4.8 Article

Recon3D enables a three-dimensional view of gene variation in human metabolism

Journal

NATURE BIOTECHNOLOGY
Volume 36, Issue 3, Pages 272-+

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/nbt.4072

Keywords

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Funding

  1. Novo Nordisk Foundation Center for Biosustainability
  2. Technical University of Denmark [NNF10CC1016517]
  3. National Institutes of Health [GM057089]
  4. Luxembourg National Research Fund (FNR) through the National Centre of Excellence in Research (NCER) on Parkinson's disease
  5. Luxembourg National Research Fund (FNR) through the ATTRACT programme [FNR/A12/01]
  6. European Union [668738]
  7. Institutional Strategy of the University of Tubingen (German Research Foundation DFG) [ZUK 63]
  8. Google Inc.
  9. National Science Foundation [NSF DBI-1338415]
  10. Department of Energy
  11. National Institutes of Health (NIGMS)
  12. National Institutes of Health (NCI)
  13. NNF Center for Biosustainability [Network Reconstruction, Yeast Cell Factories, Genome Scale CHO in Silico Models] Funding Source: researchfish
  14. Novo Nordisk Fonden [NNF10CC1016517] Funding Source: researchfish

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Genome-scale network reconstructions have helped uncover the molecular basis of metabolism. Here we present Recon3D, a computational resource that includes three-dimensional (3D) metabolite and protein structure data and enables integrated analyses of metabolic functions in humans. We use Recon3D to functionally characterize mutations associated with disease, and identify metabolic response signatures that are caused by exposure to certain drugs. Recon3D represents the most comprehensive human metabolic network model to date, accounting for 3,288 open reading frames (representing 17% of functionally annotated human genes), 13,543 metabolic reactions involving 4,140 unique metabolites, and 12,890 protein structures. These data provide a unique resource for investigating molecular mechanisms of human metabolism. Recon3D is available at http://vmh.life.

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