TY - JOUR
T1 - Pathway design using de novo steps through uncharted biochemical spaces
AU - Kumar, Akhil
AU - Wang, Lin
AU - Ng, Chiam Yu
AU - Maranas, Costas D.
N1 - Funding Information:
We acknowledge the inputs given by Anthony Burgard, Anupam Chowdhury, and Ali Khodayari at the various stages of idea creation, refinement, and realization. We gratefully acknowledge funding from the DOE (http://www.energy.gov/) grant no. DESC0008091, DOE's Center for Bioenergy Innovation (CBI), and NSF (http://www.nsf. gov/) award no. EEC-0813570. The funders had no role in the study design, data collection, and analysis, decision to publish, or preparation of the manuscript.
Publisher Copyright:
© 2017 The Author(s).
PY - 2018/12/1
Y1 - 2018/12/1
N2 - Existing retrosynthesis tools generally traverse production routes from a source to a sink metabolite using known enzymes or de novo steps. Generally, important considerations such as blending known transformations with putative steps, complexity of pathway topology, mass conservation, cofactor balance, thermodynamic feasibility, microbial chassis selection, and cost are largely dealt with in a posteriori fashion. The computational procedure we present here designs bioconversion routes while simultaneously considering any combination of the aforementioned design criteria. First, we track and codify as rules all reaction centers using a prime factorization-based encoding technique (rePrime). Reaction rules and known biotransformations are then simultaneously used by the pathway design algorithm (novoStoic) to trace both metabolites and molecular moieties through balanced bio-conversion strategies. We demonstrate the use of novoStoic in bypassing steps in existing pathways through putative transformations, assembling complex pathways blending both known and putative steps toward pharmaceuticals, and postulating ways to biodegrade xenobiotics.
AB - Existing retrosynthesis tools generally traverse production routes from a source to a sink metabolite using known enzymes or de novo steps. Generally, important considerations such as blending known transformations with putative steps, complexity of pathway topology, mass conservation, cofactor balance, thermodynamic feasibility, microbial chassis selection, and cost are largely dealt with in a posteriori fashion. The computational procedure we present here designs bioconversion routes while simultaneously considering any combination of the aforementioned design criteria. First, we track and codify as rules all reaction centers using a prime factorization-based encoding technique (rePrime). Reaction rules and known biotransformations are then simultaneously used by the pathway design algorithm (novoStoic) to trace both metabolites and molecular moieties through balanced bio-conversion strategies. We demonstrate the use of novoStoic in bypassing steps in existing pathways through putative transformations, assembling complex pathways blending both known and putative steps toward pharmaceuticals, and postulating ways to biodegrade xenobiotics.
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U2 - 10.1038/s41467-017-02362-x
DO - 10.1038/s41467-017-02362-x
M3 - Article
C2 - 29330441
AN - SCOPUS:85043307792
SN - 2041-1723
VL - 9
JO - Nature communications
JF - Nature communications
IS - 1
M1 - 184
ER -