4.6 Article

Genomic-scale comparison of sequence- and structure-based methods of function prediction: Does structure provide additional insight?

Journal

PROTEIN SCIENCE
Volume 10, Issue 5, Pages 1005-1014

Publisher

COLD SPRING HARBOR LAB PRESS
DOI: 10.1110/ps.49201

Keywords

disulfide oxidoreductase; fuzzy functional forms (FFFs); protein function prediction; oligosaccharyltransferase (OST); OST3; OST6; N33; structural genomics

Funding

  1. NIGMS NIH HHS [GM48835, R01 GM048835] Funding Source: Medline

Ask authors/readers for more resources

A function annotation method using the sequence-to-structure-to-function paradigm is applied to the identification of all disulfide oxidoreductases in the Saccharomyces cerevisiae genome. The method identifies 27 sequences as potential disulfide oxidoreductases. All previously known thioredoxins, glutaredoxins, and disulfide isomerases are correctly identified. Three of the 27 predictions are probable false-positives. Three novel predictions, which subsequently have been experimentally validated, are presented. Two additional novel predictions suggest a disulfide oxidoreductase regulatory mechanism for two subunits (OST3 and OST6) of the yeast oligosaccharyltransferase complex. Based on homology, this prediction can be extended to a potential tumor suppressor gene, N33, in humans, whose biochemical function was not previously known. Attempts to obtain a folded, active N33 construct to test the prediction were unsuccessful. The results show that structure prediction coupled with biochemically relevant structural motifs is a powerful method for the function annotation of genome sequences and can provide more detailed, robust predictions than function prediction methods that rely on sequence comparison alone.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available