John Christopher & Jonathan Mason

4th RSC/SCI Symposium on GPCRs in Medicinal Chemistry.

Windlesham September 2012

GPCR fragment-based design and a novel structure-

based perspective on druggability

Non-Confidential

Heptares Therapeutics

Breakthrough medicines targeting previously undruggable GPCRs

$40M from leading venture investors since 2009

Major R&D partnerships with multiple large pharma companies

Structure-Based Drug Design for GPCRs, enabled for the first time by StaRs

(Stabilised Receptors)

Leading GPCR capability in industry, integrating chemistry & structural biology

Engine creating both small molecule NCEs and antibody therapeutics

Exceptional pipeline of investigational medicines for serious diseases

1

Non-Confidential

GPCR Discovery Preclinical Phase 1 Phase 2 Indication(s)

Muscarinic M1 Alzheimer’s Disease, Schizophrenia

Orexin 1 Binge Eating, Nicotine Addiction

Dual Orexin 1/2 Chronic Insomnia

GLP-1 Type 2 Diabetes (First Oral NCE)

GPR39 Type 2 Diabetes (Disease Modifying)

mGlu5 Autism, Dyskinesia, Depression

CGRP Migraine Treatment & Prophylaxis

Adenosine A2A / Progress Confidential CNS Disorders

Progress Confidential CNS Disorders

Progress Confidential Undisclosed

Progress Confidential Antibody Therapeutics

Progress Confidential Undisclosed

Heptares Product Pipeline

MedImmune

Non-Confidential

Outline of Presentation

Fragment Screening Methods

Fragment H2L examples

A Water perspective...

– Druggability

– SAR & Kinetics

3

Non-Confidential

SPR kinetics /

stoichiometry

Radioligand binding

Thermal shift

CE

StaRs enable Fragment Screening

NMR

HCS

SPR

SAR

Structural model

BPMX-ray

Primary screening

validated with

• SPR

• NMR

• HCS

• CE

Hits triaged by

• SPR kinetics

• SPR stoichiometry

• Binding assays

• Thermal shift

Hits validated by

• SAR / analogues

• X-ray / modelling

• BPM / SDM

Primary

Screening

Hit

Confirmation

Hit

Validation

4

Non-Confidential

SPR Fragment Screening POC

A2A StaR

DPCPX

riboflavin

caffeine

theophylline

1-methylxanthine

3-methylxanthinexanthine

7-methylxanthine

hypoxanthineallopurinol

FADDPCPX

riboflavin

caffeine

theophylline

1-methylxanthine

3-methylxanthinexanthine

7-methylxanthine

hypoxanthineallopurinol

FAD

Highly stable surface

– DPCPX controls

Inactive fragments

Weak (mM) fragments

easily detected

More potent (mM)

fragments

Weakly binding fragments hits easily discriminated from inactives

Xanthines added to library as likely binders

Chip stable for days Congreve, M. et al, Methods Enzymol. 2011, 493, 115

5

Non-Confidential

Vs. plots

-10

10

30

50

70

-10 10 30 50 70

A2A

b1A

R

Adenosine A2A and b1 Adrenergic Receptor (b1 AR)

SPR screen

b1 selective

hits

A2A selective

hits

Non-selective

hits

Standard

Similar results for screening Heptares

fragment library against A2A and b1AR

6

Non-Confidential

NMR Screening: b1AR (with ZoBio)

TINS = Target Immobilized NMR Screening:

Immobilized protein – only small amounts needed (~1mg)

Very sensitive method: mM hits identified (not found by SPR)

7

Congreve, M. et al, Methods Enzymol. 2011, 493, 115

Non-Confidential

High Concentration Screening

Lipid Receptor Agonist StaR

Agonist StaR binds known agonists with higher

affinity compared to wild-type receptor (binding

assay radioligand usage significantly reduced).

10% DMSO has a minimal effect on ligand-binding

to the StaR in membranes, unlike wild-type.

Enables high concentration (100 mM) fragment

screening which is not feasible with wild-type.

Approx 6% hit rate (84 / 1419 fragments inhibit

binding > 30%, n = 2).

StaR

-12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2

0

1000

2000

3000

4000

1%

5%

10%

[DMSO]

Log [Agonist] (M)

Bo

un

d lig

an

d (

cp

m)

Wild-type

-11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1

0

5000

10000

15000

20000

25000

Log [Agonist] (M)

Bo

un

d lig

an

d (

cp

m)

0 20 40 60 80 100

0

20

40

60

80

100

% inhibition of specific binding (n = 2)

% in

hib

itio

n o

f s

pe

cif

ic b

ind

ing

(n

= 1

)

8

Non-Confidential

Outline of Presentation

Fragment Screening Methods

Fragment H2L examples

A Water perspective...

