network analysis of proteomes peter andras school of computing science university of newcastle
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Network analysis of Network analysis of proteomesproteomes
Peter AndrasPeter AndrasSchool of Computing ScienceSchool of Computing Science
University of NewcastleUniversity of Newcastlepeter.andras@ncl.ac.ukpeter.andras@ncl.ac.uk
OverviewOverview IntroductionIntroductionThe dataThe dataNetwork analysisNetwork analysisProtein interaction networksProtein interaction networksAnalysis of protein interaction networksAnalysis of protein interaction networksComputational drug target discoveryComputational drug target discovery
MotivationMotivationSearch for new antibiotics, drugs for Search for new antibiotics, drugs for
genetic and prion diseasesgenetic and prion diseasesDestroying and restoring the functionality Destroying and restoring the functionality
of cellsof cellsHow to do this ?How to do this ?eXSys projecteXSys project
Cells – 1 Cells – 1
Cells – 2 Cells – 2
Analysing cellsAnalysing cellsAnalysing and understanding cells by Analysing and understanding cells by
analysing their protein interaction networkanalysing their protein interaction network Ideally: dynamic analysisIdeally: dynamic analysisSimplified version: static analysisSimplified version: static analysis
Proteomics dataProteomics dataYeast-two-hybrid dataYeast-two-hybrid dataGene co-expression based predicted dataGene co-expression based predicted dataOther experimental dataOther experimental data
Web databasesWeb databases DIP (Database of Interacting Proteins) – DIP (Database of Interacting Proteins) –
experimentally validated data, mostly for yeastexperimentally validated data, mostly for yeast STRING (Search Tool for the Retrieval of STRING (Search Tool for the Retrieval of
Interacting Genes/Proteins) – large amount of Interacting Genes/Proteins) – large amount of predicted data based on gene expression datapredicted data based on gene expression data
KEGG – metabolic cycle descriptionsKEGG – metabolic cycle descriptions EBI – Proteome – full proteomesEBI – Proteome – full proteomes Swiss – Prot – general protein informationSwiss – Prot – general protein information
Data collectionData collectioneXSys data management engineeXSys data management engineCollects and updates automatically data Collects and updates automatically data
from web databasesfrom web databasesExtracts information about protein Extracts information about protein
interactions and stores this in proprietary interactions and stores this in proprietary formatformat
Allows to get specific data about selected Allows to get specific data about selected proteins from web databasesproteins from web databases
NetworksNetworksGraphs: nodes and edgesGraphs: nodes and edges
Scale-free networksScale-free networks
Damaging scale-free networksDamaging scale-free networksRobustness to random damageRobustness to random damageHigh sensitivity to targeted damageHigh sensitivity to targeted damage
Important nodesImportant nodesHubs: high connectivity nodesHubs: high connectivity nodes
Bottlenecks: nodes connecting clustersBottlenecks: nodes connecting clusters
Other important nodesOther important nodesElementary cycle number of nodesElementary cycle number of nodesEffect of deletion on the characteristic Effect of deletion on the characteristic
polynomialpolynomial
Integrity measuresIntegrity measuresAverage minimum path length: how close Average minimum path length: how close
are in average the nodes of the graphare in average the nodes of the graph
Clustering coefficient: how densely Clustering coefficient: how densely clustered is the graphclustered is the graph
Number of isolated clustersNumber of isolated clusters
Other integrity measuresOther integrity measuresComparison of characteristic polynomials Comparison of characteristic polynomials
of the damaged and non-damaged of the damaged and non-damaged networksnetworks
Informational measuresInformational measures
Comparative integrity measuresComparative integrity measures Integrity measures calculated for well Integrity measures calculated for well
specified targeted damage or random specified targeted damage or random damagedamage
E.g., top 10% hub nodes deleted, average E.g., top 10% hub nodes deleted, average damage by 10% of randomly selected damage by 10% of randomly selected nodes deletednodes deleted
Network analysisNetwork analysisEvaluation and categorisation of nodesEvaluation and categorisation of nodes
Evaluation of damaging capacity of nodes Evaluation of damaging capacity of nodes and node combinationsand node combinations
Selection of nodes to achieve a desired Selection of nodes to achieve a desired level of damagelevel of damage
Protein interaction systemsProtein interaction systemsProtein interaction systems can be viewed Protein interaction systems can be viewed
as networksas networks
Static picture of the cell, ignores the Static picture of the cell, ignores the temporal activation of sub-networks of the temporal activation of sub-networks of the full protein interaction networkfull protein interaction network
Protein interaction networksProtein interaction networks
E. coli
