data integration: the stitch database of protein-small molecule interactions
TRANSCRIPT
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Data integrationThe STITCH database of protein–small molecule interactions
Lars Juhl Jensen
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guilt by association
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functional associations
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Kuhn et al., Nucleic Acids Research, 2010
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parts lists
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>2.5 million proteins
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630 genomes
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many databases
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different formats
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model organism databases
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Ensembl
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RefSeq
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PubChem compounds
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>74,000 small molecules
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genomic context
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gene fusion
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Korbel et al., Nature Biotechnology, 2004
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conserved neighborhood
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operons
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Korbel et al., Nature Biotechnology, 2004
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bidirectional promoters
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Korbel et al., Nature Biotechnology, 2004
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phylogenetic profiles
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Korbel et al., Nature Biotechnology, 2004
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interaction data
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protein–small molecule
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in vitro binding assays
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protein–protein
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yeast two-hybrid
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affinity purification
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fragment complementation
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Jensen & Bork, Science, 2008
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genetic interactions
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Beyer et al., Nature Reviews Genetics, 2007
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gene coexpression
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many databases
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BindingDB
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CTDComparative Toxicogenomics Database
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DrugBank
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GLIDAGPCR-Ligand Database
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PDSP KiPsycoactive Drug Screening Program
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PharmGKBPharmacogenomics Knowledge Base
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BINDBiomolecular Interaction Network Database
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BioGRIDGeneral Repository for Interaction Datasets
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DIPDatabase of Interacting Proteins
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IntAct
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MINTMolecular Interactions Database
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HPRDHuman Protein Reference Database
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PDBProtein Data Bank
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GEOGene Expression Omnibus
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different formats
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different identifiers
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partially redundant
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curated knowledge
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complexes
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pathways
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Letunic & Bork, Trends in Biochemical Sciences, 2008
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high confidence
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many databases
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MIPSMunich Information center
for Protein Sequences
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Gene Ontology
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KEGGKyoto Encyclopedia of Genes and Genomes
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MetaCyc
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PIDNCI-Nature Pathway Interaction Database
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Reactome
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different formats
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different identifiers
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partially redundant
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text mining
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>10 km
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human readable
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not computer readable
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different names
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Reflect
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dictionary
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Pafilis, O’Donoghue, Jensen et al., Nature Biotechnology, 2009
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text corpus
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MEDLINE
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SGDSaccharomyces Genome Database
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The Interactive Fly
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OMIMOnline Mendelian Inheritance in Man
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co-mentioning
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NLPNatural Language Processing
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integration
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many data types
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not comparable
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variable quality
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spread over 630 genomes
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quality scores
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reproducibility
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von Mering et al., Nucleic Acids Research, 2005
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intergenic distances
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Korbel et al., Nature Biotechnology, 2004
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benchmarking
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calibrate vs. gold standard
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von Mering et al., Nucleic Acids Research, 2005
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raw quality scores
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probabilistic scores
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orthology transfer
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von Mering et al., Nucleic Acids Research, 2005
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combine all evidence
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Acknowledgments
Damian Szklarczyk
Andrea Franceschini
Michael Kuhn
Sune Frankild
Heiko Horn
Evangelos Pafilis
Milan Simonovic
Alexander Roth
Pablo Minguez
Tobias Doerks
Jean Muller
Manuel Stark
Samuel Chaffron
Chris Creevey
Philippe Julien
Jan Korbel
Berend Snel
Martijn Huynen
Reinhardt Schneider
Sean O’DonoghueChristian von Mering
Peer Bork
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Predicting novel targets for existing drugs using side effect information
Lars Juhl Jensen
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the problem
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new uses for old drugs
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drug–drug network
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shared target(s)
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chemical similarity
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Campillos & Kuhn et al., Science, 2008
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Campillos & Kuhn et al., Science, 2008
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similar drugs share targets
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only trivial predictions
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the idea
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chemical perturbations
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phenotypic readouts
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drug treatment
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side effects
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the hard work
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information on side effects
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no database
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package inserts
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Campillos & Kuhn et al., Science, 2008
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text mining
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side-effect ontology
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backtracking
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Campillos & Kuhn et al., Science, 2008
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manual validation
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SIDER
Kuhn et al., Molecular Systems Biology, 2010
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side-effect correlations
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Campillos & Kuhn et al., Science, 2008
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GSC weighting
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side-effect frequencies
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Campillos & Kuhn et al., Science, 2008
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raw similarity score
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Campillos & Kuhn et al., Science, 2008
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p-values
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Campillos & Kuhn et al., Science, 2008
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side-effect similarity
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chemical similarity
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Campillos & Kuhn et al., Science, 2008
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confidence scores
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reference set
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incomplete databases
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text mining
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manual validation
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MATADOR
Günther et al., Nucleic Acids Research, 2008
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Campillos & Kuhn et al., Science, 2008
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the results
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drug–drug network
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Campillos & Kuhn et al., Science, 2008
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categorization
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Campillos & Kuhn et al., Science, 2008
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20 drug–drug pairs
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in vitro binding assays
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Ki<10 µM for 11 of 20
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cell assays
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9 of 9 showed activity
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the future
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link side-effects to targets
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direct target prediction
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Acknowledgments
Monica Campillos
Michael Kuhn
Anne-Claude Gavin
Peer Bork
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larsjuhljensen