1. Protein-protein interactions Lecture series in systems biology Department of Bioinfomatics Shanghai Jiao Tong University Woo Mao-Ying ricket@sjtu.edu.cn http://202.120.45.17/course/intro/ppi.htm

2. Outline Why protein-protein interactions?. Experimental methods for discovering PPIs: Yeast-two-hybrid （酵母双杂交） AP-MS （亲和纯化 - 质谱串联） PPIs databases: DIP MIPs Computational prediction of PPIs Phylogenetic based method （基于进化的手段） Expression correlation based method （基于表达相关性） STRING (EMBL)

3. Why protein-protein interactions (PPI)? Gene is the basic unit of heredity. Genomes are availabe. genome Proteome （蛋白质组） interactome Proteins, the working molecules of a cell, carry out many biological activities Proteins function by interacting with other proteins.

4. Why protein-protein interactions (PPI)? PPIs are involved in many biological processes: Signal transduction ( 信号传递 ) Protein complexes or molecular machinery （蛋白复合物或分子体系） Protein carrier （蛋白的运输） Protein modifications (phosphorylation) （蛋白质的修饰） … PPIs help to decipher the molecular mechanisms underlying the biological functions, and enhance the approaches for drug discovery

5. High throughput experimental methods for discovering PPIs Yeast-two-hybrid (Y2H ，酵母双杂交）  Ito T. et al., 2001  Uetz P. et al., 2000 Affinity purification followed by mass spectrometry (AP-MS ，亲和纯化 - 质谱串联）  Gavin AC et al., 2002, 2006  Ho Y. et al., 2002  Krogan NJ et al., 2006

6. Y2H experiments Idea:  Bait 诱饵蛋白 (prey 捕获蛋白 ) protein is fused to the binding domain (activation domain).  If bait and prey proteins interact, the transcription of the reporter gene is initiated.  High throughput screening the interactions between the bait and the prey library.  In yeast nucleus

7. AP-MS experiments Fuse [a TAP tag consisting of protA (IgG binding peptides) and calmodulin binding peptide (CBP) separated by TEV protease cleavage site] to the target protein After the first AP step （亲和纯化第一步） using an IgG ( 免疫球蛋白 ) matrix, many contaminants are eliminated. In the second AP step （亲和纯化第二步）, CBP binds tightly to calmodulin coated beads. After washing which removes remained contaminants and the TEV protease, the bound meterial is released under mild condition with EGTA ( 乙二醇二乙醚二胺 四乙酸 ). Proteins are identified by mass spectrometry

8. PPIs Databases. DIP- Database of Interacting Protein. (http://dip.doe-mbi.ucla.edu/ )http://dip.doe-mbi.ucla.edu/ MIPS-Munich Information center for Protein Sequences. (http://mips.gsf.de/ )http://mips.gsf.de/

9. DIP Protein function Protein-protein relationship Evolution of protein-protein interaction The network of interacting proteins Unknown protein-protein interaction The best interaction conditions

10. DIP-Statistics Number of proteins:20731 Number of organisms:274 Number of interactions:57687 Number of distinct experiments describing an interaction: 65735 Number of data sources (articles):3915

11. DIP-Searching information

12. Find information about your protein

13. DIP Node (DIP:1143N)

14. Graph of PPIs around DIP:1143N Nodes are proteins Edges are PPIs The center node is DIP:1143N Edge width encodes the number of independent experiments identyfying the interaction. Green (red) is used to draw core (unverified) interactions. Click on each node (edge) to know more about the protein (interaction).

15. List of interacting partners of DIP:1143N

16. MIPS Services:  Genomes  Databanks retrieval systems  Analysis tools  Expression analysis  Protein protein interactions MPact: the MIPS protein interaction resource on yeast. MPPI: the MIPS Mammalian Protein-Protein Interaction Database.  Protein complexes Mammalian protein complexes at MIPS

17. MPact: the MIPS protein interaction resource on yeast Query all PPIs of a yeast protein

18. MPact: the MIPS protein interaction resource on yeast

19. MPact: Interaction Visualization

20. MPPI: the MIPS Mammalian Protein-Protein Interaction Database Query PPIs of a mamalian protein. You can use x-ref, for example Uniprot accession number.

21. Results for PPI search In short format

22. Results for PPI search In full format

23. Mammalian protein complexes at MIPS

25. Search information of complexes

26. Assessment of large–scale data sets of PPIs The overlap between the individual methods is surprisingly small The methods may not have reached saturation. Many of the methods may produce a significant fraction of false positives. Some methods may have difficulties for certain types of interactions Von Mering C, et al. Nature, (2002) 417 : 399–403

27. Functional biases AP-MS discovers few PPIs involved in transport and sensing Y2H detects few PPIs involved in translation. Different methods complement each other Von Mering C, et al. Nature, (2002) 417 : 399–403

28. Coverage and Accuracy Von Mering C, et al. Nature, (2002) 417 : 399–403 Limited and biased coverage (False Negatives) High error rate (False Positives) Expensive, time-consuming and labor-intensive

29. Computational methods of prediction Current approaches:  Genomic methods  Biological context methods  Structural based methods

30. Genomic methods Protein a and b whose genes are close in different genomes are predicted to interact. Protein a and b are predicted to interact if they combine (fuse) to form one protein in another organism. Protein a and c are predicted to interact if they have similar phylogenetic profiles.

31. Biological context methods Gene expression: Two protein whose genes exhibit very similar patterns of expression across multiple states or experiments may then be considered candidates for functional association and posibly direct physical interaction. GO annotations: two interacting proteins likely have the same GO term annotations. Machine learning techniques are adopted for PPI classification by intergrating all known information.

32. STRING: Search Tool for the Retrieval of Interacting Genes/Proteins A database of known and predicted protein interactions Direct (physical) and indirect (functional) associations The database currently covers 2,483,276 proteins from 630 organisms Derived from these sources: Supported by

33. Searching information Query infomation via protein names or protein sequences.

34. Graph of PPIs Nodes are proteins Lines with color is an evidence of interaction between two proteins. The color encodes the method used to detect the interaction. Click on each node to get the information of the corresponding protein. Click on each edge to get information of the interaction between two proteins.

35. List of predicted partners Partners with discription and confidence score. Choose different types of views to see more detail

36. Neighborhood View The red block is the queried protein and others are its neighbors in organisms. Click on the blocks to obtain the information about corresponding proteins. The close organisms show the similar protein neighborhood patterns. Help to find out the close genes/proteins in genomic region.

37. Occurence Views Represents phylogenetic profiles of proteins. Color of the boxes indicates the sequence similarity between the proteins and their homologus protein in the organisms. The size of box shows how many members in the family representing the reported sequence similarity. Click on each box to see the sequence alignment.

38. Gene Fusion View This view shows the individual gene fusion events per species Two different colored boxes next to each other indicate a fusion event. Hovering above a region in a gene gives the gene name; clicking on a gene gives more detailed information

39. References Ito T et.al: A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proc. Natl Acad. Sci. USA 2001, 98:4569-4574. Uetz P et. al: A comprehensive analysis protein-protein interactions in Saccharomyces cerevisiae. Nature 2000, 403:623-627. Gavin AC et.al: Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature 2002, 415:141-147. Gavin AC et.al: Proteome survey reveals modularity of the yeast cell machinery. Nature 2006, 440:631-636. Ho Y et.al: Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry. Nature 2002, 415:180-183. Von Mering C et.al: Comparative assessment of large-scale data sets of protein-protein interactions. Nature 2002, 417:399-403.

40. Thank you for your attention