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Architect: a tool for producing high-quality metabolic models through improved enzyme annotation

Nirvana Nursimulu, Alan M. Moses, John Parkinson
doi: https://doi.org/10.1101/2021.10.12.464133
Nirvana Nursimulu
1Department of Computer Science, University of Toronto, Toronto, ON, Canada
2Program in Molecular Medicine, The Hospital for Sick Children, 21-9709 PGCRL, 686 Bay Street, Toronto, ON, Canada
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Alan M. Moses
1Department of Computer Science, University of Toronto, Toronto, ON, Canada
3Department of Cell & Systems Biology, University of Toronto, Toronto, ON, Canada
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John Parkinson
2Program in Molecular Medicine, The Hospital for Sick Children, 21-9709 PGCRL, 686 Bay Street, Toronto, ON, Canada
4Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
5Department of Biochemistry, University of Toronto, Toronto, ON, Canada
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  • For correspondence: john.parkinson@utoronto.ca
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Abstract

Motivation Constraints-based modeling is a powerful framework for understanding growth of organisms. Results from such simulation experiments can be affected at least in part by the quality of the metabolic models used. Reconstructing a metabolic network manually can produce a high-quality metabolic model but is a time-consuming task. At the same time, current methods for automating the process typically transfer metabolic function based on sequence similarity, a process known to produce many false positives.

Results We created Architect, a pipeline for automatic metabolic model reconstruction from protein sequences. First, it performs enzyme annotation through an ensemble approach, whereby a likelihood score is computed for an EC prediction based on predictions from existing tools; for this step, our method shows both increased precision and recall compared to individual tools. Next, Architect uses these annotations to construct a high-quality metabolic network which is then gap-filled based on likelihood scores from the ensemble approach. The resulting metabolic model is output in SBML format, suitable for constraints-based analyses. Through comparisons of enzyme annotations and curated metabolic models, we demonstrate improved performance of Architect over other state-of-the-art tools.

Availability Code for Architect is available at https://github.com/ParkinsonLab/Architect.

Contact john.parkinson{at}utoronto.ca

Supplementary information Supplementary data are available at Bioinformatics online.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/ParkinsonLab/Architect

  • http://compsysbio.org/projects/Architect

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted October 13, 2021.
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Architect: a tool for producing high-quality metabolic models through improved enzyme annotation
Nirvana Nursimulu, Alan M. Moses, John Parkinson
bioRxiv 2021.10.12.464133; doi: https://doi.org/10.1101/2021.10.12.464133
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Architect: a tool for producing high-quality metabolic models through improved enzyme annotation
Nirvana Nursimulu, Alan M. Moses, John Parkinson
bioRxiv 2021.10.12.464133; doi: https://doi.org/10.1101/2021.10.12.464133

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