In biochemistry, a metabolic pathway is a linked series of chemical reactions occurring within a cell. The reactants, products, and intermediates of an enzymatic reaction are known as metabolites, which are modified by a sequence of chemical reactions catalyzed by enzymes. Advancements in metabolic engineering have enabled us to engineer and express enzymes and construct novel pathways for various applications including drug discovery and value-added biochemical production. Therefore, the vital problem is to design a pathway between two certain compounds.
Computational Pathway Design
Computational pathway design algorithms enumerate potential routes linking the two molecules, while often taking into consideration a multitude of criteria such as shortest route, minimal number of heterologous reactions, thermodynamic feasibility, and enzyme availability.
There are some pathway design tools with different criteria such as MRE(Metabolic Route Explorer) and Gil. The latter is made by the iGEM team Korea_U_Seoul in 2015. These tools are both useful to find potential routes linking the two molecules and rank the routes for various applications, but are not comprehensive enough to judge the practicability of those pathways. For instance, the route found by Gil with largest ATP production from L-Tyrosine to Naringenin is almost infeasible in thermodynamics, which get lower score than the 500th route in MRE. So it’s crucial to put several affecting factors into consideration.
Our aim is to develop a software to find better metabolic pathways with combining more critical factors which may influent the performance of pathway. Recently, we have developed an alpha version of our tool. This version ranks all the pathways with comprehensive consideration, including thermodynamic feasibility, material competition of heterologous reactions, atom conservation.
. David L. Nelson; Cox, Michael M. (2008).Lehninger principles of biochemistry (5th ed.). New York: W.H. Freeman. ISBN 978-0-7167-7108-1.
. Lin Wang, Satyakam Dash, Chiam Yu Ng, Costas D. Maranas. (2017). A review of computational tools for design and reconstruction of metabolic pathways. Synthetic and Systems Biotechnology 2 (2017) 243-252