Lovastatin is a potent hypercholesterolemic drug used for lowering blood cholesterol. Lovastatin acts by competitively inhibiting the enzyme, 3-hydroxy-3-methylglutaryl coenzyme A reductase involved in the biosynthesis of cholesterol. Commercially lovastatin is produced by a variety of filamentous fungi including Penicillium species, Monascus ruber and Aspergillus terreus as a secondary metabolite. Production of lovastatin by fermentation decreases the production cost compared to costs of chemical synthesis. In recent years, lovastatin has also been reported as a potential therapeutic agent for the treatment of various types of tumors and also play a tremendous role in the regulation of the inflammatory and immune response, coagulation process, bone turnover, neovascularization, vascular tone, and arterial pressure. This review deals with the structure, biosynthesis, various modes of fermentation and applications of lovastatin.

Microbial L-asparaginase occupies a prominent place among biocatalysts owing to their ability to catalyze the reaction that hydrolyze the asparagine molecule. Effect of various medium components on the production of L-asparaginase in submerged fermentation by Pectobacterium carotovorum was studied for optimal nutrient requirements. Six different media compositions were tested for the L-asparaginase production keeping fermentation conditions constant at temperature 30 °C, initial pH 7.0 and agitation speed of 120 rpm. Maximum intracellular and extracellular L-asparaginase activity was obtained in the medium containing tryptone, yeast extract, monosodium glutamate, K₂HPO₄ and L-asparagine. These medium components were further optimized by central composite experimental design using response surface methodology. Maximum intracellular and extracellular L-asparaginase activity of 2.282 U/mL and 0.587 U/mL were obtained respectively at the late logarithmic phase in optimized media. Unstructured kinetic models were used to describe the cell growth and product formation kinetics. The unstructured models predicted the cell growth and product formation profile accurately with high coefficient of determination.