Three-dimensional reconstruction of protein networks provides insight into human genetic disease. Academic Article uri icon

Overview

MeSH

  • Computational Biology
  • Humans
  • Image Processing, Computer-Assisted
  • Mutation

MeSH Major

  • Genetic Diseases, Inborn
  • Metabolic Networks and Pathways
  • Protein Interaction Maps

abstract

  • To better understand the molecular mechanisms and genetic basis of human disease, we systematically examine relationships between 3,949 genes, 62,663 mutations and 3,453 associated disorders by generating a three-dimensional, structurally resolved human interactome. This network consists of 4,222 high-quality binary protein-protein interactions with their atomic-resolution interfaces. We find that in-frame mutations (missense point mutations and in-frame insertions and deletions) are enriched on the interaction interfaces of proteins associated with the corresponding disorders, and that the disease specificity for different mutations of the same gene can be explained by their location within an interface. We also predict 292 candidate genes for 694 unknown disease-to-gene associations with proposed molecular mechanism hypotheses. This work indicates that knowledge of how in-frame disease mutations alter specific interactions is critical to understanding pathogenesis. Structurally resolved interaction networks should be valuable tools for interpreting the wealth of data being generated by large-scale structural genomics and disease association studies.

publication date

  • January 15, 2012

has subject area

  • Computational Biology
  • Genetic Diseases, Inborn
  • Humans
  • Image Processing, Computer-Assisted
  • Metabolic Networks and Pathways
  • Mutation
  • Protein Interaction Maps

Research

keywords

  • Journal Article

Identity

Language

  • eng

PubMed Central ID

  • PMC3708476

Digital Object Identifier (DOI)

  • 10.1038/nbt.2106

PubMed ID

  • 22252508

Additional Document Info

start page

  • 159

end page

  • 164

volume

  • 30

number

  • 2