深圳中恒华发股份有限公司.pptx

Lecture 4.11Protein InteractionsMichel DumontierBlueprint Initiativemjdumontblueprint.org http:/blueprint.org Lecture 4.12OutlineMolecular interactionsDiscoveryExperimentalComputationalStorageData MiningFuture DirectionsLecture 4.13Molecular InteractionsBetween two molecular objectsDNA,RNA,gene,protein,molecular complex,small molecule,photonBinding SitesUnder an Experimental ConditionWith a particular Cellular LocationPossibly causing some Chemical ActionBALecture 4.14Interaction DiscoveryExpression,Interaction Data,Function,Protein modificationsMicroarrayTwo-HybridMassSpectrometryGeneticsLecture 4.15A measure of confidence?How do you know if the interaction really exists?Each method has its advantages and disadvantages.Be aware of systematic errors(i.e.tag effects)Be aware of contaminating proteins.Each method observes interactions from a slightly different experimental condition.Support from many different sources is certainly better than just one.Lecture 4.16High-throughput Mass Spectrometric Protein Complex Identification(HMS-PCI)Ste12Ho et al.Nature.2002 Jan 10;415(6868):180-3Mike Tyers,SLRILecture 4.17FilteringRemove promiscuously binding proteins:Proteins identified by MS in control lanesProteins that were found at a high frequency in the overall experimentKnown high-abundant proteins ribosomal elementsLecture 4.19Synthetic Genetic InteractionsSynthetic genetic interactions(lethal,slow growth)Mate two mutants without phenotypes to get a daughter cell with a phenotypeSynthetic lethal(SL),slow growthrobotic mating using the yeast deletion libraryGenetic interactions provide functional data on protein interactions or redundant genesAbout 23%of known SLs(1295-YPD+MIPS)are known protein interactions in yeastTong et al.Science.2001 Dec 14;294(5550):2364-8Lecture 4.110Working overtimeCharlie Boones RobotsCell PolarityCell Wall Maintenance Cell StructureMitosisChromosome StructureDNA Synthesis DNA RepairUnknownOthersSynthetic Genetic Interactions in YeastTong,BooneLecture 4.112PreBIND Literature MiningPreBIND is a data mining tool that helps researchers locate biomolecular interaction information in the scientific literature.Start with a protein name or accession find abstracts with significant interaction information.Ranked list of potential interactors based on the number of high-scoring abstracts found and SVM score.Information is only available for yeast,mouse and human proteins described by NCBI RefSeq identifiersDonaldson et al.PreBIND and Textomy-mining the biomedical literature for protein-protein interactions using a support vector machine.BMC Bioinformatics.2003 Mar 27;4(1):11.Lecture 4.113Search PreBIND with“Chk1”Lecture 4.114View Possible InteractionsLecture 4.115View the abstractLecture 4.116Lecture 4.117Confirm and submit a BIND InteractionLecture 4.118Computational Interaction PredictionBy HomologyIf A and B interact andC is homologous to A and D is homologous to BDo C and D interact?Transitive property They may,ifC&D are from the same species unless host-pathogen interactionBinding surface is conservednote domain interactionsBinding residues are conserved Localize to the same cellular compartmentLecture 4.119OutlineMolecular interactionsDiscoveryStorageDatabasesFile FormatsData MiningFuture DirectionsLecture 4.120Information ScopeDBEvolutionary BiologyBiochemistryClinical StudiesChemistryBiophysicsBioinformaticsPharmacologyPopulation BiologyProteomicsEpidemiologyMolecular BiologyImmunologyGenomicsGeneticsLecture 4.121A free,open-source database for archiving and exchanging molecular assembly information.BIND is managed by the Blueprint Initiative at Mount Sinai Hospital in Toronto.The database contains Interactions/ReactionsMolecular complexesPathwaysBIND has an extensive data model,GNU software tools and is based on the NCBI toolkit;extended recently to XML/JavaThe 97000 BIND records are curated and validated.http:/bind.caBader GD,Betel D,Hogue CW.