RT Journal Article
SR Electronic
T1 Architect: a tool for producing high-quality metabolic models through improved enzyme annotation
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.10.12.464133
DO 10.1101/2021.10.12.464133
A1 Nursimulu, Nirvana
A1 Moses, Alan M.
A1 Parkinson, John
YR 2021
UL http://biorxiv.org/content/early/2021/10/13/2021.10.12.464133.abstract
AB 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.caSupplementary information Supplementary data are available at Bioinformatics online.Competing Interest StatementThe authors have declared no competing interest.