Pharmaceutical Knowledge retrieval through Reasoning of ChEMBL RDF
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This document discusses knowledge retrieval from the ChEMBL database of bioactive compounds for pharmaceutical research. It summarizes how semantic web techniques like RDF and SPARQL can be used to link and query ChEMBL data, as well as other linked data sources, to discover relationships and access additional information. Examples of SPARQL queries to ChEMBL are provided. The document concludes that these techniques contribute to drug discovery by enabling efficient access and use of pharmaceutical data from ChEMBL and beyond.
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SureChEMBL and Open PHACTS
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Overview of SureChEMBL
Overview of the SureChEMBL system and web interface.
https://www.surechembl.org/search/
SureChEMBL is a freely available web resource for chemistry patent searching. It is based on a fully automatic and dynamic text and image mining pipeline.
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- 1. Pharmaceutical Knowledge Retrieval through Reasoning of ChEMBL RDF Background and Status Reporting Annsofie Andersson Master thesis at the department of pharmaceutical bioscience 2010-03-04
- 2. How is available pharmaceutical data from ChEMBL reached in an efficient way and in what way may this data be used?
- 3. Importance of this research – Use of data + BCR ABL BCR-ABL Kinase Cancer cells proliferate
- 4. Importance of this research – Use of data Cancer cells can’t proliferate Imatinib BCR-ABL Kinase + Inhibition
- 5. Use of data MoSS- Molecular Substructure Mining Run Moss on: 1. On bioactive compounds between two protein families 2. On active and inactive compounds in one protein family
- 6. Available data ChEMBL A database of bioactive and drug-like compounds http://www.ebi.ac.uk/chembl/ Kinase SARfari A chemogenomic database built around Kinase families http://www.sarfari.org/kinasesarfari/ Target proteins, Affinities with corresponding activity measures, Assays, Compounds, Pubmeds, Uniprot
- 7. Knowledge retrieval – Why were these technique chosen? Tool Semantic Web - Discover relations - Linking data Data Model RDF - Set of relationships - Resources (URI) Query Langugage SPARQL - Independent of RDF formats The Semantic Web - on the respective Roles of XML and RDF Stefan Decker1, Frank van Harmelen3,4, Jeen Broekstra4 Michael Erdmann5, Dieter Fensel3, Ian Horrocks 2, Michel Klein3, Sergey Melnik 1
- 8. Knowledge retrieval – Why Linking data? Look at other knowledge bases to Retrieve data that ChEMBL don’t contain… pathways chebi information taxonomy … Bio2RDF, Dbpedia, DrugBank, etc
- 9. ?v = variable a = rdf:type
- 10. Usage of data - Request from Martin WHERE { ?act chembl:type amp;quot;IC50amp;quot; ; chembl:onAssay ?ass; chembl:forMolecule ?mol; chembl:standardValue ?val; chembl:standardUnits ?unit. ?mol blueobelisk:smiles ?SMILES. ?ass chembl:hasTarget <http://rdf.farmbio.uu.se/chembl/target/t10885> ; chembl:hasConfScore ?conf. }"; var forQSAR = "PREFIX dc: <http://purl.org/dc/elements/1.1/>PREFIX chembl: <http://rdf.farmbio.uu.se/chembl/onto/#>PREFIX blueobelisk: <http://www.blueobelisk.org/chemistryblogs/>SELECT DISTINCT ?act ?ass ?conf ?mol ?SMILES ?val ?unit QSAR project- Activity + value, Assay, Confidence values, Molecule
- 11. Maris SELECT DISTINCT ?mol ?pubmed ?l6 ?l5 ?l4 ?target ?SMILES ?val ?seq http://rdf.farmbio.uu.se/chembl/molecule/ m248585 , http://bio2rdf.org/pubmed: 10411491 , CATIONIC, NA, VOLT, 2460, "MEQTVLVPPGPDSFNFFTRESLAAIERRIAEEKAKNPKPDKKD… http://rdf.farmbio.uu.se/chembl/target/ t10558 , O=C(NC1CCN(Cc2ccccc2)CC1)Nc3ccccc3, Martin SELECT DISTINCT ?mol ?act ?val ?unit ?ass ?conf ?SMILES http://rdf.farmbio.uu.se/chembl/molecule/ m207756 , http://rdf.farmbio.uu.se/chembl/activity/ a49416 , 33000, nM, Nc1ncnc2c1c(cn2C3CCC(O)C3)c4ccc(Oc5ccccc5)cc4, http://rdf.farmbio.uu.se/chembl/assay/ a152959 , 8^^http://www.w3.org/2001/XMLSchema-datatypesinteger URI’s
- 12. Conclusions Semantic web contributes to the discovery of (new)relations SPARQL enables querying against ChEMBL for pharmaceutical data ChEMBL holds information about bioactive compounds Together these parts contribute to the pharmaceutical drug discovery
- 13. Where next? How is available pharmaceutical data from ChEMBL reached in an efficient way and in what way may this data be used? Explore additional (available) data Develop precise queries for a certain cause Go further into the usage of retrieved data
- 14. Where next? Develop queries Accessing from all possible ways “ Premake” queries Wizard Visualize information Biological Networking Moss Manager Other languages A visit to the Mark Wilkinson group in Vancouver
- 15. Summary