Our method enables candidate pathways to be ranked to determine which ones are best to engineer. The proposed ranking function can integrate data from different sources such as host compatibility for inserted genes, the estimation of steady-state fluxes from the genome-wide reconstruction of the organism’s metabolism, or the estimation of metabolite toxicity from experimental assays. We use several machine-learning tools in order to estimate enzyme promiscuity and reaction efficiency at each step of the identified pathways.

Pathway Enumeration

Modeling of the metabolic network was done by using directed hypergraphs, where reactions are represented by hyperedges that connect sets of vertices (the substrates) to disjoint sets of vertices (the products). By using the hypergraph formalism, we have implemented a retrosynthetic tool that enumerates all pathways starting from target compounds of interest to the chassis organism.

The RetroPath WebServer

These diverse techniques involved in the design of heterologous biosynthetic pathways have been integrated in a web server interface. The web server is currently only accessible for registered users. Please contact us if you plan to use it.