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RepeatsDB in 2021: improved data and extended classification for protein tandem repeat structures.

Lisanna Paladin1, Martina Bevilacqua1, Sara Errigo1

  • 1Dept. of Biomedical Sciences, University of Padua, Via Ugo Bassi 58/B, Padua 35121, Italy.

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|November 25, 2020
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Summary

RepeatsDB 3.0 enhances protein tandem repeat classification using a hierarchical system that combines structural and sequence similarity. This update improves data organization and accessibility for researchers studying these ubiquitous protein structures.

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Area of Science:

  • Structural biology
  • Bioinformatics
  • Genomics

Background:

  • Protein tandem repeats are fundamental protein structures found across all life forms.
  • The increasing number of solved repeat structures necessitates advanced annotation and classification methods.
  • Existing databases require updates to manage and present complex repeat data effectively.

Purpose of the Study:

  • To introduce RepeatsDB 3.0, an updated database for classifying protein tandem repeat structures.
  • To present an extended, hierarchical classification scheme integrating structural and sequence-based features.
  • To improve data browsing and unify annotations for similar protein sequences.

Main Methods:

  • Developed a hierarchical classification system combining structural similarity (Class, Topology, Fold) with sequence similarity (Clan, Family).
  • Integrated repeat motif data with Pfam for enhanced classification.
  • Implemented improved browsing mechanisms for the classification hierarchy.
  • Introduced a UniProt-centric view for unifying annotations.

Main Results:

  • RepeatsDB 3.0 offers an extended classification scheme for protein tandem repeats.
  • The database now integrates structural and sequence-based classification levels.
  • Enhanced browsing and a UniProt-centric view improve data accessibility and organization.
  • The updated resource facilitates better analysis of protein tandem repeat structures.

Conclusions:

  • RepeatsDB 3.0 provides a more comprehensive and organized resource for protein tandem repeat structures.
  • The new classification scheme and features address the growing complexity and volume of structural data.
  • This updated database supports researchers in the extraction, organization, and distribution of specialized information on tandem repeats.