– Druggability

– SAR & Kinetics

9

Non-Confidential

Hit to lead example 1:

CXCR4 Chemokine Receptor Antagonist

39 hits (4.8%) from 808 molecules

(fragments + targeted screening set)

Follow up gives clear SAR

Rapid identification of potent hit

series with considerably better

profile than gold standard

Hit Series Exemplar

Ki = 10 nM (LE = 0.34)

Good solubility

MWT 300, cLogP 1.3, PSA 76

N

NH

NH

NH

N

NH

NH

NH

Example fragment hit

Ki = 150 mM (LE = 0.47)

Good solubility

MWT 144, cLogP 1.3, PSA 39

PlerixaforDosed s.c.

MWT = 502

cLogP = -0.2

10

Non-Confidential

Hit to lead example 2:

b1AR antagonists

N

NH

F

FF

KD = 16 mM

Caffeine

b1

Control

A2A

Control

b1 Hits

A2A Hits

A2A

b1A

R

Typical results for „well behaved‟ hits

SPR screening

with A2A as

counter screen

Several related hits

11

Non-Confidential

NH OH

O

OH

NH

O

Analoguepurchasing

SPR hit

KD = 16 mM

LE = 0.41

IC50 = 7 mM

Binding Assay

LE = 0.50

b1AR: Structure-guided hit to lead progression

Analoguepurchasing

N

NH

F

FF

Warne, T. et al.Nature 2011, 469, 241

IC50 = 58 nM

Binding Assay

LE = 0.66

MW <250, Highly soluble

Non-Confidential

b1AR: Fragment X-ray crystallography

• Protein-Fragment crystal co-crystal complexes solved to high resolution.

• Novel chemical matter, breaking the mould of existing chemistry.

- Lack aminoalcohol motif

Non-Confidential

11 GPCRs (Family A, B & C) screened in 14 assays

GPCRs are highly comparable to enzyme targets in terms of quality of hits,

when StaR proteins are used for screening.

* StaR assay

Comparison of Heptares GPCR Fragment

Hits with Enzyme Targets

Target Method Hit LE

Adenosine A2A TINS NMR 0.56

Adenosine A2A SPR 0.53

Family A aminergic SPR 0.41

Family A peptidergic SPR 0.31

Family A lipid HCS 0.55*

CXCR4 HCS 0.47

Target Method Hit LE

Protein kinase B X-ray soak 0.47

DPPIV HCS 0.46

Thrombin X-ray soak 0.40

BACE SPR ~0.30

HSP90 NMR 0.53

PDE4 HCS 0.46

14

Non-Confidential

Outline of Presentation

Fragment Screening Methods

Fragment H2L examples

A Water perspective...

– Druggability

– SAR & Kinetics

15

Non-Confidential

GPCR structural information can be revolutionary – previously we were

biased by ligand + analogs data

Beware of biases in how we see and “force-fit” data

Courtesy of Arthur Doweyko,

Non-Confidential17

Why Water?

Water molecules play an essential role in the structure and function of

biological systems

-appear to play a key role in the GPCR structures available to date, perhaps due

to the deep pockets present in the GPCR transmembrane binding sites?

Displacement of waters from a binding site is a key component of ligand

binding, with significant binding energy, and thus potency, often from the

entropic gain of the displacement

But all waters are not equal…

- Burying an ”unhappy” water [i.e. entropically and/or enthalpically worse

than bulk sovent] may affect both potency and kinetics

- Pertubation of the remaining waters will also affect binding ±

Opportunity to provide new insights into druggability, to drive SAR and find

solutions to many SAR issues (predicition of ”magic methyl”, SAR not explainable

by direct ligand-protein interactions...)

Non-Confidential18

Water: The new wave...

New computational approaches now available that can create water

networks (with or without a ligand present)

+ energetically differentiate ”happy” and ”unhappy” waters

Favourable binding sites contain multiple ”unhappy” waters, with a cluster

being particularly favourable ( higher affinity/LE fragment hits etc...)

- in an environment compatible with a drug-like molecule (mixture of

hydrophobic & hydrophilic hotspots rule of 5 etc properties)

OH

Ser

OH

Ser

OH

Ser

... e.g. not all serines are the same

All pockets are equal, but somepockets are more equal than others

Non-Confidential

The New Wave: WaterMap (Schrödinger) + GRID (Mol. Discovery)

Abel et al.

