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Related Experiment Videos

Genomic-scale comparison of sequence- and structure-based methods of function prediction: does structure provide

J S Fetrow1, N Siew, J A Di Gennaro

  • 1Department of Molecular Biology, The Scripps Research Institute, La Jolla, California 92037, USA.

Protein Science : a Publication of the Protein Society
|April 24, 2001
PubMed
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This study introduces a novel method for identifying disulfide oxidoreductases in yeast genomes. The approach accurately identifies known enzymes and discovers new ones, advancing our understanding of cellular redox regulation.

Area of Science:

  • Genomics
  • Biochemistry
  • Structural Biology

Background:

  • Disulfide oxidoreductases are crucial for cellular redox homeostasis.
  • Accurate identification of these enzymes is essential for understanding cellular functions and diseases.
  • Genome-wide annotation of enzyme families remains a challenge.

Purpose of the Study:

  • To identify all disulfide oxidoreductases within the Saccharomyces cerevisiae genome.
  • To develop and validate a function annotation method based on the sequence-to-structure-to-function paradigm.
  • To discover novel disulfide oxidoreductases and their potential roles in cellular processes.

Main Methods:

  • Application of the sequence-to-structure-to-function paradigm for function annotation.
  • Bioinformatic analysis of the Saccharomyces cerevisiae genome.

Related Experiment Videos

  • Experimental validation of novel predictions.

    • Main Results:

    • Identification of 27 potential disulfide oxidoreductase sequences.
    • Correct identification of all known thioredoxins, glutaredoxins, and disulfide isomerases.
    • Discovery and experimental validation of three novel disulfide oxidoreductases.
    • Prediction of a regulatory role for OST3 and OST6 subunits in the oligosaccharyltransferase complex.
    • Homology-based extension of findings to the human N33 gene, a potential tumor suppressor.

    Conclusions:

    • Structure prediction coupled with biochemically relevant structural motifs offers a powerful and robust method for genome sequence function annotation.
    • This approach provides more detailed predictions than sequence comparison alone.
    • The study highlights the potential of computational methods in discovering novel enzyme functions and regulatory mechanisms.