Interrogating the Druggable Proteome:

Steven Muskal, Ph.D.Chief Executive OfficerEidogen-Sertanty, Inc.

smuskal@eidogen-sertanty.com

Target-Fishing and Drug Design

Discovery results from efficient collaboration

Chemistry Biology

Informatics(modeling)

What can be made

What should be made

• Number druggable targets: ~2000-3000

Commercially validated targets: ~200

• Same synthetic methods used through industry

Methods are published, “same” training

• Commercially available starting materials ~500-750K

“Clean”/Suitable ~ 250-300K

Pharma companies are playing "on the same end of the field"

Protein structure growth is accelerating

> 50K Structures/co-complexes (Aug-2008)> 600 deposits per month >150/week!

PDB Growthsource: rcsb.org

0

10000

20000

30000

40000

50000

60000

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year

PDB

Str

uctu

res

YearlyCumulative

Drugs developed using SBDD

Source: http://www.active-sight.com/science/sbdd.html

GlycosidaseNeuraminidaseRocheInfluenzaOseltamivir phosphate/Tamiflu, Zanamivir/Relenza

MetalloproteaseMatrix metalloproteaseAgouronCancerAG3340/Prinomastat

OxidoreductaseCox-2Searle, MerckInflammation, rheumatoid arthritis

Celecoxib/Celebrex, Rofecoxib/Vioxx

Methyl transferaseThymidylate synthaseAgouronCancerThymitaq

LyaseCarbonic AnhydraseMerckGlaucomaTrusopt

AspartylproteaseHIV-1 Protease

Roche, Abbott, Agouron, Merck, VertexAIDS

Saquinavir/Invirase, Ritonavir/Norvir, Indinavir/ Crixivan, Nelfinavir/Viracept, Amprenavir/Agenerase, Fosamprenavir/Lexiva,

ATP HydrolaseGyraseBayerBacterial infectionFluoroquinolone/Ciprofloxacin

Tyrosine kinasec-Abl kinaseNovartisChronic Myeloid LeukemiaSTI-571/Gleevec

Enzyme FamilyProtein targetedCompany(s)DiseaseInhibitor/Drug

• Knowledge-Driven Discovery Solutions Provider• Formed in March 2005 when Sertanty (Libraria Sertanty 2003) acquired Eidogen (Bionomix 2000)• >$20M Invested in Technology Development• 12 FTE’s• Worldwide Customerbase• Cash-Positive

About Eidogen-Sertanty

• DirectDesign™ Discovery Collaborations• In Silico Target Screening (“Target Fishing” and Repurposing)• Target and compound prioritization services• Fast Follower Design: Novel, Patentable Leads

• Chemogenomic Databases & Analysis Software• TIP™ - Structural Informatics Platform• KKB™ - Kinase SAR and Chemistry Knowledgebase• CHIP™ - Chemical Intelligence Platform

Eidogen-Sertanty Investors

Tavistock Life SciencesTavistock Life Sciences

Band of AngelsBand of Angels

HighBAR Ventures HighBAR Ventures ((Bill Joy, Andreas Bill Joy, Andreas BechtolsheimBechtolsheim, Roy Thiele, Roy Thiele--SardiSardiññaa))

Technofyn Technofyn (Alejandro Zaffaroni)(Alejandro Zaffaroni)

The Athenaeum FundThe Athenaeum Fund

Automated Modeling and Proteomic Structural MiningSequence-to-Structure Calculation Cascade Search-by: KeyWord, Sequence, Ligand, Protein Structure, Receptor-Sites, etc. Exploit Structural fold and receptor-site conservation

Off-Target Identification (opportunities v. liabilities)

Borrowing Matter Ideas from co-complexes and other drugs

Bringing Proteomic riches to non-specialists

Viracept

HIV protease

Cathepsin D

N

S

N

NH

OHN

CK5

O N

N

NH OHO

DTQ

O

NH

N

NH

O

NH

1PU

O

NH

NNH

N5B

NNH

NNH

OOH

COX-2 / SC-558 complex

Sulfotransferase SULT1E1(Drug Metabolism)

