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J A Di Gennaro

Publications and source records attributed to J A Di Gennaro.

2 recordsLinked to original sources

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

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.

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Enhanced functional annotation of protein sequences via the use of structural descriptors.

In order to circumvent limitations of sequence based methods in the process of making functional predictions for proteins, we have developed a methodology that uses a sequence-to-structure-to-function paradigm. First, an approximate three-dimensional structure is predicted. Then, a three-dimensional descriptor of the functional site, termed a Fuzzy Functional Form, or FFF, is used to screen the structure for the presence of the functional site of interest (Fetrow et al., 1998; Fetrow and Skolnick, 1998). Previously, a disulfide oxidoreductase FFF was developed and applied to predicted structures obtained from a small structural database. Here, using a substantially larger structural database, we expand the analysis of the disulfide oxidoreductase FFF to the B. subtilis genome. To ascertain the performance of the FFF, its results are compared to those obtained using both the sequence alignment method BLAST and three local sequence motif databases: PRINTS, Prosite, and Blocks. The FFF method is then compared in detail to Blocks and it is shown that the FFF is more flexible and sensitive in finding a specific function in a set of unknown proteins. In addition, the estimated false positive rate of function prediction is significantly lower using the FFF structural motif, rather than the standard sequence motif methods. We also present a second FFF and describe a specific example of the results of its whole-genome application to D. melanogaster using a newer threading algorithm. Our results from all of these studies indicate that the addition of three-dimensional structural information adds significant value in the prediction of biochemical function of genomic sequences.

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