P. aeruginosa
Analysis of protein interaction Analysis of protein interaction networks – 1 networks – 1
Protein interaction networks are scale-free Protein interaction networks are scale-free networks networks high sensitivity to targeted high sensitivity to targeted damage, low sensitivity to random damagedamage, low sensitivity to random damage
Earlier work shows that hub proteins are Earlier work shows that hub proteins are likely to be essential proteinslikely to be essential proteins
Analysis of protein interaction Analysis of protein interaction networks – 2networks – 2
Conjecture: graph theoretic network Conjecture: graph theoretic network integrity is related to functional integrity of integrity is related to functional integrity of the protein interaction systemthe protein interaction system
Objective: determine important nodes and Objective: determine important nodes and node combinations that can cause node combinations that can cause significant integrity damagesignificant integrity damage
Analysis of protein interaction Analysis of protein interaction networks – 3networks – 3
Lists of hubs, bottlenecks, elementary Lists of hubs, bottlenecks, elementary cycle nodes and other important nodescycle nodes and other important nodes
Calculation of comparative damage Calculation of comparative damage measuresmeasures
Analysis of protein interaction Analysis of protein interaction networks – 4networks – 4
Calculation of optimal combination of Calculation of optimal combination of nodes that have damage potential above a nodes that have damage potential above a pre-specified limitpre-specified limit
Cocktails of target proteins; blocking the Cocktails of target proteins; blocking the activity of target proteins causes activity of target proteins causes significant integrity damage to the protein significant integrity damage to the protein interaction networkinteraction network
Analysis of protein interaction Analysis of protein interaction networks – 5networks – 5
Checking potential targets for toxicityChecking potential targets for toxicity
BLAST comparison of targets with BLAST comparison of targets with important proteins of host organismimportant proteins of host organism
Selection of admissible targets and target Selection of admissible targets and target combinationscombinations
Protein network analysisProtein network analysiseXSys network analysis engineeXSys network analysis engine
Takes data files generated by the eXSys Takes data files generated by the eXSys data management enginedata management engine
Performs network analysis and generates Performs network analysis and generates suggested target protein cocktails of suggested target protein cocktails of admissible targetsadmissible targets
Analysis of B. subtilisAnalysis of B. subtilis
B. subtilis
Important nodes for B. subtilis – 1 Important nodes for B. subtilis – 1
Id Swiss-Prot Id
Protein Name Gene Name
Function
355 P35164
Sensor protein resE
RESE Member of the two-component regulatory system resd/rese involved in the global regulation of aerobic and anaerobic respiration. Probably phosphorylates resd.
378 P16497
Sporulation kinase A
KINA Phosphorylates the sporulation-regulatory proteins spo0a and spo0f. It also autophosphorylates in the presence of atp.
391 Q45614
Sensor protein yycG
YYCG Essential Member of the two-component regulatory system yycG/yycF involved in the regulation of the ftsAZ operon. Probably phosphorylates yycF.
392 O31661
YKRQ protein YKRQ
393 P39764
Sporulation kinase C
KINC Phosphorylates the sporulation-regulatory protein spo0a.
Hub nodes
Important nodes for B. subtilis – 2Important nodes for B. subtilis – 2
Id- Swiss-Prot Id
Protein Name Gene Name Significance Function
121 P05652 DNA gyrase subunit B
GYRB Essential DNA gyrase negatively supercoils closed circular double-stranded DNA in an ATP-dependent manner and also catalyzes the interconversion of other topological isomers of double-stranded DNA rings, including catenanes and knotted rings.
122 Q45066 Topoisomerase IV subunit A
PARC/GRLA Essential Topoisomerase IV is essential for chromosome segregation. It has relaxation of supercoiled DNA activity. Performs the decatenation events required during the replication of a circular DNA molecule
123 P05653 DNA gyrase subunit A
GYRA Essential DNA gyrase negatively supercoils closed circular double-stranded DNA in an ATP-dependent manner and also catalyzes the interconversion of other topological isomers of double-stranded DNA rings, including catenanes and knotted rings.
124 Q59192 Topoisomerase IV subunit B
PARE Essential Topoisomerase IV is essential for chromosome segregation. It has relaxation of supercoiled DNA activity. Performs the decatenation events required during the replication of a circular DNA molecule
453 O07622 Hypothetical protein yhw
YHFW
Bottleneck nodes
Important nodes for B. subtilis – 3Important nodes for B. subtilis – 3
Id Swiss-Prot Id
Protein Name Gene Name
Significance Function
52 P16336 Preprotein translocase secY subunit
SECY Essential Involved in protein export. Interacts with secA and secE to allow the translocation of proteins across the plasma membrane, by forming part of a channel.
