Molecular interactions

Based on Chapter 4 of Post-genome Bioinformatics

by Minoru Kanehisa, Oxford University Press, 2000

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.

1) Element

MoleculeGene

2) Binary Relation

Molecular interactionGenetic interactionOther types of relations

3) Network

Pathway

AssemblyNeighbour Cluster

Hierarchical TreeGenome

Representation of the same graph by: (a) a drawing of nodes and edges, (b) a linked list, and (c) an adjacency matrix.

(a)

A

B

DC

E

F

(b) A B

B A C D

C B E

D B E

E C D F

F E

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

(c)

Biological examples of network comparisons.

Pathway vs. Pathway

Pathway vs. Genome

Genome vs. Genome

Cluster vs. Pathway

Pathway alignment is a problem of graph isomorphism: (a) a maximum common induced subgraph and (b) a maximum clique.

(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)

(b)

(a) Pathway 1 Pathway 2A

B

C

D

E

a

b c

d

A

A

B-a

B-b

C-d

D-f

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).

A - a

B - b

C - c

D - d

. . .

. . .

Clusteringalgorithm

A BC

D

E G

H

K

F

I

J

A BC

D

E G

H

K

F

I

J

a bc

d

e g

h

k

f

i

j

a bc

d

e g

h

k

f

i

j

(a)Graph 1 Correspondences Graph 2

(b) A-B-C-D-E-F-G-H-I-J-K

: : :

A-c-b-d-e-f-h-g-j-k-i

Examples of binary relations

Type of relation Contents ExamplesFactual relation

Similarity relation

Functional relation

Links between databaseentities

Computed similarityComputed complementarity

Molecular reactionsMolecular interactionsGenetic interactions

Chromosomal relationsEvolutionary relations

Factual data and its publication informationNucleotide sequence and translated aminoacid sequenceProtein sequence and 3D structure

Sequence similarity: 3D stuctural similarity3D structural complementarity

Substrate-product relationsMolecular pathways; molecular assembliesPositively co-expressed genesNegatively co-expressed genesCorrelation of gene locations (operons)Orthologous and paralogous genes

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.

H3C

O

O

OHC00022

O

OH

CH3

NH2

1.4.1.1

O

OH

CH3

NH2

2.6.1.21 5.1.1.1

OH

O

O

HOO

C00036

O

OH

NH2

O

OH

C00049

1.4.3.16

C00133

4.1.1.124.1.1.3

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

Network data representation in KEGG

Network type KEGG data Content RepresentationPathwayAssembly

Genome

Cluster

Pathway map

Genome mapComparative genomemap

Expression map

Metabolic pathway, regulatory pathway, andmolecular assembly

Chromosomal location of genes

Differential gene expression profile bymicroarrays

GIF image map

Java applet

Java applet

NeighbourPathway AssemblyGenome

Hierarchical tree

Orthologue grouptable

Gene catalogueMolecular catalogueTaxonomyDisease catalogue

Functional unit of genes in a pathway orassembly, together with orthologous relationof genes and chromosomal relation of genes

Hierarchical classification of genesHierarchical classification of moleculesHierarchical classification of organismsHierarchical classification diseases

HTML table

Hierarchical text

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

(b) Metabolic pathway

Pentose phosphate cycle

Purine metabolism

HISTIDINE METABOLISM

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

3.5.1.-

2.6.1.-Phosphoribulosyl-Formimino-AICAR-P

Phosphoribosyl-Formimino-AICAR-P

Phosphoribosyl-AMP

Phosphoriboxyl-ATPPRPP

5P-D-1-ribulosyl-formimine

Imidazole-Glicerol-3P

Imidazole-acetole P

L-Histidinol-P

1.1.1.23

2.1.1.-

6.3.2.11

2.1.1.22

6.3.2.11

3.4.13.5

3.4.13.20

3.4.13.3

4.1.1.22

4.1.1.281.4.3.61.2.1.31.141353.5.2.-3.5.3.5

N-Formyl-L-aspartate

Imidazoloneacetate

Imidazole-4-acetate

Imidazoleacetaldehyde Histamine

Carnosine

Aneserine

1.1.1.23

6.1.1

1-Methyl-L-histidine

L-Hisyidinal

L-Hisyidinal

5P Ribosyl-5-amino 4-Imidazole carboxamide(AICAR)

L-Histidine

Hercyn

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.

