Format

Send to

Choose Destination
See comment in PubMed Commons below
BMC Syst Biol. 2016 Mar 11;10:26. doi: 10.1186/s12918-016-0271-6.

Systems biology of the structural proteome.

Author information

  • 1Department of Bioengineering, University of California, La Jolla, San Diego, CA, 92093, USA.
  • 2Joint BioEnergy Institute, Emeryville, CA, 94608, USA.
  • 3Bioinformatics and Systems Biology Program, University of California, La Jolla, San Diego, CA, 92093, USA.
  • 4National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, 20894, USA.
  • 5Department of Systems Biology, Harvard Medical School, Boston, MA, 02115, USA.
  • 6Office of the Director, National Institutes of Health, Bethesda, MD, 20894, USA.
  • 7Department of Bioengineering, University of California, La Jolla, San Diego, CA, 92093, USA. palsson@eng.ucsd.edu.

Abstract

BACKGROUND:

The success of genome-scale models (GEMs) can be attributed to the high-quality, bottom-up reconstructions of metabolic, protein synthesis, and transcriptional regulatory networks on an organism-specific basis. Such reconstructions are biochemically, genetically, and genomically structured knowledge bases that can be converted into a mathematical format to enable a myriad of computational biological studies. In recent years, genome-scale reconstructions have been extended to include protein structural information, which has opened up new vistas in systems biology research and empowered applications in structural systems biology and systems pharmacology.

RESULTS:

Here, we present the generation, application, and dissemination of genome-scale models with protein structures (GEM-PRO) for Escherichia coli and Thermotoga maritima. We show the utility of integrating molecular scale analyses with systems biology approaches by discussing several comparative analyses on the temperature dependence of growth, the distribution of protein fold families, substrate specificity, and characteristic features of whole cell proteomes. Finally, to aid in the grand challenge of big data to knowledge, we provide several explicit tutorials of how protein-related information can be linked to genome-scale models in a public GitHub repository ( https://github.com/SBRG/GEMPro/tree/master/GEMPro_recon/).

CONCLUSIONS:

Translating genome-scale, protein-related information to structured data in the format of a GEM provides a direct mapping of gene to gene-product to protein structure to biochemical reaction to network states to phenotypic function. Integration of molecular-level details of individual proteins, such as their physical, chemical, and structural properties, further expands the description of biochemical network-level properties, and can ultimately influence how to model and predict whole cell phenotypes as well as perform comparative systems biology approaches to study differences between organisms. GEM-PRO offers insight into the physical embodiment of an organism's genotype, and its use in this comparative framework enables exploration of adaptive strategies for these organisms, opening the door to many new lines of research. With these provided tools, tutorials, and background, the reader will be in a position to run GEM-PRO for their own purposes.

PMID:
26969117
PMCID:
PMC4787049
DOI:
10.1186/s12918-016-0271-6
[PubMed - in process]
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for BioMed Central Icon for PubMed Central
    Loading ...
    Support Center