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Predicting protein function from domain content
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
2008 (English)In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 24, no 15, 1681-1687 p.Article in journal (Refereed) Published
Abstract [en]

MOTIVATION: Computational assignment of protein function may be the single most vital application of bioinformatics in the post-genome era. These assignments are made based on various protein features, where one is the presence of identifiable domains. The relationship between protein domain content and function is important to investigate, to understand how domain combinations encode complex functions.

RESULTS: Two different models are presented on how protein domain combinations yield specific functions: one rule-based and one probabilistic. We demonstrate how these are useful for Gene Ontology annotation transfer. The first is an intuitive generalization of the Pfam2GO mapping, and detects cases of strict functional implications of sets of domains. The second uses a probabilistic model to represent the relationship between domain content and annotation terms, and was found to be better suited for incomplete training sets. We implemented these models as predictors of Gene Ontology functional annotation terms. Both predictors were more accurate than conventional best BLAST-hit annotation transfer and more sensitive than a single-domain model on a large-scale dataset. We present a number of cases where combinations of Pfam-A protein domains predict functional terms that do not follow from the individual domains.

AVAILABILITY: Scripts and documentation are available for download at http://sonnhammer.sbc.su.se/multipfam2go_source_docs.tar

Place, publisher, year, edition, pages
2008. Vol. 24, no 15, 1681-1687 p.
Keyword [en]
Amino Acid Sequence, Computer Simulation, Models; Biological, Models; Chemical, Molecular Sequence Data, Protein Structure; Tertiary, Proteins/*chemistry/classification/*metabolism, Sequence Analysis; Protein/*methods, Structure-Activity Relationship
National Category
Bioinformatics and Systems Biology
Research subject
Biochemistry with Emphasis on Theoretical Chemistry
Identifiers
URN: urn:nbn:se:su:diva-14973DOI: 10.1093/bioinformatics/btn312ISI: 000257956600005PubMedID: 18591194OAI: oai:DiVA.org:su-14973DiVA: diva2:181493
Available from: 2008-11-12 Created: 2008-11-12 Last updated: 2017-12-13Bibliographically approved
In thesis
1. The relationship between orthology, protein domain architecture and protein function
Open this publication in new window or tab >>The relationship between orthology, protein domain architecture and protein function
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Lacking experimental data, protein function is often predicted from evolutionary and protein structure theory. Under the 'domain grammar' hypothesis the function of a protein follows from the domains it encodes. Under the 'orthology conjecture', orthologs, related through species formation, are expected to be more functionally similar than paralogs, which are homologs in the same or different species descended from a gene duplication event. However, these assumptions have not thus far been systematically evaluated.

To test the 'domain grammar' hypothesis, we built models for predicting function from the domain combinations present in a protein, and demonstrated that multi-domain combinations imply functions that the individual domains do not. We also developed a novel gene-tree based method for reconstructing the evolutionary histories of domain architectures, to search for cases of architectures that have arisen multiple times in parallel, and found this to be more common than previously reported.

To test the 'orthology conjecture', we first benchmarked methods for homology inference under the obfuscating influence of low-complexity regions, in order to improve the InParanoid orthology inference algorithm. InParanoid was then used to test the relative conservation of functionally relevant properties between orthologs and paralogs at various evolutionary distances, including intron positions, domain architectures, and Gene Ontology functional annotations.

We found an increased conservation of domain architectures in orthologs relative to paralogs, in support of the 'orthology conjecture' and the 'domain grammar' hypotheses acting in tandem. However, equivalent analysis of Gene Ontology functional conservation yielded spurious results, which may be an artifact of species-specific annotation biases in functional annotation databases. I discuss possible ways of circumventing this bias so the 'orthology conjecture' can be tested more conclusively.

Place, publisher, year, edition, pages
Stockholm: Department of Biochemistry and Biophysics, Stockholm University, 2011. 112 p.
Keyword
homology, orthology, paralogy, gene duplications, protein function prediction, low-complexity regions, protein domains, domain architecture evolution, introns, intron position conservation, orthology conjecture, domain grammar hypothesis
National Category
Bioinformatics and Systems Biology
Research subject
Biochemistry with Emphasis on Theoretical Chemistry
Identifiers
urn:nbn:se:su:diva-62152 (URN)978-91-7447-350-6 (ISBN)
Public defence
2011-10-24, Magnélisalen, Kemiska övningslaboratoriet, Svante Arrhenius väg 16 B, Stockholm, 14:00 (English)
Opponent
Supervisors
Note
At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 6: Epub ahead of print.Available from: 2011-10-02 Created: 2011-09-09 Last updated: 2011-10-06Bibliographically approved

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