1. Protein-protein interactions Chapter 12

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

3. Using publicly available interaction data 1.There are interactors for your protein in the literature 2.There are databases of interactions where your protein may appear 3.There are homologues of your protein in the protein interaction databases 4.You can predict interactors by other means? 5.This failing, at this point you go back to the bench… Are there know interaction partners for you pet protein? Check if:

4. Using publicly available interaction data Problems: Low coverage Does not include results from high throughput experiments Gene names may not be consistent 1.Are there interactors for my protein in the literature ?

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. ”We estimate that more than half of all current high-throughput interaction data are spurious”

10. Computational prediction of protein interactions Tryptophan synthetase   fusion 1PII TrpCTrpF Fused in E.coli Unfused in some other genomes (Synechocystis sp. and Thermotoga maritima.) Enright et al (1999) Nature 409:86 Marcotte et al (1999) Science 285: 751 Gene fusion events

11. Pellegrini et al (1999) PNAS 96: 4285 Computational prediction of protein interactions Phylogenetic profiles

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

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

14. 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. Organisms# proteins# interactions Fruit fly705220,988 H. pylori7101425 Human9161407 E. coli18317408 C. elegans26384030 Yeast492118,225 Others985401

15. 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

16. 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

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

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

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

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

21. 21 BIND database Displays unique icons of functional classes

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

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

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

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

26. 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

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

28. 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.

29. 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

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

31. Molecular basis of protein interaction “Tree determinant residues” Rab Ras Rho Arf Ran x REP + _ MSA 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 Casari et al (1995) Nat. Struct. Biol 2(2) AMAS (part of a bigger package)

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