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Title: Pathway design using de novo steps through uncharted biochemical spaces

Abstract

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 show 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.

Authors:
 [1];  [2];  [2];  [2]
  1. Pennsylvania State Univ., University Park, PA (United States). The Huck Institutes of the Life Sciences
  2. Pennsylvania State Univ., University Park, PA (United States). Dept. of Chemical Engineering
Publication Date:
Research Org.:
Pennsylvania State Univ., University Park, PA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21); Natural Science Foundation
OSTI Identifier:
1526279
Grant/Contract Number:  
SC0008091; EEC-0813570
Resource Type:
Accepted Manuscript
Journal Name:
Nature Communications
Additional Journal Information:
Journal Volume: 9; Journal Issue: 1; Journal ID: ISSN 2041-1723
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; 59 BASIC BIOLOGICAL SCIENCES

Citation Formats

Kumar, Akhil, Wang, Lin, Ng, Chiam Yu, and Maranas, Costas D. Pathway design using de novo steps through uncharted biochemical spaces. United States: N. p., 2018. Web. doi:10.1038/s41467-017-02362-x.
Kumar, Akhil, Wang, Lin, Ng, Chiam Yu, & Maranas, Costas D. Pathway design using de novo steps through uncharted biochemical spaces. United States. doi:10.1038/s41467-017-02362-x.
Kumar, Akhil, Wang, Lin, Ng, Chiam Yu, and Maranas, Costas D. Fri . "Pathway design using de novo steps through uncharted biochemical spaces". United States. doi:10.1038/s41467-017-02362-x. https://www.osti.gov/servlets/purl/1526279.
@article{osti_1526279,
title = {Pathway design using de novo steps through uncharted biochemical spaces},
author = {Kumar, Akhil and Wang, Lin and Ng, Chiam Yu and Maranas, Costas D.},
abstractNote = {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 show 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.},
doi = {10.1038/s41467-017-02362-x},
journal = {Nature Communications},
number = 1,
volume = 9,
place = {United States},
year = {2018},
month = {1}
}

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