Molecular interactions

1. Molecular interactions Based on Chapter 4 of Post-genome Bioinformatics by Minoru Kanehisa, Oxford University Press, 2000

2. Central dogma: DNA -> RNA -> Protein Sequence Structure Function Interaction Network Function Genome Transcriptome Proteome

3. Network representation. A network (graph) consists of a set of elements (vertices) and a set of binary relations (edges). Biological knowledge and computational results are represented by different types of network data. 2) Binary Relation 1) Element Molecular interaction Genetic interaction Other types of relations Molecule Gene 3) Network Assembly Neighbour Cluster Hierarchical Tree Pathway Genome

4. Representation of the same graph by: (a) a drawing of nodes and edges, (b) a linked list, and (c) an adjacency matrix. (a) (b) A B B A C D C B E D B E E C D F F E A B C D (c) A B C D E F A B 1 C 0 1 D 0 1 0 E 0 0 1 1 F 0 0 0 0 1 E F

5. Biological examples of network comparisons. Pathway vs. Pathway Pathway vs. Genome Genome vs. Genome Cluster vs. Pathway

6. Pathway alignment is a problem of graph isomorphism: (a) a maximum common induced subgraph and (b) a maximum clique. Pathway 1 Pathway 2 (a) A a B b c d E C B-a B-b C-d D-f A D A (b) (A, a) (A, b) (A, c) (A, d) (A, e) (A, f) (B, a) (B, b) (B, c) (B, d) (B, e) (B, f) (C, a) (C, b) (C, c) (C, d) (C, e) (C, f) (D, a) (D, b) (D, c) (D, d) (D, e) (D, f) (E, a) (E, b) (E, c) (E, d) (E, e) (E, f)

7. a a A b b B C c c D d d g G g E e e k k K i I i h H h f F f J j j A B C D G E K I H F J A heuristic algorithm for biological graph comparison. It searches for clusters of correspondences, as shown in (a), which is similar in spirit to sequence alignment, shown in (b). Graph 1 Correspondences Graph 2 (a) A - a B - b C - c D - d . . . . . . Clustering algorithm (b) A-B-C-D-E-F-G-H-I-J-K : : : A-c-b-d-e-f-h-g-j-k-i

8. Examples of binary relations

9. O O O An example of computing possible reaction paths from pyruvate (C00022) to L-alanine (C00041) given a set of substrate-product binary relations, or a given list of enzymes. EC number CH3 O 1.4.1.1 OH H3C C00041 NH2 OH C00022 2.6.1.21 5.1.1.1 CH3 4.1.1.12 OH 4.1.1.3 C00133 NH2 O O OH OH OH 1.4.3.16 O O NH2 O HO C00049 C00036

10. Query relaxation. Nodes E and E’ are considered to be equivalent according to the grouping G.

11. Network data representation in KEGG

12. Genome-pathway comparison, which reveals the correlation of physical coupling of genes in the genome - operon structure (a) and functional coupling (b) of gene products in the pathway (a) E. coli genome hisL hisG hisD hisC hisB hisH hisA hisF hisI yefM yzzB

13. (b) Metabolic pathway HISTIDINE METABOLISM Pentose phosphate cycle 5P-D-1-ribulosyl- formimine 3.5.1.- Phosphoribulosyl- Formimino-AICAR-P 2.6.1.- Imidazole- acetole P Phosphoribosyl-AMP L-Hisyidinal 3.6.1.31 3.5.4.19 5.3.1.16 2.4.2.- 4.2.1.19 2.6.1.9 3.1.3.15 2.4.2.17 PRPP Phosphoriboxyl-ATP Phosphoribosyl- Formimino-AICAR-P Imidazole- Glicerol-3P L-Histidinol-P 5P Ribosyl-5-amino 4- Imidazole carboxamide (AICAR) 1.1.1.23 1-Methyl- L-histidine L-Hisyidinal 3.4.13.5 Aneserine 6.3.2.11 2.1.1.- Purine metabolism 2.1.1.22 Carnosine 6.3.2.11 1.1.1.23 3.4.13.3 6.1.1 3.4.13.20 N-Formyl-L- aspartate Imidazolone acetate Imidazole- 4-acetate Imidazole acetaldehyde Histamine Hercyn 4.1.1.22 3.5.3.5 3.5.2.- 1.14135 1.2.1.3 1.4.3.6 4.1.1.28 L-Histidine

