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SABIO-RK Making Reaction Kinetics Data Accessible Martin Golebiewski

SABIO-RK Making Reaction Kinetics Data Accessible Martin Golebiewski EML Research, Heidelberg, Germany. Biochemical Pathways. Kinetic Law:. Kinetic Parameters:. V m = Maximum velocity. K m = Michaelis Constant. Enzyme Kinetics. Calculation of reaction rates:.

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SABIO-RK Making Reaction Kinetics Data Accessible Martin Golebiewski

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  1. SABIO-RK Making Reaction Kinetics Data Accessible Martin Golebiewski EML Research, Heidelberg, Germany

  2. Biochemical Pathways

  3. Kinetic Law: Kinetic Parameters: Vm =Maximum velocity Km = Michaelis Constant Enzyme Kinetics Calculation of reaction rates: e.g. Michaelis-Menten Kinetics

  4. Kinetic Data: Database Resources BRENDA http://www.brenda.uni-koeln.de/ Comprehensive list of kinetic parameters based on literature information UniProt Knowledgebase/Swiss-Prot http://www.expasy.org/ Represents kinetic parameters in comment lines of proteins (new feature) BioModels Database http://www.ebi.ac.uk/biomodels/ Stores published mathematical models of biological interests

  5. We need an accessible database that merges this information for published kinetic data Why Another Kinetics Database ? • Kinetic parameter values depend on environmental conditions (temperature, pH, concentrations, experimental assay, etc.) • Parameters only interpretable with their corresponding kinetic laws • None of the databases links experimental kinetic parameter data for single reactions to complete sets of information comprising- Kinetic Law for the reaction rate- Environmental conditions- Concentrations of reactants and modifiers- Data source (original publication)- Organism, tissue and cellular location • Kinetic Data must be easily accessible and interchangeable

  6. Extraction SABIO-RK Kinetic Data (publ.) Concentrations Reactants Kinetic Law Environment Parameters SABIO-RK: Database population SABIO-RK describes Reaction Kinetics and is an extension of SABIO (System for the Analysis of Biochemical Pathways) KEGG SABIO UniProt Other DBs Enzymes Organisms Reaction Pub Reactants Pathways

  7. Curators verify and complete the data and check it for consistency Information to unify the data SABIO-RK / SABIO Integration into a relational database (Oracle) Data structuring SABIO-RK: Database populationWorkflow Kinetic data manually extracted from literature by students Intermediate SQL database Input interface

  8. SABIO-RK: Database population Curation Problems • Information missing in publications about assay proceedings, experimental conditions or complete reactions (with all reactants) • Synonymic or aberrant notations of compounds and enzymes: - different nomenclature systems used - commonly used trivial names vs. systematic names - functional classification of enzymes vs. physical enzyme proteins (e.g. only 1 EC-class for hundreds of protein kinases) • Multiplicity of parameter units: - mass or molar concentrations (mg/ml vs. mmol/l) - different systems (e.g. katal, unit or mol/min for enzymatic activity) - enzyme activities can be specific (unit/mg) or absolute (unit) - different scales (e.g. M, mM, µM, nM)

  9. SABIO-RK: Database population Statistics • 20 students extracting kinetic data from literature • 3 curators verifying and inserting data into SABIO-RK • 735 publications entered by students (7180 entries for 1900 reactions) • Integrated in SABIO-RK: ~ 4500 Entries (38% with kinetic law equation) ~ 1000 Different reactions (in 170 organisms) ~ 300 Different enzymes (EC classes) ~ 11300 Kinetic parameters: 4014 Km and similar 3666 kcat and Vmax 852 Ki (inhibitor constants)

  10. SABIO-RK

  11. SABIO-RK: User interface • Web-accessible and freely available for academic users • Users can query SABIO-RK by specifying - reactants, enzymes and/or pathways - organisms, tissues and cellular locations - experimental conditions (pH, temperature) • Links to other databases: - SwissProt (for protein information about enzymes) - PubMed (to refer to original publication) • System supports export of the selected kinetic data in SBML (Systems Biology Mark-up Language) format

  12. Aldolase reaction SABIO-RK: SBML output Glycolysis reactions

  13. SABIO-RK: Future Perspectives • Extension of search functions in the user interface e.g. find pathway from one compound to another • Expansion of the data export functions in the user interface Information very limited that can be exported in SBML format • Description of the detailed mechanism of the reactions e.g. elementary steps with corresponding rate constants • Annotation to other hierarchy levels (building ontologies) e.g. integration of classification tools for chemical compounds • Annotation to other databases and usage of controlled vocabulary e.g. BioModels, ChEBI, KEGG, UniProt/SwissProt

  14. SABIO-RK: Future Perspectives • (Semi-)Automatic extraction of kinetic data by text mining tools Problems: - Publications containing kinetic data have to be identified - Most of kinetic data found in tables, graphs or figures - Reaction formulas and kinetic law equations are mainly pictures - Automatic annotation of compounds, parameters, etc. is difficult Manual data extraction might help to find rules for text mining. • SABIO-RK as platform for experimental kinetic data - Scientists producing the data can directly enter it into SABIO-RK - All the needed information can be given by the experimenters - No data lost or questionable because of missing information

  15. Summary • SABIO-RK is a web-accessible database containing biochemical reaction kinetics data for systems biologists and experimenters • Merges general reaction information retrieved from other databases and kinetic data manually extracted from literature • High degree of interrelation (all necessary information is linked) • Type of kinetics, modes of inhibition or activation and corresponding equations are shown with their parameters, measured values and experimental conditions • Kinetic data can be exported in SBML file format • http://sabio.villa-bosch.de/SABIORK

  16. Acknowledgements • Scientific Databases and Visualization Group: • Renate Kania and Ulrike Wittig (database curators) • Andreas Weidemann (programming: input interface, SQL database) • Olga Krebs (database administration) • Saqib Mir (programming: user interface, web-services) • Isabel Rojas (programming and trying to organize all this) • all our students entering the data • For helpful discussions: • Ursula Kummer, Sven Sahle, Ralph Gauges (BCB-Group) • Rebecca Wade and Matthias Stein (MCM-Group) Thank you !

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