Warburg effect

Mutations in oncogenes and tumor suppressor genes can modify multiple signaling pathways and in turn cell metabolism, which facilitates tumorigenesis. The paramount hallmark of tumor metabolism is “aerobic glycolysis” or the Warburg effect, coined by Otto Warburg in 1926, in which cancer cells produce most of energy from glycolysis pathway regardless of whether in aerobic or anaerobic condition. Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside. The increased uptake of glucose is facilitated by the overexpression of several isoforms of membrane glucose transporters (GLUTs). Likewise, the metabolic pathways of glutamine, amino acid and fat metabolism are also altered. Recent trends in anti-cancer drug discovery suggests that targeting the altered metabolic pathways of cancer cells result in energy crisis inside the cancer cells and can selectively inhibit cancer cell proliferation by delaying or suppressing tumor growth.

MCE provides a unique collection of 3,737 compounds which cover various tumor metabolism-related signaling pathways. These compounds can be used for anti-cancer metabolism targets identification, validation as well anti-cancer drug discovery.

Glycolysis is a series of metabolic processes by which one molecule of glucose is catabolized to two molecules of pyruvate with a net gain of two ATP. Glycolysis takes place in 10 steps and catalyzed by a series of enzyme, such as hexokinase, Glucose-6-phosphate isomerase, Phosphofructokinase, etc. Glycolysis is used by all cells in the body for energy generation.

Most cancer cells exhibit increased glycolysis and use this metabolic pathway for generation of ATP as a main source of their energy supply. This phenomenon is known as the Warburg effect and is considered as one of the most fundamental metabolic alterations during malignant transformation. Because increased aerobic glycolysis is commonly seen in a wide spectrum of human cancers, development of novel glycolytic inhibitors as a new class of anticancer agents is likely to have broad therapeutic applications.

MCE provides a unique collection of 1,350 glycolysis compounds that mainly target hexokinase, glucokinase, enolase, pyruvate kinase, PDHK, etc. MCE Glycolysis Compound Library is a useful tool for glucose metabolism research and anti-cancer drug discovery.

Carbohydrate metabolism serves as a central hub for energy supply and biosynthesis in living organisms and plays a critical role in the onset and progression of various diseases. In recent years, studies have shown that tumor cells reprogram their energy metabolism through aerobic glycolysis (the Warburg effect) to support rapid proliferation. Immune cells also rely on specific carbohydrate metabolic pathways to regulate their activation and differentiation states, while disorders such as diabetes and metabolic syndrome arise directly from dysregulation of carbohydrate metabolism. In addition, enzymes and key metabolic nodes involved in carbohydrate metabolism have become important targets for drug discovery, and therapeutic strategies targeting glycolysis, the pentose phosphate pathway, and energy metabolism are continuously advancing the treatment of cancer and metabolic diseases. Therefore, systematic analysis of carbohydrate metabolic networks and their associated metabolites is of great significance for elucidating disease mechanisms and developing novel therapeutic approaches.

The MCE Carbohydrate Metabolism Metabolite Library is constructed based on classical carbohydrate metabolic pathways and contains 75 metabolites. It systematically integrates key metabolic networks, including glycolysis, the pentose phosphate pathway, the tricarboxylic acid (TCA) cycle, monosaccharide metabolism, and sugar acid interconversions. The library comprehensively covers core metabolic nodes from glucose uptake and utilization to energy production and biosynthesis, while also incorporating important upstream and downstream intermediates. It enables accurate representation of intracellular metabolic flux dynamics and is well suited for applications such as metabolic flux analysis, target validation, and mechanistic studies. Furthermore, it provides robust support for multi-omics integration and the development of precision intervention strategies.