MPS - AN ARTIFICIALLY INTELLIGENT SOFTWARE SYSTEM FOR THE ANALYSIS AND SYNTHESIS OF METABOLIC PATHWAYS

The concepts of artificial intelligence have been applied for the development of a software system for metabolic pathway synthesis (MPS). An easily expandable data base system for storing enzyme and substance descriptions is used by a search algorithm for the identification of possible ways to interconvert carbon-carrying metabolites. A versatile screening capability permits the user to identify all pathways which contain or exclude any combination of enzymes, substrates, and/or products. Information provided by MPS can be used to predict on a qualitative basis the effects of adding or deleting enzymatic activities to or from the cellular environment, to classify pathways with respect to cellular regulation. MPS can be used subsequently to aid the identification of appropriate genotypes or genetic modifications that will redirect metabolism towards amplified production of desirable bioproducts. Two examples illustrating the capabilities of MPS are presented. In the first example, which considers the conversion of glucose 6-phosphate to pyruvate, MPS synthesized the classical catabolic pathways (EMP, pentose phosphate and ED) along with possible variations. A route for the biosynthesis of L-alanine that does not incorporate the enzyme alanine aminotransferase was revealed by MPS during synthesis of alternative pathways which produce L-alanine from pyruvate.