Protein interactions

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  • 1. Protein interactions Lars Juhl Jensen
  • 2. what is an interaction?
  • 3. physical interaction
  • 4. functional association
  • 5. fuzzy definitions
  • 6. physical interactions
  • 7. stable interactions
  • 8. transient interactions
  • 9. binary interactions
  • 10. multimeric complexes
  • 11. Jensen et al., Drug Discovery Today: TARGETS, 2004
  • 12. spoke representation
  • 13. Jensen et al., Drug Discovery Today: TARGETS, 2004
  • 14. matrix representation
  • 15. Jensen et al., Drug Discovery Today: TARGETS, 2004
  • 16. interaction assays
  • 17. yeast two-hybrid
  • 18. fragment complementation
  • 19. affinity purification
  • 20. Jensen & Bork, Science, 2008
  • 21. interaction databases
  • 22. BioGRID General Repository for Interaction Datasets
  • 23. DIP Database of Interacting Proteins
  • 24. IntAct
  • 25. MINT Molecular Interactions Database
  • 26. Exercise 1 Go to http://thebiogrid.org Query for human TYMS Find the interaction partners Check their sources Think of possible problems
  • 27. possibly many errors
  • 28. only high-throughput
  • 29. one assay
  • 30. one study
  • 31. functional associations
  • 32. guilt by association
  • 33. STRING
  • 34. Franceschini et al., Nucleic Acids Research, 2013
  • 35. Exercise 2 Go to http://string-db.org Query for human TYMS Show only highest confidence Show network in confidence view Show network in evidence view
  • 36. genomic context
  • 37. operons
  • 38. Korbel et al., Nature Biotechnology, 2004
  • 39. bidirectional promoters
  • 40. Korbel et al., Nature Biotechnology, 2004
  • 41. gene fusion
  • 42. Korbel et al., Nature Biotechnology, 2004
  • 43. phylogenetic profiles
  • 44. Korbel et al., Nature Biotechnology, 2004
  • 45. a real example
  • 46. Cell Cellulosomes Cellulose
  • 47. experimental data
  • 48. physical interactions
  • 49. Jensen & Bork, Science, 2008
  • 50. genetic interactions
  • 51. Beyer et al., Nature Reviews Genetics, 2007
  • 52. gene coexpression
  • 53. text mining
  • 54. co-mentioning
  • 55. curated knowledge
  • 56. complexes
  • 57. pathways
  • 58. Letunic & Bork, Trends in Biochemical Sciences, 2008
  • 59. many databases
  • 60. different formats
  • 61. different identifiers
  • 62. variable quality
  • 63. not comparable
  • 64. not same species
  • 65. hard work
  • 66. (graduate students)
  • 67. quality scores
  • 68. von Mering et al., Nucleic Acids Research, 2005
  • 69. calibrate vs. gold standard
  • 70. von Mering et al., Nucleic Acids Research, 2005
  • 71. homology-based transfer
  • 72. orthologs vs. paralogs
  • 73. Franceschini et al., Nucleic Acids Research, 2013
  • 74. Exercise 3 Query STRING for human TYMS Show only experimental evidence Show up to 50 interaction partners Show also low-confidence links Redo exercise for mouse TYMS
  • 75. related web resources
  • 76. STITCH
  • 77. STRING + 300k chemicals
  • 78. drugs
  • 79. metabolites
  • 80. known drug targets
  • 81. high-throughput screens
  • 82. metabolic pathways
  • 83. Exercise 4 Go to http://stitch-db.org Query for human TYMS What is the role of thymidylate? What is the role of dUMP? What is the role of Permetrexed?
  • 84. general approach
  • 85. suite of new resources
  • 86. COMPARTMENTS
  • 87. TISSUES
  • 88. DISEASES
  • 89. curated knowledge
  • 90. experimental data
  • 91. text mining
  • 92. computational predictions
  • 93. common identifiers
  • 94. quality scores
  • 95. visualization
  • 96. compartments.jensenlab.org
  • 97. tissues.jensenlab.org
  • 98. thank you!