34 P42920 50S ribosomal protein L3 RPLC Essential This protein binds directly to 23S ribosomal RNA and may participate in the formation of the peptidyltransferase center of the ribosome
35 P42921 50S ribosomal protein L4 RPLD Essential This protein binds directly and specifically to 23S rRN
36 P42924 50S ribosomal protein L23 RPLW Essential Binds to a specific region on the 23S rRNA
37 P42919 50S ribosomal protein L3 RPLC Essential This protein binds directly to 23S ribosomal RNA and may participate in the formation of the peptidyltransferase center of the ribosom
Other important nodes
Target list for B. subtilisTarget list for B. subtilis
Id Swiss-Prot Id
Protein Name Gene Name Significance
55 P05647 50S ribosomal protein L34 RPMH Essential
56 O06492 Glutamyl tRNA amidotransferase subunit C GATC Essential
374 Q45614 Sensor protein yycG YYCG Essential
410 P42924 Preprotein translocase secY subunit SECY Essential
776 P42060 50S ribosomal protein L22 RL22 Essential
Target nodes validated against human proteome
eXSys proteome analysis system – 1 eXSys proteome analysis system – 1
Components:Components:eXSys data management engineeXSys data management engineeXSys network analysis engineeXSys network analysis engineeXSys user interface and network eXSys user interface and network
visualisation toolvisualisation toolPerforms data collection, analysis of Performs data collection, analysis of
protein interaction networks, provides user protein interaction networks, provides user interface and network visualisation interface and network visualisation
eXSys proteome analysis system – 2 eXSys proteome analysis system – 2
Computational search for new Computational search for new antibiotic targetsantibiotic targets
Bacterial proteome + host proteomeBacterial proteome + host proteome
Analysis of bacterial proteome with BLAST Analysis of bacterial proteome with BLAST validation against the host proteomevalidation against the host proteome
List of potential antibiotic targets that can List of potential antibiotic targets that can cause significant damage to the bacteria cause significant damage to the bacteria while are likely to not damage the hostwhile are likely to not damage the host
New antibioticsNew antibioticsUsual antibiotics target a single protein or Usual antibiotics target a single protein or
a related class of proteins (e.g., penicillin a related class of proteins (e.g., penicillin targeting PBPs, ribosomal antibiotics targeting PBPs, ribosomal antibiotics targeting ribosomal subunits)targeting ribosomal subunits)
New antibiotics: multiple target proteins, New antibiotics: multiple target proteins, achieving effect by combined damageachieving effect by combined damage
Computational search for drug targets Computational search for drug targets for prion and genetic diseases – 1 for prion and genetic diseases – 1
Prions and mutated genes produce wrong Prions and mutated genes produce wrong protein interactions within the protein protein interactions within the protein interaction networkinteraction network
Restoring the functionality of the cells Restoring the functionality of the cells might be done by adding or changing might be done by adding or changing existing proteins such that the functional existing proteins such that the functional integrity of the protein interaction system is integrity of the protein interaction system is restoredrestored
Computational search for drug targets Computational search for drug targets for prion and genetic diseases – 2for prion and genetic diseases – 2
Analysing protein interaction systems of Analysing protein interaction systems of diseased cells can lead to the prediction of diseased cells can lead to the prediction of likely interventions that may lead to the likely interventions that may lead to the restoration of functional integrity of the restoration of functional integrity of the protein interaction systemprotein interaction system
Summary – 1 Summary – 1 Cells can be perceived as protein Cells can be perceived as protein
interaction systemsinteraction systemsProtein interaction systems can be Protein interaction systems can be
analysed as networksanalysed as networksProtein interaction networks are scale-free Protein interaction networks are scale-free
networks, which are resistant to random networks, which are resistant to random damage but highly sensitive to targeted damage but highly sensitive to targeted damagedamage
Summary – 2 Summary – 2 The eXSys protein interaction network The eXSys protein interaction network
analysis system can collect data about analysis system can collect data about proteomes and analyse them to detect proteomes and analyse them to detect potential new drug target proteinspotential new drug target proteins
Computational drug target discovery may Computational drug target discovery may lead to new antibiotics and new drugs to lead to new antibiotics and new drugs to restore the functionality of diseased cellsrestore the functionality of diseased cells
eXSys project teameXSys project teamProject leaders: Project leaders:
Peter Andras Peter Andras Malcolm P YoungMalcolm P Young
Project members:Project members:Olusola IdowuOlusola IdowuSteven LyndenSteven LyndenPanos PeriorellisPanos Periorellis
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