Considering protein interaction sites in coexpression networks and a tool called intersite

1
Considering protein interaction sites in
co-expression networks and a tool called intersite

• In order to analyze a co-expression network of
  Affy probes, putative protein product structure
  was considered via number of interaction sites.
  A web based tool called Intersite was developed
  as a Group Decision Support System for annotating
  the interaction sites on proteins.

2
Background

• Understanding Protein Function on a Genome scale
  using networks
• First Annual Midwest Computational Biology and
  Bioinformatics Symposium at Northwestern
  University, 9/2007
• Talk by Dr. Mark Gerstein Yale University
• Problems with using pathway node degree
  (hub-ness) as an indicator for essentiality
• Need to consider interact-ability
• via number of interaction sites on a protein
  product
• Showed more correlation between essentiality
  (slower evolution rate) and network between-ness
  than between essentiality and node degree

3
Background

• Yeates, Todd O and Beeby, Morgan.
• Proteins in a Small World.
• Science 22 Dec 2006 Vol. 314. no. 5807, pp. 1882
  1883

4
Background

• Kim PM, Lu LJ, Xia Y, Gerstein MB.
• Relating three-dimensional structures to protein
  networks provides evolutionary insights.
• Science. 2006 Dec 22 314(5807)1938-41.

Fig. 1. The creation of the structural
interaction network (SIN) data set. All
interactions from the filtered protein
interaction data set are mapped to Pfam domains
(30). The Pfam domains are mapped to known
structures of protein interactions by means of
iPfam (31). Only those interactions in which both
interaction partners (or a homologous domain of
either) can be found in a 3D structure of a
protein complex are kept. All interactions are
then classified into mutually exclusive and
simultaneously possible by 3D structural
exclusion. When a protein has more than one
simultaneously possible interaction, the number
of interaction interfaces is counted.
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The Idea

• Facilitate the same analysis for other networks.
• ie, coexpression networks
• Incorporate human decision making
• Incorporate genomic/primary sequence data

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A co-expression network

• Cramer GR, Ergül A, Grimplet J, Tillett RL,
  Tattersall EA, Bohlman MC, Vincent D, Sonderegger
  J, Evans J, Osborne C, Quilici D, Schlauch KA,
  Schooley DA, Cushman JC.
• "Water and salinity stress in grapevines early
  and late changes in transcript and metabolite
  profiles.
• Funct Integr Genomics. 2007 Apr7(2)111-34. Epub
  2006 Nov 29.
• Data available as experiment VV2 on plexdb.org
• 4 timepoints
• X 3 treatments
• X 3 replicates
• 3 controls at time 0
• 39 Affy hybridizations with RMA normalization
• X 16,602 Affy grape probes

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A co-expression network

• A program was written that, among other things
• Built a correlation network based on an
  arbitrarily set cutoff value for edge assignment
• Thinned the network by dropping those edges
  associated with first and second order partial
  correlations not significantly different from
  zero
• according to de la Fuente, et al.
  Bioinformatics. Vol. 20, No. 18. Pp. 3565-3574,
  2004.

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A co-expression network
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A co-expression network

• Zero-order Pearson correlation networks were
  constructed with the following characteristics

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A co-expression network

• Related networks were created, with edges removed
  which are associated with a first-order partial
  correlation not significantly different from
  zero.

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Probe ID -gt a protein product

• Map file from Wengang Zhou
• Difficult problem!

OneMany
ManyMany
Grape Probe ID
AT Gene Name
UniProt AC
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Interactions?

