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Related Experiment Videos

PEP: Predictions for Entire Proteomes.

Phil Carter1, Jinfeng Liu, Burkhard Rost

  • 1CUBIC, Department of Biochemistry and Molecular Biophysics, Columbia University, 650 West 168th Street BB217, New York, NY 10032, USA. carter@cubic.bioc.columbia.edu

Nucleic Acids Research
|January 10, 2003
PubMed
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The PEP database offers comprehensive predictions and annotations for entire proteomes across eukaryotes, prokaryotes, and archaea. It provides valuable insights into protein structures and functions, aiding biological research.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Proteomics

Background:

  • Protein sequence analysis is crucial for understanding biological functions.
  • A comprehensive database integrating diverse proteomic data is needed.
  • Existing databases may lack integrated analyses across all life kingdoms.

Purpose of the Study:

  • To create a comprehensive database of predictions for entire proteomes (PEP).
  • To provide integrated analyses and annotations for protein sequences from diverse organisms.
  • To facilitate access to proteomic data and derived structural information.

Main Methods:

  • Alignment of publicly available protein sequences against SWISS-PROT, TrEMBL, and PDB.
  • Generation of annotations including secondary structure, transmembrane helices, and functional classes.

Related Experiment Videos

  • Identification of proteins with regions lacking regular secondary structure.
  • Creation of a related database of structural domain-like fragments and homology clusters.

    • Main Results:

    • The PEP database provides extensive predictions and annotations for proteomes of eukaryotes, prokaryotes, and archaea.
    • Detailed annotations cover secondary structure, transmembrane helices, signal peptides, and functional classes.
    • A supplementary database of structural fragments and homology clusters derived from PEP is available.

    Conclusions:

    • The PEP database serves as a valuable, freely accessible resource for proteomic analysis.
    • Integrated data and derived structural fragments enhance the study of protein structure-function relationships.
    • The database is accessible via flat files and integrated into SRS for broad scientific use.