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Conservation of Protein Domains Over Different Proteins02:26

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain.  Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to form...

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Gclust: trans-kingdom classification of proteins using automatic individual threshold setting.

Naoki Sato1

  • 1Department of Life Sciences, Graduate School of Arts and Sciences, University of Tokyo, Komaba, Meguro-ku, Tokyo, 153-8902, Japan. naokisat@bio.c.u-tokyo.ac.jp

Bioinformatics (Oxford, England)
|January 23, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces Gclust software for trans-kingdom protein clustering, overcoming sequence divergence and transit peptide challenges. It efficiently identifies homologous proteins across diverse organisms using novel similarity measures and organism counts.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Trans-kingdom protein clustering is challenging due to significant sequence divergence between eukaryotes and prokaryotes.
  • Organellar proteins possess transit sequences, further complicating cross-kingdom comparisons.
  • Large-scale protein clustering requires efficient heuristics to identify homologous proteins across divergent species.

Purpose of the Study:

  • To develop a method for efficient and accurate trans-kingdom protein clustering.
  • To address the challenges posed by sequence divergence and transit peptides in protein homology detection.
  • To construct comprehensive protein clusters encompassing a wide range of organisms.

Main Methods:

  • Utilized Gclust software for constructing minimal homolog groups via all-against-all BLASTP and single-linkage clustering.
  • Incorporated estimation of protein domain structures and exclusion of multi-domain proteins.
  • Explicitly considered transit peptides and employed an entropy-optimized organism count method for heuristic similarity threshold estimation.

Main Results:

  • Developed Gclust software capable of constructing protein clusters for up to 95 organisms.
  • The method successfully addressed sequence divergence and transit peptide issues in protein clustering.
  • Resultant protein clusters were evaluated using power law analysis, demonstrating their robustness.

Conclusions:

  • Gclust provides an effective solution for large-scale trans-kingdom protein clustering.
  • The developed heuristic methods enable accurate identification of homologous proteins across diverse taxa.
  • The software and associated data are publicly available, facilitating further research in comparative genomics.