Novel Drug Discovery has proven to be immensely difficult

- To date, little impact of Human Genome Project

- Target validation remains a major challenge

8

10

12

No Launched Drugs/ New Targets/ New indications

First-in-Class (chemical)

New Targets

New Indications

Drugs often modulate multiple diseases

• Secondary indications

– 40% revenues of 1993 Top 20

– 38% revenues of 1999 Top 40

• 59% of new indications discovered by

Data: Derived from Drug News Perspect, Prous Science

Gelijns et al New Engl J Med 339 (10) 693-8

Pritchard et al ‘Capturing the unexpected benefits of medical research’, OHE 2001

DeMonaco, MIT Sloan Working Paper 4552-05

0

2

4

6

19901991199219931994199519961997199819992000

Year

No Launched Drugs/ New Targets/ New indications

• Need classification of diseases based

on targets/ pathways

clinicians in market place

CombinatoRx Inc

Borisy et al., (2003) PNAS 100:13, 7977–7982

Unexpected drug combinations

Known

anti-fungals

Known

anti-fungal +

non-fungal

agents

Two Two

non-fungal

agents

Examples• Fluconazole and phenazopyridine inhibits proliferation of fluconazole-resistant C. albicans• Corticosteroid and dipyridamole selectively inhibit cytokine production• Chlorpromazine (antipsychotic) and pentamidine (anti-protozoal) prevent tumor cell growth in vitro and in vivo

How do we assess benefit of combinations

Nature Medicine (2003) 9 (5), 510-511

Feed forward control

Feedback control

effectorcontroller

effectorcontroller

There is no such thing as a Selective Drug

Hopkins et al, Curr Op Struct Biol (2006), 16, 127-136

Cerep’s Bioprint Profiling: 2000 drugs in

200 molecular assays

Promiscuity of

kinase inhibitors for

cancer therapy

Sutent, SU11248: approved

for renal carcinoma, binds

79 kinases Kd < 10µM

Fabian MA et al,

Nature Biotechnology 23, 329 - 336

(2005)

Polypharmacology Opportunity of a Portfolio

44 targets + 135 target combinations

with existing compounds = 179 projects

No of compounds

active in 2 targets (<1uM)

>1000

1 - 10

10 - 100

100 - 1000

Targets coloured by gene family

Polypharmacology Strategies

P1

P1 &P2

P2

P1

P1P1

Drug

Combination

Cleavable

Conjugate

Conjugate Overlapping

Pharmacophore

Highly Integrated

Pharmacophore

Morphy, Kay & Rankovic, Drug Discov Today, (2004) 9, August, 641-651

P2 P2 P2

P2

Increase in MW and structural complexity

Increase in pharmacophore overlap

StARLITe

Bioactivity

Compound

Targ

et

Ki=4.5 nM>Thrombin (Homo sapiens)MAHVRGLQLPGCLALAALCSLVHSQHVFLAPQQARSLLQRVRRANTFLEEVRKGNLERECVEETCSYEEAFEALESSTATDVFWAKYTACETARTPRDKLAACLEGNCAEGLGTNYRGHVNITRSGIECQLWRSRYPHKPEINSTTHPGADLQENFCRNPDSSTTGPWCYTTDPTVRRQECSIPVCGQDQVTVAMTPRSEGSSVNLSPPLEQCVPDRGQQYQGRLAVTTHGLPCLAWASAQAKALSKHQDFNSAVQLVENFCRNPDGDEEGVWCYVAGKPGDFGYCDLNYCEEAVEEETGDGLDEDSDRAIEGRTATSEYQTFFNPRTFGSGEADCGLRPLFEKKSLEDKTERELLESYIDGRIVEGSDAEIGMSPWQVMLFRKSPQELLCGASLISDRWVLTAAHCLLYPPWDKNFTENDLLVRIGKHSRTRYERNIEKISMLEKIYIHPRYNWRENLDRDIALMKLKKPVAFSDYIHPVCLPDRETAASLLQAGYKGRVTGWGNLKETWTANVGKGQPSVLQVVNLPIVERPVCKDSTRIRITDNMFCAGYKPDEGKRGDACEGDSGGPFVMKSPFNNRWYQMGIVSWGEGCDRDGKYGFYTHVFRLKKWIQKVIDQFGE

John Overington

�2 million bioactivities

�30, 000 lead series

�12, 000 clinical candidates

�1300 drugs

Of 1284

disorders, 867

share at least

one gene with

Disease-Disease and Disease-Gene Networks

one gene with

another disorder

Goh, Kwang-Il et al. (2007)

Proc. Natl. Acad. Sci. USA 104, 8685-8690

Cysteine proteasesCysteine proteases

MetalloproteasesMetalloproteases

Aspartyl proteasesAspartyl proteases PhosphodiesterasesPhosphodiesterases

AminergicAminergic

GPCRsGPCRs

PeptidePeptide

GPCRsGPCRs

GPCRs (others)GPCRs (others)

Compounds hit multiple targets and gene families

Serine proteasesSerine proteases

Kinases

Nuclear hormone receptorsNuclear hormone receptors

Ion ChannelsIon Channels

Enzymes Enzymes

(others)(others)

