Download
slide1 n.
Skip this Video
Loading SlideShow in 5 Seconds..
Protein-protein interactions PowerPoint Presentation
Download Presentation
Protein-protein interactions

Protein-protein interactions

122 Vues Download Presentation
Télécharger la présentation

Protein-protein interactions

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. Protein-protein interactions Chapter 12

  2. Stable complex: homodimeric citrate synthase Transient Signaling Complex Rap1A – cRaf1 Multi-domain protein Interface 4890 Å2 Interface 1310 Å2 Stable vs. transientprotein-protein interactions Transient Interaction Stable complex “Hydrophilic” interfaces Hydrophobic interfaces

  3. Using publicly available interaction data Are there know interaction partners for you pet protein? Check if: There are interactors for your protein in the literature There are databases of interactions where your protein may appear There are homologues of your protein in the protein interaction databases You can predict interactors by other means? This failing, at this point you go back to the bench…

  4. Using publicly available interaction data Are there interactors for my protein in the literature ? • Problems: • Low coverage • Does not include results from high throughput experiments • Gene names may not be consistent

  5. Using publicly available interaction data 2. Are there databases of interactions where my protein may appear? Some DBs: BIND, MINT (General) + organism specific databases (e.g. MIPS/CYGD) Caution! Check: -the experimental methods used to identify the interaction (e.g. high error rate in large scale yeast-two hybrids) -check the method used to incorporate the interaction in the database (e.g. manual curation vs. literature mining using “intelligent” algorithms)

  6. Experimental techniques Yeast two-hybrid screens MS analysis of tagged complexes Correlated mRNA expression levels

  7. Experimental techniques Yeast two-hybrid screens MS analysis of tagged complexes Correlated mRNA expression levels 90% of genes with conserved co-expression are members of stable complexes Use microarrays to identify co-expression

  8. How good is the data?(von Mering et al., Nature 417:399)

  9. How good is the data?(von Mering et al., Nature 417:399) ”We estimate that more than half of all current high-throughput interaction data are spurious”

  10. Computational prediction of protein interactions Gene fusion events Tryptophan synthetase abfusion TrpC TrpF 1PII Fused in E.coli Unfused in some other genomes (Synechocystis sp. and Thermotoga maritima.) Enright et al (1999) Nature409:86 Marcotte et al (1999) Science285: 751

  11. Computational prediction of protein interactions Phylogenetic profiles Pellegrini et al (1999) PNAS96: 4285

  12. Computational prediction of protein interactions Pre-computed predictions: where to find them?

  13. Identification of functional modules from protein interaction data Messy data Functional modules Custering Graph theory formalisms Pereiral-Leal, Enright and Ouzounis (2003) Proteins in press

  14. DIP database • Documents protein-protein interactions from experiment • Y2H, protein microarrays, TAP/MS, PDB • 55,733 interactions between 19,053 proteins from 110 organisms. 14

  15. DIP database Duan et al., Mol Cell Proteomics, 2002 • Assess quality • Via proteins: PVM, EPR • Via domains: DPV • Search by BLAST or identifiers / text • URL • Dyrk1a GI 24418935 15

  16. DIP database Duan et al., Mol Cell Proteomics, 2002 • Assess quality • Via proteins: PVM, EPR • Via domains: DPV • Search by BLAST or identifiers / text • Map expression data 16

  17. DIP/LiveDIP Duan et al., Mol Cell Proteomics, 2002 • Records biological state • Post-translational modifications • Conformational changes • Cellular location 17

  18. DIP/Prolinks database Bowers et al., Genome Biol, 2004. • Records functional association using prediction methods: • Gene neighbors • Rosetta Stone • Phylogenetic profiles • Gene clusters 18

  19. Other functional association databases • Phydbac2 (Claverie) • Predictome (DeLisi) • ArrayProspector (Bork) 19

  20. BIND database Alfarano et al., Nucleic Acids Res, 2005 • Records experimental interaction data • 83,517 protein-protein interactions • 204,468 total interactions • Includes small molecules, NAs, complexes • URL 20

  21. BIND database • Displays unique icons of functional classes 21

  22. MPact/MIPS database Guldener et al., Nucleic Acids Res, 2006 • Records yeast protein-protein interactions • Curates interactions: • 4,300 PPI • 1,500 proteins 22

  23. STRING database von Mering et al., Nucleic Acids Res., 2005 • Records experimental and predicted protein-protein interactions using methods: • Genomic context • High-throughput • Coexpression • Database/literature mining • URL 23

  24. STRING database • Graphical interface for each of the evidence types • Benchmark against Kegg pathways for rankings 24

  25. STRING database • 736,429 proteins in 179 species • Uses COGs and homology to transfer annotation 25

  26. More interaction databases • IntAct (Valencia) • Open source interaction database and analysis • 68,165 interactions from literature or user submissions • MINT (Cesareni) • 71,854 experimental interactions mined from literature by curators • Uses IntAct data model • BioGRID (Tyers) • 116,000 protein and genetic interactions 26

  27. InterDom database Ng et al., Nucleic Acids Res, 2003 • Predicts domain interactions (~30000) from PPIs • Data sources: • Domain fusions • PPI from DIP • Protein complexes • Literature • Scores interactions 27

  28. Definition of CBM • Interacting domain pair – if at least 5 residue-residue contacts between domains (contacts – distance of less than 8 Ǻ) • Structure-structure alignments between all proteins corresponding to a given pair of interacting domains • Clustering of interface similarity, those with >50% equivalently aligned positions are clustered together • Clusters with more than 2 entries define conserved binding mode. 28

  29. DIMA database Pagel et al., Bioinformatics, 2005 • Phylogenetic profiles of Pfam domain pairs • Uses structural info from iPfam • Works well for moderate information content 29

  30. So.. You know your two proteins interact… do you want to know how? Prediction of the molecular basis of protein interactions

  31. Molecular basis of protein interaction “Tree determinant residues” Rab REP MSA Ras Rho Arf Ran x REP Prediction _ + Experimental tests Pereira-Leal and Seabra (2001) J. Mol. Biol. Pereira-Leal et al (2003) Biochem. Biophys. Res. Com.

  32. Molecular basis of protein interaction “Tree determinant residues” Continued… Sequence Space algorithm AMAS (part of a bigger package) Casari et al (1995) Nat. Struct. Biol 2(2)

  33. Molecular basis of protein interaction In silico docking Requires 3D structures of components Conformational changes cannot be considered (rigid body)