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Updated: Dec 16, 2025

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The Genome3D Consortium for Structural Annotations of Selected Model Organisms.

Vaishali P Waman1, Tom L Blundell2, Daniel W A Buchan3

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|July 5, 2020
PubMed
Summary

The Genome3D consortium offers a unified portal for protein structure prediction and annotation across ten model organisms. This resource integrates multiple bioinformatics tools, aiding researchers in comparative analysis and understanding protein structure-function relationships.

Keywords:
AnnotationCATHFold recognitionFunction predictionHidden Markov modelHomology modelingProtein domainProtein familyProtein structure predictionProtein superfamilySCOPSuperfamily mapping

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Area of Science:

  • Structural Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Protein structure prediction and annotation are crucial for understanding biological function.
  • Existing resources are often fragmented, hindering comprehensive analysis.
  • The Genome3D consortium addresses this by integrating multiple prediction and annotation tools.

Purpose of the Study:

  • To create a common portal for accessing predicted protein models and annotations.
  • To compare structural classifications between CATH and SCOP databases.
  • To provide a consensus mapping of protein superfamilies.

Main Methods:

  • Integration of multiple protein structure prediction and annotation resources (CATH-Gene3D, DOMSERF, pDomTHREADER, PHYRE, SUPERFAMILY, FUGUE/TOCATTA, VIVACE).
  • Utilizing SCOP- and CATH-based protein domain assignments.
  • Comparative analysis of structural classifications from CATH and SCOP databases.

Main Results:

  • Development of a unified portal, Genome3D, for protein structure prediction and annotation.
  • Identification of 1429 consensus superfamilies through CATH/SCOP mapping.
  • Provision of structural annotations for ten model organisms, including Homo sapiens and E. coli.

Conclusions:

  • Genome3D serves as a valuable gateway for comparative assessment of protein structure predictions.
  • The resource facilitates broader perspectives on protein structure-function relationships in model organisms.
  • This collaborative effort enhances the accessibility and utility of protein structure data.