Cryptotanshinone: an Encouraging Natural Compound for Treating Metabolic Diseases

Cryptotanshinone (CPT) is a bioactive diterpene quinone isolated from Salvia species and is particularly abundant in Salvia miltiorrhiza. Danshen, a traditional Chinese medicinal preparation derived from the dried roots of Salvia miltiorrhiza Bunge, has been used for centuries to treat diverse ailments, including metabolic disorders. However, the specific therapeutic potential of CPT alone in metabolic diseases remains largely underexplored. Metabolic disorders have nearly tripled over recent decades worldwide. Current estimates indicate that type 2 diabetes mellitus (T2DM) affects approximately 529 million individuals globally, while obesity impacts almost 600 million people. In the context of cardiovascular disease, researchers estimate a global burden of 523 million cases. Although these conditions often progress silently, they can lead to severe complications that drastically impair both the quality and life expectancy. Therefore, the search for effective and safe therapeutic strategies for metabolic diseases is imperative. This review aims to evaluate CPT therapeutic potential in metabolic diseases. It also highlights existing knowledge gaps and proposes future research directions. Additionally, we integrate an analysis of CPT’s chemical and physicochemical properties, as well as its pharmacokinetic profile. Several studies indicate that CPT may counteract some of the metabolic alterations in metabolic disorders, including insulin resistance, weight gain, and altered blood lipid levels. Its therapeutic potential appears to arise from its ability to modulate antioxidant, anti-inflammatory, and catabolic pathways, as well as the microbiome. The global prevalence of metabolic disease continues to increase. In this review, we synthesize current evidence on the effects of CPT in metabolic diseases, identify critical knowledge gaps and propose future research directions to more effectively harness its therapeutic potential in this context.