Molecular interactions

1
Molecular interactions

• Based on Chapter 4 of
  Post-genome Bioinformatics by Minoru
  Kanehisa, Oxford University
  Press, 2000

2
Central dogma DNA -gt RNA -gt 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
D
C
(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
C
E
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)
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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
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.
CH3
EC number
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
HO
O
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
2.4.2.17
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
PRPP
Phosphoribosyl- Formimino-AICAR-P
Phosphoriboxyl-ATP
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
1.4.3.6
1.2.1.3
1.14135
3.5.2.-
3.5.3.5
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 (ab) 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
2.6.1.1
2.6.1.5
2.6.1.57
Pretyrosine
4.2.1.91
2.6.1.9
2.6.1.57
Phenylpyruvate
4.2.1.51
1.4.1.20
2.6.1.1
Prephenate
6.1.1.20
Indole
4.2.1.91
2.6.1.57
2.6.1.9
2.6.1.5
RNA
Phenylalanine
4.2.1.20
4.2.1.20
1.4.3.2
5.4.99.5
4.1.1.48
4.2.1.20
5.3.1.24
2.4.2.18
4.1.3.27
2.5.1.19
4.6.1.4
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
1.1.9925
1.1.1.25
4.1.3.-
3-Dehydro- quinate
Tryptophan metabolism
4.2.1.10
4-Aminobenzoate
Ubiquinone biosynthesis
4.2.1.10
4.2.1.11
3-Dehydro- shikimate
Protocatechuate
1.1.9925
1.1.1.24
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
5
6
5
D-Ribulose-5P
4
6
5
D-Ribose-5P
D-Fructose-1,6P2
7
Citrate cycle (TCA cycle)
Pentose Phosphate pathway
D-Sedoheptulose-7P
3
3
Glycerone-P
Glyceraldehyde-3P
NADH
NADH
(S )-Malate
Funarate
3
Glycerae-1,3P2
Oxaloacetate
4
4
4
ATP
FADH2
3
Glycerate-3P
Citrate
6
Glycerate-2P
3
4
Succinate
CoA
21
CoA
GTP
21
Isocitrate
Phophoenolpyruvate
6
CoA
CoA
3
21
21
CO2
CO2
NADH
ATP
3
10
23
5
5
12
25
2-Oxo- glutarate
Pyruvate
S-Acetyl- dihydrolipoamide
S-Acetyl- dihydrolipoamide
Acetyl-CoA
Succinyl-CoA
8
8
8
8
Lipoamide
Dihydro- lipoamide
Lipoamide
Dihydro- 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
2.7.1.11
3.1.3.11
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
1.2.4.1
2.3.1.12
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
A strategy for network reconstruction from
genomic information.
Reference knowledge (e.g. KEGG)
Predicted network by orthologue identification
Predicted network by path computation
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)
(d)
Metabolic network
Chemical network
Enzyme network
Protein-protein interaction network
Gene regulatory network


22
Biological examples of complex systems
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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

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Functional Reconstruction Problem (Sequence -gt
organism)

• 1. Genome is a blueprint of life
  (Dollys 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

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Pathway Assembly
31
DNA Damage
32
Suzie Grants 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

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Effects of IL-6, LIF, OSM, CNTF and IL-11 on
MCF-7 cell proliferation.


p lt 0.001 p lt 0.01 p lt 0.02

Cell No. ( Control)

n 9 expts.
14
IL-6
LIF
IL-11
OSM
CNTF
Control
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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

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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
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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
Src
Ras
PLC-g
MAPK
Cell Proliferation
42
Effects of OSM and EGF on proliferation of MCF-7
cells.
120
100
80
60
Cell Number ( Control)

40
20
N10
0
EGF
OSM
Control
OSMEGF
43
Summary of Suzies 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?