Using both target and compound similarity

SiteSorter™

Same Family Different Target FamilySimilar Sites In The Human Proteome

PharmSim™

Similar Drugs & Available Compounds2D Similar Pharmacophore Similarity

N

O

O

O

NCN

OO

O

NC

N

OO

OO

NC

N

OO

NO

NC

N

N N

N

S

O

O O

NO

N

O

Cl

O

N

S

N

N

SO

NN

S

OO

O

> 400KSequences

> 158KChains &Models

> 388KSites

> 33MSequence Similarities

> 75MStructure Similarities

> 74MSite Similarities

TIP algorithm engine

Reference: Interrogating the druggable genome with structural informatics, MolecularDiversity (2006)

PXR – Promiscuous ligand-binding siteQuery: PXR site

Bile Acid Receptor FXR

PPAR-gamma receptor

ACE2

Thyroid Receptor Caspase-3

HMG-CoA Reductase (statin target)

Site Similarity Coloring

Highly Similar Receptor regions

Dissimilar Receptor regions

Example High-ranking similar sites:

Pregnane X-receptor –PXR (“sensor)” CYP3A4 (“executioner”)PXR Binds > 50% drugsIncluding some bile acids, statins, herbal components, a selection of HIV protease inhibitors, calcium channel modulators, numerous steroids, plasticizers and monomers, organochlorinepesticides, a peroxisomeproliferator-activated receptor-ãantagonist, xenobiotics and endobiotics…

...1 0 1 ...11 0 100

A

A A

2-4.5

R

19-24

2-4.5

2-4.519-24

19-24

R

R

D

H P4.5-7

7-10 10-14

Journal of Chemical Information and Computer Sciences, 1999, 39 (3) : 569-74

Ligand pharmacophoric potential

Ligands grouped by pharmacophoric potential

NMDA Receptor AntagLeukotriene AntagPAF AntagAngiotensin II Blocker Ca Channel Blocker K Channel Activator Substance P AntagACAT Inhibitor Cyclooxygenase InhibLipoxygenase Inhib

Journal of Chemical Information and Computer Sciences, 2000, 40 : 117-125

O

N

S

N N

N+

O

O

RANITIDINE (Zantac)

Target: Histamine H2-antagonist

MWT: 314.4; LogP: 0.27; pKa [2.30, 8.20]Oral Avail.: 52% (±11)Urinary Excretion: 69% (±6)Plasma Bound: 15% (±3)Clearance: 730 mL/min (±80)Half-Life: 2.1 hr (±0.2)Effective Conc.: 100 ng/mL

N

N

SN

N

N

N

CIMETIDINE (Tagamet)

Target: Histamine H2-antagonist

MWT: 252.3; LogP: 0.40; pKa: [6.80] Oral Avail.: 62% (±6)Urinary Excretion: 62% (±20)Plasma Bound: 19%Clearance: 540 mL/min (±130)Half-Life: 1.9 hr (±0.3)Effective Conc.: 800 ng/mL

Eidogen-Sertanty Pharmacophoric Similarity Score, PharmSim= 0.88/1.00

Drug similarity example - Non-obvious “Me-Too’s”

N

O

O

F

O O

O

N

N

O

O

F

O O

O

Chiral

ATORVASTATIN (Lipitor) 172577 – Takeda

Drug similarity example (cont)

Eidogen-Sertanty Pharmacophic Similarity Score, PharmSim= 0.79/1.00

Target: HMG-CoA Reductase2007 Sales >$12.8B (worldwide)

Target: HMG-CoA Reductase

In silico target screening (“Target Fishing”)

