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Using Ontology Reasoning to Classify Protein Phosphatases K.Wolstencroft, P.Lord, L.tabernero, A.brass, R.stevens University of Manchester Introduction Automated classification of proteins into protein subfamilies 1. 2. 3. 4. 5. Background Architecture Advantages Results Future directions Motivation Biological data production fast - High throughput techniques - Large numbers of species being sequenced - Large amount of data uncharacterised Data analysis is now the rate-limiting step Why Classify? • Classification and curation of a genome is the first step in understanding the processes and functions happening in an organism • Classification enables comparative genomic studies - what is already known in other organisms • The similarities and differences between processes and functions in related organisms often provide the greatest insight into the biology Protein Classification • Proteins divided into broad functional classes “Protein Families” - evolutionary relationships - common domain architecture • Relationship between sequence and structure allows searching for distinct structural (and functional) domains within the sequence • Domains could be several amino acids long – or could span most of the protein Example A search of the linear sequence of protein tyrosine phosphatase type K – identified 9 functional domains >uniprot|Q15262|PTPK_HUMAN Receptor-type protein-tyrosine phosphatase kappa precursor (EC 3.1.3.48) (R-PTP-kappa). MDTTAAAALPAFVALLLLSPWPLLGSAQGQFSAGGCTFDDGPGACDYHQDLYDDFEWVHV SAQEPHYLPPEMPQGSYMIVDSSDHDPGEKARLQLPTMKENDTHCIDFSYLLYSQKGLNP GTLNILVRVNKGPLANPIWNVTGFTGRDWLRAELAVSSFWPNEYQVIFEAEVSGGRSGYI AIDDIQVLSYPCDKSPHFLRLGDVEVNAGQNATFQCIATGRDAVHNKLWLQRRNGEDIPV……….. Protein Family Classification • Often diagnostic domains/motif signify family membership e.g. ALL proteins with a tyrosine protein kinase-specific active site (IPR008266) domain are types of tyrosine kinase Current Techniques • Human expert classification – gold standard – human knowledge applied to results from bioinformatics analysis tools • Automated use of bioinformatics analysis tools – quick – less detailed Automated Methods Bioinformatics analysis tools • top BLAST hit - annotating as ‘similar to’ other known proteins - Could result in protein A is similar to protein B, which is similar to protein C, which is similar to protein D etc, etc, • Interpro Scan analysis - shows number and types of domains, but does not provide interpretations Human Expert Annotation • Same similarity searching tools used for domain/motif identification • Humans use expert knowledge to classify proteins according to domain arrangements Presence / order / number of each important Can an ontology be used to capture this knowledge to the standard of a human annotator? Ontology Approach • Use ontology to capture the ‘rules’ for protein family membership in formal OWL representation • Ontology contains the human expert knowledge • Ontology reasoning can take the place of human analysis of the data The Protein Phosphatases • large superfamily of proteins – involved in the removal of phosphate groups from molecules • Important proteins in almost all cellular processes • Involved in diseases – diabetes and cancer • human phosphatases well characterised Phosphatase Functional Domains Andersen et al (2001) Mol. Cell. Biol. 21 7117-36 Determining Class Definitions R5 - Contains 2 protein tyrosine phosphatase domains - Contains 1 transmembrane domain - Contains 1 fibronectin domains - Contains 1 carbonic anhydrase Protégé OWL Modelling Requirements • Extract phosphatase sequences from rest of protein sequences from a whole genome • Identify the domains present in each • Compare these sequences to the formal ontology descriptions • Classify each protein instance to a place in the hierarchy Architecture OWL DL ontology Raw protein myGrid Instance Classified Protein sequences Services Store Phosphatases Reasoner (racer) myGrid Services • extract protein phosphatase sequences from whole genome using simple filtering – patmatdb EMBOSS tool used to extract proteins with phosphatase diagnostic motifs • perform InterproScan to determine domain architecture • transform the InterproScan results into abstract OWL instance descriptions InterproScan Results Conversion to abstract OWL format restriction(<http://www.owlontologies.com/unnamed.owl#containsDomainIPR00034 0> cardinality(1)) restriction(<http://www.owlontologies.com/unnamed.owl#containsDomainIPR00176 3> cardinality(1)) restriction(<http://www.owlontologies.com/unnamed.owl#containsDomainIPR00038 7> cardinality(1)) Instance Store • Instance Store enables reasoning over individuals • Can support much higher numbers of individuals • OWL ontology is loaded into the instance store • A DL reasoner (racer) is used to compare individuals to the OWL ontology definitions Instance Store Example Instances • Protein Individual Dual Specificity Phosphatase DUSE • Ontology Definition of Dual Specificity Phosphatase restriction(<http://www.owlontologies.com/unnamed.ow l#containsDomainIPR000340 > cardinality(1)) restriction(<http://www.owlontologies.com/unnamed.ow l#containsDomainIPR000387 > cardinality(1)) containsDomain IPR000340 Necessary and Sufficient for class membership Also inherits containsDomain IPR000387 from Parent Class PTP Results • Human phosphatases have been classified using the system • The ontology classification performed equally well as expert classification • The ontology system refined classification - DUSC contains zinc finger domain characterised and conserved – but not in classification - DUSA contains a disintegrin domain previously uncharacterised – evolutionarily conserved Aspergillus fumigatus • Phosphatase proteins very different from human >100 human <50 A.fumigatus • Whole subfamilies ‘missing’ Different fungi-specific phosphorylation pathways? No requirement for tissue-specific variations? • Novel serine/threonine phosphatase with homeobox conserved in aspergillus and closely related species, but not in any other - virulence Ongoing Work • Phosphatases in other genomes – Trypanosomes – Plasmodium falciparum • Other protein families – Ion Channels – ABC transporters – Nuclear receptors Conclusions • Using ontology allows automated classification to reach the standard of human expert annotation • Reasoning capabilities allow interpretation of domain organisation • Highlights anomalies and variations from what is known • Allows fast, efficient comparative genomics studies Acknowledgements PhD Supervisors: Andy Brass, Robert Stevens Group: myGrid, Phil Lord, Carole Goble Phosphatase Biologist: Lydia Tabernero Medical Research Council