Miscellaneous Miscellaneous

Paolini et al. Nature Biotechnology, (2006) 24,7, 805-815

• proteins = nodes = 486

• chemical interaction = line = 3636

• 25% of compds: significant interaction

between gene families

Redundancy: knocking out many proteins has no

effectYeast protein-protein interaction network- Y2H- Phenotypic effect of knocking out protein

Lethal

Non-lethal

Slow growth

Unknown

Lethality and centrality in protein networks, Barabási et al. Nature (2001), 411, 41

Error and attack tolerance of complex networks, Barabási et al. Nature, (2000), 406, 378Network Biology, Barabási & Oltvai, Nature Reviews Genetics (2004), 5,101-113

A robustness-based approach to systems-oriented drug design, Kitano, Nat. Rev. Drug Disc. 6, 202-210 (2007)

Yu H et al. PLoS Comput Biol. 2007 Apr 20;3(4):e59

c. Compound-Protein Networkb. Protein-Protein Network

Towards Network Pharmacology

a) Disease-Disease Network

c. Compound-Protein Network

Jeong et al Nature (2001) 411, 41-2

Goh et al PNAS 104(21) 8685-90

Yildirim et al Nat Biotech (2007) 25(10) 1119-1126

Paolini et al Nat Biotech (2006) 24(7) 805-15

Hopkins et al Nat Biotech (2007) 25(10) 1110-1

Rationale for NaV1.3• Axotomy (Leffler et al 01)

- increase in I – TTXs

- GDNF or NGF i.t partially reverse this

- GDNF and NGF i.t completely reverse this

• SCI (Hains et al 03)

- increase message in DHN

- i.t oligos decrease message and protein,

hyperexcitability of DHN, mech allodynia and thermal

hyperalgesia

- no effect on normal noxious or motor function

• CCI (Hains et al 04)

- increase message in DHN (not astrocytes or microglia)

- i.t oligos decrease message and protein, and

hyperexcitability of DHN

Rationale for NaV1.7 (PN1)

• Nasser et al 04- Expressed in injured peripheral nerves (also in symp

nerves)

- Global null dies shortly after birth

- nociceptor specific knock out – increased mech/ thermal

thresholds and reduced inflam responses

- dominant mutations lead to oedema, redness, warmth

and bilateral pain

Rationale for NaV1.8 (SNS)

• Lai et al 02 - SNL

- i.t oligos reduce expression and neuropathic pain behaviours

• Gold et al 03 - SNL- i.t oligos reduce expression in injured cell bodies

- does not redistribute to injured terminals

- little change in uninjured axons- little change in uninjured axons

- CAPs increased in injured nerves cf sham or contralateral

- aberrant activity in injured fibres is necessary

• Roza et al 03 - KO

- greater proportion of wild type neuromas exhibit mechanosensitive and spontaneous activity cf KO

• Stirling et al 05 - KO

- no effect on acute, inflam or neuro pain- upregulation of 1.7

Rationale for NaV1.9 (NaN)

• Dib Hajj et al (02)- cut neurones in periphery – decrease in message and I in DRG

- central cut does not decrease message, protein and I

- GDNF increase I- TTXr 3 fold (NSE with NGF)

• Craner et al (02)• Craner et al (02)- diabetic neuropathy increase in message and protein for

1.3, 1.6 and 1.9

- decrease in message and protein for 1.8

• Rush and Waxman (04)- increase I-1.9 in 1.8 null mice

Which channel should we work on?

Have data in:

• KO

- electrophysiology

- behaviour - behaviour

• Protein expression changes in variety of

models

• Anti-sense data

B. Avulsed (4d)

NaV1.8 - like i.r. in human DRG

A. Post Mortem

C. Avulsed (3 mo)

NaV1.9 - like i.r. in human DRG

A. Post Mortem

B. Avulsed (4d)

C. Avulsed (3 mo)

Inte

nsity o

f

imm

unore

activity

Some nerve fibres proximal to injury

Plasticity in localisation of 1.8 and 1.9Plasticity in localisation of 1.8 and 1.9

4 days 3 months 12 months

Inte

nsity o

f

imm

unore

activity

Time elapsed between injury & surgery

Injured DRG cell bodies

Sodium channels - summary

• Cell type localisation is different in rat and humans

• Localisation/ plasticity comparable for 1.8 and 1.9 in clinical tissueand 1.9 in clinical tissue

• Therapeutically need to block exaggerated afferent input (1.3 + 1.7 + 1.8 + 1.9…), but do not block skeletal muscle and cardiac channels

Epigenetic Code

• Genetic code is same in all cells in an organism

• Epigenetic code is cell and tissue specific

• Gene expression modulated by chromatin folding, • Gene expression modulated by chromatin folding,

chemical modifications and recruitment of

transcriptional machinery

• Epigenetic modifications are inherited, but may be

responsive to environment eg injury, stress,

exposure to toxins, diet….