Off-target opportunities

C-KIT - G

Intra-Family Opportunities Inter-family Opportunities

B-RAF

C-KIT

BAY 43-9006

Sequence ID = 30%Site ID = 60%

Top 10 SiteSorter rank

B-RAF inhibitor BAY 43-9006 also inhibits C-KIT

Viracept

Cathepsin D is inhibited by HIV protease inhibitors

HIV protease

Cathepsin D

Key contacts conserved

Celebrex analog SC-558(Pfizer – Celebrex 2004 Sales $3.3 B,

black-box warning in 2005){Bextra pulled from market in 2005]

Identifying “off-target” opportunities and liabilities

LIMK1 – ATP binding site comparison LIMK1 

AURKA  SRC 62% ID in ATP Site 

>3000 inhibitors in KKB 

58% ID in ATP Site 

>5100 inhibitors in KKB 

­ H­bond donors ­ H­bond acceptors ­ H­bond donor/acceptors 

LCK 58% ID in ATP Site 

>8200 inhibitors in KKB 

­ Conserved with LIMK1 ­ Not conserved with LIMK1 

The ATP site of LIMK1 shares a high level of homology with several well­studied kinases

Kinase Targets of Clinical Interest from Vieth et al. Drug Disc. Today 10, 839 (2005).

Eidogen-Sertanty KKB SAR Data Point Distribution

Primary targets w/ reportedclinical data

Reported secondary targets & targets w/ >60% ID

Kinase SAR Knowledgebase – Hot Targets

>362,000 SAR data points curated from >4,270 journal articles and patents

>130 Bayesian QSAR Models

Kinase Knowledgebase (KKB)Kinase inhibitor structures and SAR data mined from

> 4100 journal articles/patents

KKB Content Summary (Q1-2008):# of kinase targets: >300# of SAR Data points: > 345,000# of unique kinase molecules with SAR data: >118,000# of annotated assay protocols: >15,350# of annotated chemical reactions: >2,300# of unique kinase inhibitors: >463,000 (~340K enumerated from patent chemistries)

KKB Growth Rate:• Average 15-20K SAR data points added per quarter• Average 20-30K unique structures added per quarter

Kinase Validation Set

Three sizable datasets freely available to the research community

http://www.eidogen-sertanty.com/kinasednld.php

0.00001

0.0001

0.001

0.01

0.1

1

0 0.2 0.4 0.6 0.8 1Tanimoto Similarity to Known Active

P(A

ctiv

e)

Fast follower design - Novel active chemotypes in 5-50 molecules

AvailableCompounds

Weak IPKnown CompoundNew Application

Direct-DesignsStronger IP

Novel CompoundsNew Applications

IPAlreadyBlocked

Probabilityof

Activity

Similarity to Known Actives

Direct-Designs

Synthetically accessible molecule design

ChIPTM

Schurer et al. J. Chem. Inf. Model. 45(2), 239-248, 2005.

Success requires efficient “cause-effect” feedback

That which is synthetically “feasible:”• In-house expertise• Starting material availability• Cost/time

That which is medicinally relevant, efficacious, and safe:• Potency• Selectivity• Bioavailability• Low toxicity• Cost effective

What can be made?

What should be made?

Direct Design Case 1: Using SAR information

Sawyers, C. L. et. al. Cancer Cell 2002, 2, 117

Previously published ABL inhibitors

H2NN

NNH

NNH2

N

N N

HO

N

N

O

HN NH

N N

N

MeO N

N

HN Br

MeO

NH2

N

N N

0.002 µM (Traxler et. al. Novartis) 0.005 µΜ

0.038 µM (Zimmermann et. al. Novartis)

Gleevec

0.03 µM (Bridges et. al. Parke Davis)

0.02 µM

(Widler et. al. Novartis)

ABL Kinase Project

Capture known ABL-kinase SAR data

27 journal articles / patents413 small molecules

Build a pharmacophoric eScreenTM modelGrouping of comparable IC50 SAR data based on assay type, binding site, assay conditions3-point pharmacophore fingerprints

Data Capture – Model Development

Generation of 60,000 member virtual Library using 15,000 commercially available carboxylic acids