……..NE, TYROSINE AND TRYPTOPHAN BIOSYNTHESIS Tyrosine metabolism

Alkaloid biosynthesis I

2.6.1.9 2.6.1.57

2.6.1.1 2.6.1.5

6.1.1.1

1.4.3.2

2.6.1.9 2.6.1.57

2.6.1.1 2.6.1.5

4.1.1.48 4.2.1.20

4.2.1.20

4.2.1.20

Tryptophanmetabolism

5.3.1.242.4.2.184.1.3.272.5.1.19

2.7.1.71

1.1.99251.1.1.25

4.2.1.10

4.2.1.11

1.1.99251.1.1.24

Quniate

4.2.1.91

4.2.1.51

2.6.1.57

2.6.1.572.6.1.92.6.1.5

1.4.1.20 2.6.1.1

1.4.3.2

6.1.1.20

4.2.1.91

4.2.1.51

1.14.16.1

1.3.1.43

Tyr-tRNA

4-Hydroxy-phenylpyruvate

Prephenate

Tyrosine

Pretyrosine

RNA Phenylalanine

5.4.99.5

4.6.1.4

Anthranilate

Histidine

N-(5-Phospho--v-ribosyl)-anthranilate

1-(2- Carboxy-Phenylamino)-1-deoxy-D-ribulose5-phosphate

(3-Indolyl)-Glycerolphosphate

Indole

L-Tryptophan

4.1.3.-

Folatebiosynthesis

Ubiquinone biosynthesis

Chorismate

4-Aminobenzoate

4.6.1.3

3-deoxy-D-arabino-heptonate

3-Dehydro-quinate

4.2.1.10

3-Dehydro-shikimate

Protocatechuate

Shikimate

Phenylpyruvate

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

Grand challenge problems

Protein folding problems Organism reconstruction problem

Prediction Structure prediction - to predict protein 3Dstructure from amino acid sequence

Network prediction - to predict entirebiochemical network from completegenome sequence

Knowledge Known protein 3D structures Known biochemical pathways andassemblies

Knowledge based prediction Threading Network reconstruction

Ab initio prediction Energy minimization Path computation

Prediction of perturbed states Protein engineering Pathway engineering

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.

66 6 6

56

6

33

3

3

3

3

3

8

5

54

7

8

10

21

23

NADPH

NADPH

D-Ribulose-5P

D-Ribose-5P

PentosePhosphatepathway

6-Phospho-

D-gluconate

D-Glucono-1,5-Lactone-6P

D-Glucose-6P

D-Glucose

CO2D-Xylulose-5P

D-Fructose-6P

D-Fructose-1,6P2

D-Sedoheptulose-7P

NADH

ATP

Glycerone-PGlyceraldehyde-3P

Glycerae-1,3P2

Glycerate-3P

Glycerate-2P

Phophoenolpyruvate

ATP

Pyruvate

NADH

Lipoamide

CO2

S-Acetyl-dihydrolipoamide

Dihydro-lipoamide

Acetyl-CoA

6

44

6

55

88

12

21

25

NADH

Lipoamide

CO2

S-Acetyl-dihydrolipoamide

Dihydro-lipoamide

Succinyl-CoA

4

NADH

(S )-MalateFunarate

4

FADH2

GTP 21CoA

CoA CoA

NADH

Isocitrate

Citrate

21CoA

Oxaloacetate

Citrate cycle(TCA cycle)

2-Oxo-glutarate

Succinate

Glycolysis viewed as a network of enzymes (gene products). Each box is an enzyme with its EC number inside.

