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Molecular interactions

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Title: Molecular interactions


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

2
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
3
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
4
Biological examples of network comparisons.
Pathway vs. Pathway
Pathway vs. Genome
Genome vs. Genome
Cluster vs. Pathway
5
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)
6
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
7
Examples of binary relations
8
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
O
1.4.1.1
OH
H3C
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
9
Query relaxation. Nodes E and E are considered
to be equivalent according to the grouping G.

A B B C G C D
B E E E E F
A B C D E F
10
Network data representation in KEGG
11
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
12
(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
13
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
14
Grand challenge problems
15
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
16
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
17
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)
18
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
19
Genetic and chemical blueprints of life.
20
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)
Chemical network
Enzyme network
Metabolic network
Protein-protein interaction network
Gene regulatory network


21
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

30
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

31
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34
Pathway Assembly
35
DNA Damage
36
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.

37
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
38
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

39
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
40
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

41
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
42
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

43
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

44
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

45
EGF signalling
EGFR, ErbB-2, 3 or 4
EGF
EGFR
PI3K
Src
Ras
PLC-g
MAPK
Cell Proliferation
46
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
47
Summary
  • Effects of OSM on breast cancer cells enhanced by
    EGF
  • Inhibition of proliferation
  • Decreased clonogenicity
  • Cell cycle suppression
  • Decreased ER expression
  • Differentiation
  • Mechanism?
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