Identification of best building blocks by pharmacophoric-based eScreenTM and eADMEprioritization

Synthesis of 80 compounds of this scaffold

Virtual Library Analysis – Synthesis

Measured IC50 (predicted IC50)

8 Compounds with IC50 ≤ 10 µM (initial synthesis)

NH

O

OHNH

O

OCN

NH

O

OHNH

O

S

O

OO

CN

NH

O

OH

NH

O

N

N

CN

OH

ONH

NH

O

O

CN

OH

ONH

NH

O

S

O

O O

CN

NH

O

OHNH

O

N

N CN

O

O

N

O

NH

NH

O

OHH CN

NH

O

OHNH

O

N

N CO2Me

4 (9) µM

5 (7) µM

3 (4) µM

1a1k

2k

2q

1q 1j

2j

3j

5 (5) µM

8 (8) µM

10 (21) µM

10 (9) µM

7 (6) µM

Assay Results

NH

O

R

R

NH

R

JP2001-089471, Japan Tobacco, Inc.

(claimed as PDGFR inhibitors)

Data CapturePredictive model building

Data analysis and scaffold extraction

Scaffold hopping

Synthesis of compoundsBio assay

Design proliferation,Prioritization, and in silico screening

4 months

ABL Project Summary

Direct Design Case 2: Using co-complex information

Lead Discovery: Knowledge-Based Design

N

S

N

NH

OHN

CK5

O N

N

NH OHO

DTQ

O

NH

N

NH

O

NH

1PU

O

NH

NNH

N5B

NNH

NNH

OOH

Similar to Vertex’s BREED: J. Med. Chem. 47, 2768 (2004).

From ligand query to sites to new ligand ideas

Example Ligands Extracted from Similar Sites

LigandCross – Mixing Ligand Features from Aligned Sites

Example LigandCross Results

LigandCross Ligands with Reported Biological Activity

Direct Design Case 3: Using Active Molecule(s)

ChIP-ing Towards Me-Too’s

Known PDE-IV Inhibitors

PharmSim: 0.93MDLSim: 33.1/100.0

PharmSim: 0.92MDLSim 44.4/100.0

N

N N

N

S

O

O O

N

O

O

O

NC

ChIP’d Me2

N

S

O

ON

N

O

Cl

N

SO

O

PharmSim: 0.92MDLSim 50.6/100.0

ChIP’d Me2

Other ChIP Generated PDE-IV “Me-Too’s”

N

N N

N

S

O

O O

NO

N

O

Cl

O

N

S

N

N

S

O

NN

S

OO

O

N

O

O

F

OS

N

NN

NO

O

O O

ON

N

N

S

O

N

Cl

O

NN

N

O

N

N

Cl R

RR

NH2R N

N

NH

RR

RR

r7005+

R Cl

ONH

RRN

OR

RR

r7049+

N

N

ClO

NH2

O

SOO

NNH

O

SOO

N

N

N

O

MFCD00194055MFCD00009045

+

PFP Sim 0.8623

N

N

Cl

O

O

Cl

O

NH2N

S

N

N

N

O

O N

S

O

MFCD00274530

MFCD00005325

MFCD00000717

+

PFP Sim 0.9375

Example ChIP Generated Synthetic Road-Maps

Conclusions

• Significant receptor-site similarities exist within and

across target families

• The structurally resolved and modelable proteome

is a very rich source for new matter ideas

• Biologically active molecules can be used to

generate other very novel, bioactive molecules

Acknowledgements

• Stephan Schürer

• Kevin Hambly

• Joe Danzer

• Brian Palmer

• Derek Debe

• Aleksandar Poleksic

• Accelrys/Scitegic - Shikha Varma-O'Brien/Ton van Daelen

• ChIP: National Institute of Standards and Technology (NIST) –ATP program: ‘Chemical Intelligence Platform for Rapid Discovery of DrugLeads’

ContactSteven Muskal

Chief Executive Officersmuskal@eidogen-sertanty.com