14. Hierarchy-pathway comparison, which reveals the correlation of evolutionary coupling of genes (similar sequences or similar folds due to gene duplications) and functional coupling of gene products in the pathway. SCOP hierarchical tree 1. All alpha 2. All beta 3. Alpha and beta (a/b) 3.1 beta/alpha (TIM)-barrel 3.2 Cellulases . . . . . . . 3.74 Thiolase 3.75 Cytidine deaminase 4. Alpha and beta (a+b) 5. Multi-domain (alpha and beta) 6. Membrane and cell surface pro 7. Small proteins 8. Peptides 9. Designed proteins 10. Non-protein ……..NE, TYROSINE AND TRYPTOPHAN BIOSYNTHESIS Tyrosine metabolism Alkaloid biosynthesis I Tyr-tRNA 6.1.1.1 Tyrosine 2.6.1.1 2.6.1.5 1.4.3.2 1.3.1.43 2.6.1.9 2.6.1.57 4-Hydroxy- phenylpyruvate 1.14.16.1 4.2.1.51 2.6.1.57 2.6.1.1 2.6.1.5 Pretyrosine 4.2.1.91 2.6.1.9 2.6.1.57 Phenylpyruvate 1.4.1.20 2.6.1.1 4.2.1.51 Prephenate 6.1.1.20 Indole RNA 2.6.1.5 2.6.1.9 2.6.1.57 4.2.1.91 Phenylalanine 4.2.1.20 1.4.3.2 5.4.99.5 4.2.1.20 2.5.1.19 4.6.1.4 4.1.3.27 2.4.2.18 5.3.1.24 4.2.1.20 4.1.1.48 3-deoxy- D-arabino- heptonate L-Tryptophan Anthranilate N-(5-Phospho- b-v-ribosyl)- anthranilate 1-(2- Carboxy- Phenylamino)- 1-deoxy-D-ribulose 5-phosphate (3-Indolyl)- Glycerol phosphate Chorismate 2.7.1.71 Shikimate Histidine 4.6.1.3 1.1.1.25 1.1.9925 4.1.3.- 3-Dehydro- quinate 4-Aminobenzoate Tryptophan metabolism 4.2.1.10 Ubiquinone biosynthesis 4.2.1.10 4.2.1.11 3-Dehydro- shikimate Protocatechuate 1.1.1.24 1.1.9925 Folate biosynthesis Quniate

15. Grand challenge problems

16. Glycolysis, the TCA cycle , and the pentose phosphate pathway, viewed as a network of chemical compounds. Each circle is a chemical compound with the number of carbons shown inside. NADPH D-Glucono-1,5- Lactone-6P D-Glucose-6P 6-Phospho- D-gluconate D-Glucose 6 6 6 6 D-Xylulose-5P CO2 NADPH D-Fructose-6P 6 5 5 D-Ribulose-5P 4 D-Fructose-1,6P2 6 5 D-Ribose-5P 7 Citrate cycle (TCA cycle) Pentose Phosphate pathway D-Sedoheptulose-7P Glycerone-P 3 3 Glyceraldehyde-3P NADH NADH Funarate (S )-Malate Glycerae-1,3P2 3 Oxaloacetate 4 4 4 ATP FADH2 Glycerate-3P 3 Citrate 6 Glycerate-2P 3 Succinate 4 CoA 21 CoA GTP 21 Isocitrate 6 CoA Phophoenolpyruvate CoA 3 21 21 CO2 CO2 NADH ATP 25 12 5 5 2-Oxo- glutarate 23 10 3 Pyruvate S-Acetyl- dihydrolipoamide S-Acetyl- dihydrolipoamide Succinyl-CoA Acetyl-CoA 8 8 8 8 Dihydro- lipoamide Lipoamide Dihydro- lipoamide Lipoamide NADH NADH