(2003)BIND:the Biomolecular Interaction Network Database.Nucleic Acids Res.31(1):248-50 PMID:12519993 Lecture 4.122Browse Interface(v2.5)Lecture 4.123BIND Submit Record View(v3.0)Lecture 4.124Publication LinksLecture 4.125OntoglyphsLecture 4.126Gene OntologyFunctional protein annotationhttp:/www.geneontology.org Controlled vocabulary for protein function and localizationMolecular function e.g.DNA helicaseBiological process e.g.mitosisCellular Component e.g.nucleusLecture 4.127BIND Interaction Viewer 3.0Lecture 4.128Database of Interacting Proteins(DIP)The DIP database catalogs experimentally determined interactions between proteins.It combines information from a variety of sources to create a single,consistent set of protein-protein interactions.The data stored within the DIP database were curated,both,manually by expert curators and also automatically using computational approaches that utilize knowledge about the protein-protein interaction networks extracted from the most reliable,core subset of the DIP data.44349 interactions from 107 organisms involving 17048 proteinsSalwinski L,Miller CS,Smith AJ,Pettit FK,Bowie JU,Eisenberg D(2004)The Database of Interacting Proteins:2004 update.NAR 32 Database issue:D449-51http:/dip.doe-mbi.ucla.eduCopyright 1999-2003 UCLAThe DIP database is the property of the Regents of the University of California.It is forbidden to redistribute,derivatize,or encapsulate the DIP in another database without permission from UCLA and David Eisenberg.Lecture 4.129DIP Search InterfaceLecture 4.130MINTMINT database v3.0.MINT is a relational database designed to store interactions between biological molecules.MINT focuses on experimentally verified protein interactions with special emphasis on proteomes from mammalian organisms.MINT consists of entries mined in the scientific literature by curators.The curated data can be analyzed in the context of the high throughput data and viewed graphically through the MINT Viewer.42534 Interactions with 18148 proteinsZanzoni A.,Montecchi-Palazzi L.,Quondam M.,Ausiello G.,Helmer-Citterich M.and Cesareni G.MINT:a Molecular INTeraction database.(2002)FEBS Letters,513(1);135-140.http:/mint.bio.uniroma2.it/mint Lecture 4.131MINT Record ViewLecture 4.132MINT Interaction ViewerLecture 4.133Other Interaction DatabasesMIPShttp:/mips.gsf.de/proj/yeast/tables/interaction/IntAct EBIs interaction databasehttp:/www.ebi.ac.uk/intact/Human Protein Interaction Databasehttp:/www.hpid.org/TRANSFAC transcription factorshttp:/www.gene- Repository for Interaction Sets(GRID)http:/biodata.mshri.on.ca/grid/servlet/IndexLecture 4.134Data Exchange File FormatsBIND http:/bind.ca Peer reviewed but closed process(Spec v3.1)ASN.1 or XML DTD/SchemaPSI-MI http:/ Peer reviewed,HUPO community standardWidely adoptedBioPax http:/www.biopax.org Community schema(Sloan Kettering,BioPathways Consortium)XML Schema,OWL,Protg and GKBSBMLWidely adopted for representing models of biochemical reaction networksLecture 4.135BINDASN.1(text)XMLFlat FileLecture 4.136MINT PSI level 1Lecture 4.137PSI Record FormatLecture 4.138BioPAXCollaborative effort to create a data exchange format for biological pathway data http:/www.biopax.org Lecture 4.139OutlineMolecular interactionsDiscoveryStorageData MiningGraph TheoryComparisonsVisualization ToolsFuture DirectionsLecture 4.140Integrated Data MiningDetermine new relationships between data.Identify non-obvious patternsStatistical clustering(e.g.microarray)Graph theoryLecture 4.141Graph TheoryVertex(node)EdgeCycle-5Directed Edge(Arc)Weighted Edge710We map molecular interaction networks to graphsLecture 4.142Useful Graph OperationsA graph can be treated as a set of vertices and edges:intersection,difference,unione.g.What is the intersection of my interaction set with all known published interactions?Filteringe.g.Give me all protein interactions where at least one partner is nuclear localizedOverall statisticse.g.Find the average number of interactions for cell cycle proteinsLecture 4.143k-coreA part of a graph where every node is connected to other nodes with at least k edges(k=0,1,2,3.)Highest k-core is a central most densely connected region of a graphRegions of dense connectivity may represent molecular complexesTherefore,high k-cores may be molecular complexesLecture 4.144k-coreBatagelj,V.,Mrvar,A.Lecture 4.145Spoke and Matrix ModelsVrp1(bait),Las17,Rad51,Sla1,Tfp1,Ypt7SpokeMatrixSimple modelUseful for data navigationTheoretical max.number of interactionsPossible ActualTopologyLecture 4.146Graph VisualizationVisualize the connectivity of a given list of interactionsLecture 4.147Graph Annotation ColouringGene Ontology Biological ProcessLecture 4.148Stand-Alone Visualization ToolsCytoscapeVisualize molecular interaction networks and integrate interactions with gene expression profiles and other state data.Data filters&custom plug-in architecture.http:/www.cytoscape.org/Osprey Visualization of complex interaction networksData enriched with Gene Ontology&GRID dbhttp:/biodata.mshri.on.ca/osprey/servlet/IndexPajekGeneral network analysis Used to analyze social,biological,web networkshttp:/vlado.fmf.uni-lj.si/pub/networks/pajek/Lecture 4.149Compare HMS-PCI to Other Large-scale Data SetsCo-Immunoprecipitation(CoIP)dataPopulation of complexes