• Kim el al. used
• Pfam
• Protein information based on a given network
• Finn, et al. Pfam clans, web tools and
  services Bioinformatics. 35D 2005.
• iPfam
• A database within a database containing
  pairwise interaction information between proteins
  and even their respective residues.
• Finn, Marhsall, Bateman. iPfam visualization
  of protein-protein interactions in PDB at domain
  and amino acid resolutions. Bioinformatics. 21
  3 2005.
• But

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Im on my own
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Incorporate human decision making

• Group Decision Support Systems
• Electronically integrated decision help conducted
  by and for many people at once.
• InterSite
• a Group Decision Support System for the
  annotation and classification of proteins based
  on their number and types of interaction sites

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Intersite Database Schema
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Intersite Data Flow Diagram
Login
Enter UniProt ACs
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Fetch and store GenBank data
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Incorporate human decision making
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Logged in
20
View Proteins
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Map External IDs
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Application to smallest VV2 network
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Incorporate genomic data Site Similarity Network
Site similarity is also used to assist decision
making
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Annotate/Classify
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GenBank File doesnt know it all
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User-defined sites
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Try it

• Goto http//lab.bcb.iastate.edu/sandbox/jlv/inters
  ite/
• Log in
• Use the file linked with VV2 UniProt ACs
• Paste in the top 20 Acs
• Put on your Biochemistry hat and vote!
• Use the tools to help make a decision
• EBI fetch
• PIRSF scan
• UniProt record
• GenBank file

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Results Number of Interactions
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Results Number of Interactions
30
Result Site similarity network
31
Results Site similarity network
32
Results Site similarity network
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Results Site similarity network
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Results Site similarity network
35
Results Site similarity network
36
Results Site similarity network
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Discussion

• This project was an interesting exercise in
  utilizing multiple Bioinformatics tools (and
  creating some new ones) in order to ask and
  answer questions relating sequence and structure.
  Future work may include separate analysis of the
  groups of VV probes separated by their associated
  proteins numbers of interaction sites. Also,
  like in 1, between-ness, closeness, hub-ness,
  and hierarchy level of the proteins in the
  pathways can also be calculated.
• A useful outcome from the project is the ability
  to build protein networks based on interaction
  site similarity and visualize such clusters. For
  the data used here, nucleus, membrane, and
  secreted proteins share unique interaction site
  sequences. This is probably due to the fact that
  nucleus proteins must be delivered to the nucleus
  using signal sequences and special chaperone
  interaction sites. The same is true for secreted
  proteins and membrane proteins. Further analysis
  could consider the rest of the locations
  specified for proteins with multiple subcellular
  location values.
• Availability
• Intersite is available online at
  http//lab.bcb.iastate.edu/sandbox/jlv/intersite
  . More details on this project and all the
  scripts used can be found at http//www.public.ias
  tate.edu/jlv/intersite.shtml

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References

• 1 Gerstein, Mark. Presentation.
  Understanding Protein Function on a Genome scale
  using networks. First Annual Midwest
  Computational Biology and Bioinformatics
  Symposium, Northwestern University.
• 2 Kim PM, Lu LJ, Xia Y, Gerstein MB. Relating
  three-dimensional structures to protein networks
  provides evolutionary insights. Science. 2006
  Dec 22 314(5807)1938-41.
• 4 Finn, et al. Pfam clans, web tools and
  services Bioinformatics. 35D 2005.
• 3 Finn, Marhsall, Bateman. iPfam
  visualization of protein-protein interactions in
  PDB at domain and amino acid resolutions.
  Bioinformatics. 21 3 2005.
• 5 Cramer GR, Ergül A, Grimplet J, Tillett RL,
  Tattersall EA, Bohlman MC, Vincent D, Sonderegger
  J, Evans J, Osborne C, Quilici D, Schlauch KA,
  Schooley DA, Cushman JC. "Water and salinity
  stress in grapevines early and late changes in
  transcript and metabolite profiles. Funct
  Integr Genomics. 2007 Apr7(2)111-34. Epub 2006
  Nov 29.
• 6de la Fuente, et al. Bioinformatics. Vol. 20,
  No. 18. Pp. 3565-3574, 2004.
• 8 Wu, Cathy H, et al. The iProClass
  integerated database for protein functional
  analysis. Computational Biology and Chemistry.
  28 (2004) 87-96.
• 9 Liu, Hongfang, et al. BioThesaurus a
  web-based thesaurus of protein and gene names.
  Bioinformatics. 22 1 2006. pp103-105.