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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
Summary
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.
- 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.