Protein Misprediction Uncovered By New Technique

Main Category: Biology / Biochemistry
Also Included In: IT / Internet / E-mail;  Genetics
Article Date: 28 Aug 2008 - 3:00 PDT

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A new bioinformatics tool is capable of identifying and correcting abnormal, incomplete and mispredicted protein annotations in public databases. The MisPred tool, described in the open access journal BMC Bioinformatics, currently uses five principles to identify suspect proteins that are likely to be abnormal or mispredicted.

Laszlo Patthy led a team from the Institute of Enzymology of the Hungarian Academy of Sciences, Budapest, that developed this new approach. He explained how necessary it is, "Recent studies have shown that a significant proportion of eukaryotic genes are mispredicted at the transcript level. As the MisPred routines are able to detect many of these errors, and may aid in their correction, we suggest that it may significantly improve the quality of protein sequence data based on gene predictions". The MisPred approach promises to save much time and effort that would otherwise be spent in further investigation of erroneously identified genes.

The MisPred approach rates annotations according to five dogmas:

1. Extracellular or transmembrane proteins must have appropriate secretory signals.
   
   
2. A protein with intra- and extra-cellular parts must have a transmembrane segment.
   
   
3. Extracellular and nuclear domains must not occur in a single protein.
   
   
4. The number of amino acid residues in closely related members of a globular domain family must fall into a relatively narrow range.
   
   
5. A protein must be encoded by exons located on a single chromosome.

There are some exceptions to these rules, as pointed out by Patthy, "Some secreted proteins may truly lack secretory signal peptides since they are subject to leaderless protein secretion. Similarly, it cannot be excluded at present that transchromosomal chimeras can be formed and may have normal physiological functions. Nevertheless, the fact that MisPred analyses of protein sequences of the Swiss-Prot database identified very few such exceptions indicates that the rules of MisPred are generally valid".

The authors found that the absence of expected signal peptides and violation of domain integrity account for the majority of mispredictions. The authors note that "Interestingly, even the manually curated UniProtKB/Swiss-Prot dataset is contaminated with mispredicted or abnormal proteins, although to a much lesser extent than UniProtKB/TrEMBL or the EnsEMBL or GNOMON predicted entries".

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Notes:

1. Identification and correction of abnormal, incomplete and mispredicted proteins in public databases Alinda Nagy, Hedi Hegyi, Krisztina Farkas, Hedvig Tordai, Evelin Kozma, Laszlo Banyai and Laszlo Patthy
BMC Bioinformatics
Article available at the journal website: http://www.biomedcentral.com/bmcbioinformatics/
All articles are available free of charge, according to BioMed Central's open access policy.

2. BMC Bioinformatics is an open access journal publishing original peer-reviewed research articles in all aspects of computational methods used in the analysis and annotation of sequences and structures, as well as all other areas of computational biology. BMC Bioinformatics (ISSN 1471-2105) is indexed/tracked/covered by PubMed, MEDLINE, BIOSIS, CAS, Scopus, EMBASE, Thomson Reuters (ISI) and Google Scholar. 3.

BioMed Central (http://www.biomedcentral.com/) is an independent online publishing house committed to providing immediate access without charge to the peer-reviewed biological and medical research it publishes. This commitment is based on the view that open access to research is essential to the rapid and efficient communication of science.

Source: Graeme Baldwin
BioMed Central

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