Chemical modifications of

DNA and histone proteins

• DNA Methylation

• Covalent modifications • Covalent modifications

of histone tails

Modifications may be activating

or repressing

H3K4 H3K9 H3K27 H4K20

Me Activation Activation Activation ActivationMe

Me3 Activation Repression Repression

Ac Activation Activation

Methyl donors in utero enhance

airway disease in mice

• 82 genes methylated

• Decreased expression

• Increased disease severity

• Effects reversed by demethylating agent

Hollingsworth et al 08

High Methyl Diet (HMD)

increases allergic inflammation

Hollingsworth et al 08

RT: Airway hyper-reactivity/ resistance

Aerosolized methacholine

Ovalbumen challenge (6-10w)

Lung lavage

Diet: 2w prior to mating and pregnancy

HMD induced decrease in gene expression is

reversed by azacytidine (demethylating agent)

Hollingsworth et al 08

Runx3: Transcription factor

Azacytidine – in vitro

Decrease in HDAC and increase in HAT with

broncho hyper-responsiveness in asthmatics

Su et al 09

Severe <0.5, mild <5, non asthmatic >8mg/mL

Ex vivo in nuclear PBMC lysates

Peripheral nerve injury (PNI)

Increase Neurone Restrictive Silencer Factor (NRSF) in DRG

Bind to Neurone Restrictive Silencer Element (NRSE)

PNI induces epigenetic silencing of multiple genes

Bind to Neurone Restrictive Silencer Element (NRSE)

Decreased histone acetylation

Decreased transcription of mu opioid receptor, Nav1.8, Kv4.3

Uchida et al 2010, J of Neuroscience, Uchida et al 2010, Neuroscience

Decreased acetylation of mu opioid

receptor through NRSF binding

Uchida et al 2010, J of Neuroscience

Transient hyperglycemia produces long

lasting changes in human AECs

Transient hyperglycemia in HAECs

Increased reactive oxygen species

Increase in SET7Increase in SET7

Increase in H3K4me1

Increase in NFKβp65

Increase in MCP1 and VCAM1El-Osta 2008

Transient hyperglycemia produces

sustained elevation of SET7 binding and

H3K4me1

El-Osta 2008

Transient hyperglycemia produces

sustained elevation of p65 mRNA

El-Osta 2008

Greater maternal care increases GR

expression and reduces stress response

• Maternal care: increases histone acetylation, decreases DNA methylation,

increases TF NGFI-A binding and increases GR expression

• Methionine promotes methylation and Low LG phenotype

• HDAC inhibs increase acetylation and High LG phenotype

McGowan et al 08TSA – Trichostatin A (HDAC inhib), SAM – S adenosyl methionine

Childhood abuse decreases

glucocorticoid receptor

Post mortem hippocampus

Decrease GR expression causes exaggerated stress response

Also decreased NGFI-AMcGowan et al 09

Childhood abuse increases methylation

of glucocorticoid receptor

McGowan et al 09

Differentiated T cells have different marks

and hence different signature cytokines

•Genome wide

maps - ChIP Seq

•Signature cytokines

as expected

H3K4me3 -

activating

H3K27me3 -

repressing

as expected

Wei et al 09

Jmjd3 and Jarid2 are selectively increased

in activated macrophages

De Santa et al 07

Modulating a late stage mediator

is unlikely to be effective

Birth Death

Trauma - tissue damage/ nerve injury/ surgeryTrauma - tissue damage/ nerve injury/ surgery

- infection

- stress/ abuse

- ischemia

- toxins

- drugs 10 100 1000

Numbers of genes/ proteins, up/down regulated

Single modification can effect battery of genes

Wang et al, 08

CD4+ T cells

17 modifications in 3286 promoters

More modifications associated with increased expression

TSS = Transcription Start Site

Summary

• Very few diseases are single gene, single protein, single symptom and hence treated by single target molecules

• Need to integrate disease-disease, protein-protein, compound-protein, gene expression datasets to identify better drug targets

• Drugs for chronic diseases must act at multiple pathologies ie normalise networks or systems

• Environmental influences (diet, injury, high glucose, stress…) can chronically effect expression of multiple proteins

• Epigenetic targets offer significant potential in chronic diseases

Therapeutic Area aligned Drug

Discovery is not ideal

TA1

TA2TA2

TA3

TA4

TA5

“Drugs are discovered in the clinic,

not the laboratory”not the laboratory”

Edward T. Pratt, JrPfizer CEO 1972-1991

… and some new tricks...

40% of New Drugs originate outside pharma

36% of FDA approvals originated outside pharma

(21% Biotechs and 15% Universities)

Kneller, Nature Biotech, 23(5), 529-530

Protein-chemical networks

Protein A

Protein BChemical matter

Protein A

• Observed: e.g. Paolini et al Nature Biotech (2006) 24,7, 805-815

• Predicted: e.g. Keiser et al, Nature Biotech (2007) 25, 2, 197-206

»

Genome-wide

Compound-protein

networks

Predicting drug targets

Genome-wide mapping

Protein-protein networksJeong et al, Nature 411, 41 - 42 (2001)

Paolini et al, Nat. Biotech. 24, 805-815,(2006)

Yildirm et al Nat. Biotech (sunmitted)