenzyme Q metabolism and a potential beneficial effect to halt tumour cells propagation.