of unknown topologyWant to compare this data to pairwise interactionsMust model CoIP as pairwise interactionsLecture 4.150Literature BenchmarksManually curated collection of published interactions(not including large-scale experiments)MIPS-1353 interactionsPreBIND-1196YPD-2205Combined,non-redundant-3310Is HMS-PCI Better?Compare to comprehensive high-throughput yeast two-hybrid(HT-Y2H)Ito et al.Uetz et al.Each set compared to a literature benchmarkMIPS+PreBIND-1003 interactions with HMS-PCI baitsHMS-PCI finds 2-3x more benchmark interactions than HT-Y2HIto et al.PNAS 98 p4569 2001&Uetz et al.Nature 403 p623 2000Another Large-scale MS StudyHo et al.Nature.2002 Jan 10;415(6868):180-3Gavin et al.Nature.2002 Jan 10;415(6868):141-7Ho-more sensitiveAdded info.for 446 proteinsComparing Data SetsOnly 115 common baits(Ho 600;Gavin 587)Ho vs.Gavin(spoke)198 interactions,222 proteinsHo+Gavin(matrix-44,680 intx)vs.all HT-Y2H(5 data sets-5614 intx):304 interactions,388 proteinsHo+Gavin(matrix)vs.benchmark(2078 interactions involving Ho+Gavin baits):693 interactions,619 proteins-33%Conclusion:Interaction data is not saturatingHo et al.Nature.2002 Jan 10;415(6868):180-3Gavin et al.Nature.2002 Jan 10;415(6868):141-7Ho vs.Gavin(spoke)Analysis of Combined Data SetCombine Ho,Gavin,previously known data-Whats new?Find protein complexes by finding k-coresMCODE software by Gary Bader&Chris HogueLarge nucleolar complex with functional links to RNA processing,cell cycle controlNucleolus is the ribosome factory,but recently implicated in cell cycle control,RNA transport/processingAndersen et al.Curr Biol.2002 Jan 8;12(1):1-11Pre MSHoGavinUnion6-core6-core6-core9-coreInteraction can define function Lecture 4.157OutlineMolecular interactionsDiscoveryStorageData MiningFuture DirectionsLecture 4.158Systems BiologySystems biology is the study of living organisms in terms of their underlying network structure as a function of the interactions of individual molecular components.Since a“system can be anything from a gene regulatory network to a cell,a tissue,or an entire organism,this approach requires the use and development of novel high throughput,sensitive and reliable analytical methods for the identification and characterization of genes,and/or their products,based on function.Lecture 4.159Systems BiologyCurrent experimental methods such as mass spectrometry,microarray,NMR and microscopy will be instrumental in generating essential data that will require innovative computational approaches to manage and interpret the vast amounts of data required to understand complex biological systems.Lecture 4.160Space and Time resolved simulationsDorsal-Ventral Patterning in the Early Drosophila EmbryoMichaelis-Menten kineticsObserve dynamics of the network behaviorFor a simple transcription factor(TF)gene interaction TF+G G*,k1=binding coefficientG*+P-G*+P+nX,k2=transcription rate coefficientwhere P represents the RNA polymerase concentration,and X is the gene product concentration,n represents the number of X proteins per mRNA transcript The vertical scale is concentration in units of number of molecules.The horizontal coordinate is space,running from the ventral point to the dorsal point Each sample point represents a 10 micron bin.The total time course is,in physiological time,400 secshttp:/quad.bic.caltech.edu/kastner/drosophila.html Lecture 4.161E-CellE-Cell system is an object-oriented software suite for modeling,simulation,and analysis of large scale complex systems such as biological cellshttp:/www.e-cell.orgLecture 4.162Systems Biology WorkbenchThe Systems Biology Workbench(SBW)is a modular,broker-based,message-passing framework for simplified communication between applications that aid in research in systems biology.Support for Windows,FreeBSD and LinuxBidirectional CORBA-SBW gateway Collection of modules provided with the base distribution:Simple stochastic simulator An SBML-to-MATLAB ODE and Simulink file translator An SBML reader module A clipboard module for exchanging SBML models A Browser that outputs module interface definitions A simple plotting module for time-series data A generic simulation-control GUI interface http:/ Lecture 4.163ConclusionSystems Biology Requirements:Parts List(Integrated Sequence And Structure DB)Molecular Interactions List(Biomolecular+Kinetics)Cellular Localization&Initial ConcentrationsStochastic Simulation&Distributed computing infrastructureSystems Biology Deliverables:Prediction of presence/absence of molecular speciesEffect of environmental&chemical perturbationLecture 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