17. Glycolysis viewed as a network of enzymes (gene products). Each box is an enzyme with its EC number inside. D-Glucose (extracellular) 2.7.1.69 Pentose Phosphate cycle D-Glucose-6P 2.7.1.2 D-Glucose 5.3.1.9 D-Fructose-6P 3.1.3.11 2.7.1.11 D-Fructose-1,6P2 4.1.2.13 5.3.1.1 Glyceraldehyde-3P Glycerone-P 1.2.1.12 Gycerate-1, 3P2 2.7.2.3 Glycerate-3P 5.4.2.1 Glycerate-2P 4.2.1.11 Citrate cycle (TCA cycle) Phosphoenolpyruvate Acetyl-CoA 2.7.1.40 1.2.1.51 Pyruvate 2.3.1.12 1.2.4.1 6-S-Acetyl-dihydrolipoamide 1.8.1.4 Dihydrolipoamide Lipoamide

18. A generalized concept of protein-protein interactions. Direct protein-protein interaction Protein 1 Protein 2 Binding, modification, Cleavage, etc. Indirect protein-protein interaction Protein 1 Protein 2 Enzymic reaction Protein 1 Protein 2 Gene expression Gene (Molecular template)

19. Reference knowledge (e.g. KEGG) Predicted network by orthologue identification Predicted network by path computation A strategy for network reconstruction from genomic information. Gene catalogue in the genome Binary relations: Positional cloning Genome comparisons Gene-gene (indirect) interactions DNA chips Protein-protein (direct) interactions Protein chips Substrate-product relations Biochemical knowledge Hierarchial relations Sequence analysis

20. Genetic and chemical blueprints of life.

21. Principles of the biochemical network encoded in the genome. Hierarchy - conservation and diversification (a) Low resolution network (b) Divergent inputs Divergent outputs Conserved pathway High resolution network Duality - chemical logic and genetic logic (c) Metabolic network (d) Chemical network Enzyme network Protein-protein interaction network Gene regulatory network + =

22. Biological examples of complex systems

27. From Sequence to FunctionComparison of bioinformatics aproaches for functional prediction Era Experiments Database Computational method 1977 gene cloning sequence sequence similarity search sequencing 1995 whole genome pathway pathway reconstruction sequencing path computation pathway = wiring diagram

28. Functional Reconstruction Problem(Sequence -> organism) 1. Genome is a blueprint of life (Dolly’s cloning principle) Genome + Environment (Nucleus) 2. Network of molecular interactions in the entire cell is a blueprint of life - Genome is only a warehouse of parts (Principle of molecular interaction) Germ Cell Line

30. Pathway Assembly

31. DNA Damage

32. Suzie Grant’s Study: Aims • Examine the effects of oncostatin-M (OSM) in combination with Epidermal Growth Factor (EGF) • Delineate the signalling pathway responsible for the effects induced by OSM in breast cancer cells.

33. IL-6 Cytokine Receptor Family. LIF IL-6 CNTF OSM OSM IL-11 CT C N T F R  IL - 6 R  IL- - 1 1 R  gp130 gp130 gp130 OSMR  LIFR b

34. Physiological Functions of IL-6 family members Cytokine OSM, LIF, IL-6, IL-11 OSM OSM, LIF, IL-6, CT-1 OSM, LIF, CT-1, CNTF OSM OSM, LIF, IL-6, IL-11 OSM OSM OSM, LIF, IL-6, IL-11, CNTF, CT-1 OSM, LIF, IL-6, IL-11 OSM, LIF, IL-6, IL-11 OSM, LIF, IL-6 OSM, LIF, IL-6, IL-11, CNTF, CT-1 • Function • Proliferation/maturation of megakaryocytes • Expansion of hemopoietic progenitor cells in the AGM • Induce terminal differentiation of M1 cells • Inhibit differentiation of ES cells • Stimulate proliferation of fibroblasts • Increase expression of TIMP-1, ICAM-1 and VCAM-1 • Proliferation/differentiation of vascular endothelial cells • Elevate LDL receptors in hepatocytes • Induce synthesis of acute phase proteins in the liver • Inhibit lipoprotein lipase, resulting in fat depletion • Induce bone resorption, stimulate osteoblast activity • Induce proliferation/differentiation of T-lymphocytes • Promote survival or differentiation of neurons

