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3-D substructure search by transitive closure in AlphaFold database.

Hao Liu1, Aleksi Laiho1, Petri Törönen1

  • 1Organismal and Evolutionary Biology Research Program, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland.

Protein Science : a Publication of the Protein Society
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Summary
This summary is machine-generated.

ISS_ProtSci enhances protein structural similarity searches by integrating DaliLite and Foldseek, significantly improving the discovery of distantly related proteins and protein families.

Keywords:
DaliFoldseekPfamprotein spacesuperfamily

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Area of Science:

  • Structural bioinformatics
  • Computational biology
  • Protein science

Background:

  • Understanding protein structure-function relationships is key to biological research.
  • Existing tools struggle with identifying distant structural relationships in diverse protein families.

Purpose of the Study:

  • To introduce ISS_ProtSci, a Python package for advanced structural similarity searches in the AlphaFold Database.
  • To improve the recall and accuracy of detecting distantly related proteins compared to existing methods.

Main Methods:

  • Utilizes DaliLite for precise geometric structural comparisons.
  • Employs a transitive closure algorithm for iterative exploration of protein structural neighbors.
  • Integrates Foldseek for fast all-against-all comparisons, validated by DaliLite.
  • Annotates results with UniProtKB and Pfam data using hmmsearch for domain identification.

Main Results:

  • Achieved over 99% recall in identifying relevant proteins across 12 test cases.
  • Demonstrated superior performance over Foldseek, especially for structurally diverse protein families.
  • Uncovered previously unrecognized structural relationships, aiding protein family classification.

Conclusions:

  • ISS_ProtSci offers a robust and efficient solution for comprehensive protein structural similarity analysis.
  • The package improves the detection of evolutionary and functional links between proteins.
  • Provides valuable insights for protein family classification and functional annotation.