2.7.1.2

5.3.1.1

2.7.1.401.2.1.51

1.2.4.1

1.8.1.4

2.3.1.126-S-Acetyl-dihydrolipoamide

Citrate cycle(TCA cycle) Phosphoenolpyruvate

Acetyl-CoA

Dihydrolipoamide Lipoamide

Pyruvate

4.2.1.11

5.4.2.1

Glycerate-2P

2.7.2.3

Glycerate-3P

Gycerate-1, 3P2

1.2.1.12

4.1.2.13

2.7.1.113.1.3.11

Glycerone-PGlyceraldehyde-3P

D-Fructose-1,6P2

D-Fructose-6P

5.3.1.9

2.7.1.69PentosePhosphatecycle

D-Glucose-6P

D-Glucose(extracellular)

D-Glucose

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 2Enzymic reaction

Protein 1 Protein 2

Gene(Molecular template)

Gene expression

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

A strategy for network reconstruction from genomic information.

Reference knowledge(e.g. KEGG)

Predicted network byorthologue identification

Predicted network bypath computation

Gene cataloguein the genome

Genetic and chemical blueprints of life.

Blueprint Entity Information

Genetic blueprint of life Genome Centralized Static

Chemical blueprint of life Network of interactingmolecules in the cell

Distributed Dynamic

Principles of the biochemical network encoded in the genome.

Hierarchy - conservation and diversification

(a)(b)

Duality - chemical logic and genetic logic

(c) (d)

Low resolution network

High resolution network

Divergent inputs Divergent outputs

Conserved pathway

+ =

Chemicalnetwork

Enzymenetwork

Metabolicnetwork

Protein-proteininteraction network

Gene regulatorynetwork

Biological examples of complex systems

System Node Edge

Protein 3D structure Atom Atomic interaction

Organism Molecule Molecular interaction

Brain Cell Cellular interaction

Ecosystem Organism Organism interaction

Civilization Human Human interaction

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

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

Pathway Assembly

DNA Damage

Suzie Grant’s Study: AimsSuzie 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.

IL-6 Cytokine Receptor Family.IL-6 Cytokine Receptor Family.

IL-6IL-11

CNTF LIFOSMCT

OSM

IL-6R CNTFR

IL--11RLIFRgp130gp130 gp130 OSMR

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

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

Physiological Functions of IL-6 family membersPhysiological Functions of IL-6 family members

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

Con

trol

IL-6

LIF

OS

M

CN

TF

IL-1

1

n = 9 expts.

14

0

20

40

60

80

100

120

Cel

l No.

(%

Con

trol

)

* p < 0.001# p < 0.01+ p < 0.02

*

#

#

+

Effects of OSM on breast cancer cells.Effects of OSM on breast cancer cells.

• OSMR 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

S

GRB2

OSM

JAK1

YY

YY

JAK1P P

P

PP

P

P

PSTAT3

P

P

P

P

Nucleus

Cytoplasm

P

P

P

P

TranscriptionFactors

SHC

SOS RAS

RAF

MEK

MAPK

?

P

P

P

Cell Membrane

OSM SignallingOSM SignallingOSMR

orLIFR

gp130

STAT3

STAT3Transcription

(ERK1/2)

Signalling by IL-6 Type CytokinesSignalling 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

• 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

EGF family of growth factors and receptorsEGF family of growth factors and receptors

EGF family of receptorsEGF 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

EGF signallingEGF signalling

EGF

PI3K SrcRasPLC-

MAPK

Cell Proliferation

EGFREGFR,ErbB-2,3 or 4

Effects of OSM and EGF on proliferation Effects of OSM and EGF on proliferation of MCF-7 cells.of MCF-7 cells.

Co

ntro

l

EG

F

OS

M

OS

M+

EG

F

0

20

40

60

80

100

120C

ell

Nu

mb

er (

% C

on

tro

l)

*

N=10

SummarySummary

• Effects of OSM on breast cancer cells enhanced by EGF– Inhibition of proliferation

– Decreased clonogenicity

– Cell cycle suppression

– Decreased ER expression

– Differentiation

• Mechanism?