35. 120 100 80 60 40 20 0 Effects of IL-6, LIF, OSM, CNTF and IL-11 on MCF-7 cell proliferation. # + * p < 0.001 # p < 0.01 + p < 0.02 # Cell No. (% Control) * n = 9 expts. 14 IL-6 LIF IL-11 OSM CNTF Control

36. Effects of OSM on breast cancer cells. • OSMRb and gp-130 are expressed in breast cancer cell lines and primary tumour samples • Inhibition of proliferation of ER + and - breast cancer cell lines • Decreased clonogenicity • Inhibition of cell cycle progression • Reduced S phase fraction • Increased G0/G1 phase fraction • Alterations in mRNA expression • Decrease ER and PRLR expression • Increased EGFR expression • Phenotypic changes consistent with differentiation-induction • Morphology • Lipid accumulation • Apoptosis

37. P P P P P P P P P P OSM Signalling OSM OSMRb or LIFRb gp130 Cell Membrane JAK1 JAK1 P P ? SOS RAS GRB2 Y Y P Y Y P P RAF SHC P STAT3 P Cytoplasm P MEK P STAT3 (ERK1/2) MAPK S Transcription Factors STAT3 Transcription Nucleus

38. Signalling by IL-6 Type Cytokines • In M1 cells, STAT3 is critical for IL-6 induced growth regulation and differentiation. • Nakajima et al., EMBO J, 15, 1996 • Growth inhibition of A375 cells by OSM/IL-6 is STAT3 dependant. • Kortylewski et al., Oncogene, 18, 1999 • In myeloma cells IL-6 up regulates mcl-1 through the JAK/STAT not ras/MAPK pathway. • Puthier et al., Eur. J. Immunol., 29, 1999 • OSM activates STAT3 and ERK 2 in GOS3 cells. Blockade of MEK 1 partially inhibits the effects of OSM on these cells. • Halfter et al., MCBRC, 1, 1999 • In adipocytes, LIF induces differentiation via the MAPK pathway. • Aubert et al., JBC, 274, 1999 • Growth of KS cells stimulated by OSM/IL-6 is mediated by ERK 1/2 and negatively regulated by p38. • Murakami-Mori et al., BBRC, 264, 1999 • OSM activates MAPK through a JAK 1 dependant pathway in HeLa cells. • Stancato et al., MCB, 17, 1997

39. EGF family of growth factors and receptors • Epidermal growth factor (EGF) is a polypeptide growth factor • Mitogenic for mammary epithelium and breast cancer cells • Overcomes effects of several breast inhibitors such as tamoxifen and dexamethasone • Binds the EGFR/ErbB-1, a receptor with intrinsic tyrosine kinase activity • Signalling via an EGFR homodimer or EGFR heterodimer with ErbB-2,-3 or -4 • Heterodimer of EGFR and ErbB-2 preferred

40. EGF family of receptors • EGFR/ErbB-1 • Overexpressed in about 30% of breast tumours • Expression correlates inversely with ER • Predicts aggressive disease/poor prognosis • ErbB-2 (HER2/neu) • Overexpressed in many types of cancer • Correlates with aggressive disease and shorter disease free survival in breast cancer patients • Most oncogenic of all ErbB family members • Orphan receptor • ErbB-3 • Contains a non-functional kinase • No correlation b/w expression in tumours and prognosis • ErbB-4 • Few clinical studies

41. EGF signalling EGFR, ErbB-2, 3 or 4 EGF EGFR PI3K PLC-g Ras Src MAPK Cell Proliferation

42. Effects of OSM and EGF on proliferation of MCF-7 cells. 120 100 80 60 Cell Number (% Control) * 40 20 N=10 0 EGF OSM Control OSM+EGF

43. Summary of Suzie’s work so far • Effects of OSM on breast cancer cells enhanced by EGF • Inhibition of proliferation • Decreased clonogenicity • Cell cycle suppression • Decreased ER expression • Differentiation • Mechanism?