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Social behavior of proteins?

Social behavior of proteins?. Rui Alves. Organization of the talk. Social behavior of the protein?!?!?!? Using meta text analysis Using phylogenetic profiling Using pathway homology Using protein docking Using microarray data Using protein interaction data. Proteins do not work alone!.

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Social behavior of proteins?

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  1. Social behavior of proteins? Rui Alves

  2. Organization of the talk • Social behavior of the protein?!?!?!? • Using meta text analysis • Using phylogenetic profiling • Using pathway homology • Using protein docking • Using microarray data • Using protein interaction data

  3. Proteins do not work alone!

  4. Networks of “interactions” predict global function • Having the network of proteins/genes in which your protein/gene is inserted provides predictive information: • Which cellular pathways or processes is your protein/gene likely to be involved in

  5. Organization of the talk • Social behavior of the protein?!?!?!? • Using meta text analysis • Using phylogenetic profiling • Using pathway homology • Using protein docking • Using microarray data • Using protein interaction data

  6. Publication databases are source of information

  7. Meta text databases create social models from publication analysis

  8. iHOP is a sofisticated context analysis motor

  9. Server/ Program Literature database Gene names database Language rules database Gene list Rule list How does meta-text analysis create networks? Your genes scripts Entry List of entries mentioning your gene e.g activate, inhibit rescue e.g Ste20

  10. Organization of the talk • Social behavior of the protein?!?!?!? • Meta text analysis • Evolutionary based protein interaction prediction • Using pathway homology • Using protein docking • Using microarray data • Using protein interaction data

  11. Proteins that have coevolved share a function • If protein A has co-evolved with protein B, they are likely to be involved in the same process • Looking for proteins that coevolved will help prediction social networks of proteins • There are many methods to look for co-evolution of proteins • Phylogenetic profiling, gene neighbourhoods, gene fusion events, phylogenetic trees…

  12. Database of proteins in fully sequenced genomes Database of proteins in one genome Database of profiles for each protein in each organism Creating phylogenetic profiles Sequence of each protein Homology search against each genome

  13. Database of profiles for each protein in each organism Database of proteins in fully sequenced genomes Server/ Program Using phylogenetic profiles to predict protein interactions A 1 C 0.9 … … B 0.11 … … Your Sequence (A) Proteins (A and C) that are present and absent in the same set of genomes are likely to be involved in the same process and therefore interact Calculate coincidence index Protein id A A B C Similarly, if protein A is absent in all genomes in which protein B is present there is a likelihood that they perform the same function! i/number of genomes<1 j/number of genomes 0 0 2 1

  14. How to do it? • Download genomes • Use blast for homology • Use perl for homology processing and coincidence index calculations

  15. Protein A Protein B Protein C Protein D Protein D Protein C Protein A Protein B Protein B Protein C Protein D Protein A Syntheny/Conservation of gene neighborhoods Genome 1 Genome 2 Protein A Protein B Protein C Protein D Proteins A and B are in a conserved relative position in most genomes which is an indication that they are likely to interact Genome 3 Which of these proteins “interact”? … Genome …

  16. How to do it? • Download genomes • Use perl for analysis

  17. Protein A Protein B Protein C Protein D Protein D Protein C Protein A Protein B Protein B Protein C Protein D Protein A Gene fusion events Genome 1 Protein A Protein B Protein C Protein D Genome 2 Which of these proteins interact? Proteins A and B have suffered gene fusion events in at least some genomes, which is an indication that they are likely to interact Genome 3 … Genome …

  18. How to do it? • Download genomes • Use perl for analysis

  19. Protein A Protein B Protein C Protein D Protein D Protein C Protein A Protein B Protein B Protein C Protein D Protein A Building phylogenetic trees of proteins Genome 1 Phylogenetic trees represent the evolutionary history of homologue genes/proteins based on their sequence Genome 2 Genome 3 … Genome … Get sequence of all homogues, align and build a phylogenetic tree

  20. Distance based phylogenetic trees A1 A2 A3 … ACTDEEGGGGSRGHI… A-TEEDGGAASRGHI… ACFDDEGGGGSRGHL… … A1 A3 A2 A3 A2 A1 5 substitutions 3 substitutions 8 substitutions 5 A1 A3 3 A2

  21. Maximum likelihood phylogenetic trees Probability of aa substitution Alignment ACTDEEGGGGSRGHI… A-TEEDGGAASRGHI… ACFDDEGGGGSRGHL… … A - E D … A 1 0.01 0.2 0.09 … - 0.01 1 0.0001 0.0001 … E 0.2 0.0001 1 0.5 D 0.09 0.0001 0.5 1 …

  22. Maximum likelihood phylogenetic trees A2 Alignment p(1,2) ACTDEEGGGGSRGHI… A-TEEDGGAASRGHI… ACFDDEGGGGSRGHL… … A1 5 substitutions A1 p(1,3) A3 3 substitutions p(2,3)<p(1,2)<p(1,3) A3 A2 A1 A2 p(2,3) 8 substitutions A3 A3 A1 A2

  23. … … Similarity of phylogenetic trees indicates “interaction” between proteins A1 B1 B2 A2 B3 A3 … C3 Proteins A and B have similar evolutionary trees and thus are likely to “interact” D2 … C2 D1 C1 D3

  24. How to do it? • Download genomes • Use blast,… for analysis • Use Clustal, Phylip, PAUP, … for tree building

  25. Organization of the talk • Social behavior of the protein?!?!?!? • Using meta text analysis • Using phylogenetic profiling • Using pathway homology • Using protein docking • Using microarray data • Using protein interaction data

  26. Pathway homology Server/ Program Database of protein sequences in genomes Your Sequence Database of pathways in genomes Homologue(s) Output Database of interactions in genomes

  27. Pathway homology complements protein homology

  28. Organization of the talk • Social behavior of the protein?!?!?!? • Using meta text analysis • Using phylogenetic profiling • Using pathway homology • Using protein docking • Using microarray data • Using protein interaction data

  29. Protein A Protein B What is protein docking? Protein B Protein A Protein A Protein B Protein A Best Docking Protein B Protein A Protein B Protein A Protein B Same area of interaction Positive Negative Negative

  30. Protein C Caveats of using protein docking to predict interaction Protein B Protein A Glycolisys DNA synthesis Proteins may not come into contact in the cell although if they did they could interact Very heavy computationaly

  31. When shoudl we use protein docking to predict network structure? When we have a group of proteins that are known to be involved in the same function and we want to predict how the different proteins interact with each other

  32. How to do it? • Download structures or create structure predictions • Use GRAMM, HEX, …

  33. Organization of the talk • Social behavior of the protein?!?!?!? • Using meta text analysis • Using phylogenetic profiling • Using pathway homology • Using protein docking • Using microarray data • Using protein interaction data

  34. Predicting protein interactions using micro array data Genes overexpressed as a result of stimulus Group of proteins involved in response to the stimulus cells Purify cDNA Compare cDNA levels of corresponding genes in the different populations Genes underexpressed as a result of stimulus Stimulum Purify cDNA cells Genes with expression independent of stimulus

  35. Organization of the talk • Social behavior of the protein?!?!?!? • Using meta text analysis • Using phylogenetic profiling • Using pathway homology • Using protein docking • Using microarray data • Using protein interaction data

  36. E D A C B F Predicting protein networks using protein interaction data Database of protein interactions Your Sequence (A) Server/ Program Continue until you are satisfied or completed the network

  37. Summary • Social behavior of the protein?!?!?!? • Using meta text analysis • Using phylogenetic profiling • Using pathway homology • Using protein docking • Using microarray data • Using protein interaction data

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