19

GRID Map contoured at:

Aromatic CH (lipophilic) probe: Yellow

-2.5 kcal/mol

Water probe: Green -6.0 kcal/mol

Surface defined by CH3 probe: Grey

1.0 kcal/mol

1. MD simulation and clustering technique to build a map of water occupancy in the factor Xa active site2. Chemical potentials assigned to the water sites using the inhomogenous solvation theory

very ‘unhappy’ water

‘unhappy’ water

bulk-like water

‘happy’ water

Vacuum bubble

Bulk solvent

DGWaterMap coded:

Factor Xa

S1

S4

Non-Confidential20

A New Structure-Based Perspective on Druggability– 3D GRID physicochemical + Water energetics

GRID (Molecular Discovery) used to identify binding site complementary

properties – energetic analysis of binding site with ligand functional groups:

focus on hotspots for lipophilic probe (C1=) + H-bonding (H2O probe)

- new combined hydrophobic (DRY) and lipophilic (C1=) probe : CRY

WaterMap (Schrödinger) & SZMAP (Open Eye) used to generate a full

network of waters in binding site with free energy estimation (vs bulk solvent –

neutral atom) including a breakdown into entropic & enthalpic contributions

Combined analysis enables a new druggability assessment:

- fragment/ligand potency, properties, shape requirements…

Non-Confidential21

Waters that are calculated to have a significant positive free

energy (e.g. relative to being in bulk solvent) are termed „unhappy‟.

- There should be a particularly good free energy gain from

displacing these waters; they are only in the site as creating a

vacuum is even more energetically unfavourable.

- The number and the relative position of the predicted „unhappy‟

water clusters reveal hotspots for small molecule ligand

binding

A New Structure-Based Perspective on Druggability– 3D GRID physicochemical + Water energetics

Non-Confidential22

Can we generate a water network in a protein-ligand complex similar

to that experimentally determined in high resolution X-ray structures ?

- e.g. A2A at 1.8Å (4EIY)

Water Networks: Validation

Excellent correlation

+ we also know the relative energies

of the waters, and can re-evaluate

with different ligands

- a significant advance

Can we now explain previously

unexplained SAR (in terms of direct

ligand-protein interactions) etc

Non-Confidential23

Binding Site Analysis for Druggability

Druggability – ligandability with properties of an oral drug

Use a combined analysis of „unhappy‟ waters & binding site

preference (lipophilic/hydrophobic)

Analyse numbers, connectivity & distribution of „unhappy‟ waters „Unhappy‟ water = >2.5 kcal vs bulk solvent (vacuum usually worse)

The link with protein active site druggability is not only to the total number of

„unhappy‟ waters in each binding pocket but also to their arrangement and

proximity (connectivity) to other „unhappy‟ waters.

-Two representative protease enzyme

targets factor Xa and BACE1 have key

„unhappy‟ waters displaced by the ligand

that are not connected

- extreme case in factor Xa where they are

in subpockets almost 10 Å apart, giving a

lower value of 0–1 connections;

- In GPCRs such as A2A the predicted

„unhappy‟ waters have a favourable

more globular arrangement with an

average 2-3 other adjacent „unhappy‟

waters at < 3 Å

Non-Confidential24

β1- (from StaR) & β2- (from T4L insertion) Adrenergic Receptors

β1 antag

β2 antag

β1 agonist

β2 agonist

Inactive Active

Non-Confidential25

Druggable regions with clusters of „unhappy‟ waters (WaterMap) with GRID showing concurrent

lipophilic & H-bond hotspots

Dopamine D3 Histamine H1Muscarinic M2

Druggability : Dopamine, Histamine & Muscarinic GPCRs

New insights from structural biology into the druggability of G protein-coupled receptors. Mason, Bortolato, Congreve, Marshall. Trends Pharmacol Sci. 2012;33(5):249-60.

OH

O

O

N+

H

Non-Confidential26

What about more recent structures?

S1P1 Lipid GPCR Opioid kappa Receptor

NHO

N+

P

O-

O

O-

H

HH

OH

N+

NH

O NH

H

OH

Non-Confidential27

Kinases are more like GPCRs for druggability in terms of regions of connected „unhappy‟ waters

c-Abl DFG-in c-Abl DFG-out

New insights from structural biology into the druggability of G protein-coupled receptors. Mason, Bortolato, Congreve, Marshall. Trends Pharmacol Sci. 2012;33(5):249-60.

Non-Confidential28

These sparsely distributed ‘unhappy’ waters are distributed in different subpockets, meaning that fairly ‘angular’ ligands are needed, with a requirement for a precise shape and conformation; this could explain why random screening (HTS) often fails. ranked lower in overall druggability

Less druggable enzyme targets do not have large clusters

of „unhappy‟ waters

The myth:Basic S1 for serine

proteases (factor Xa)

The structure that broke the myth

The clinical candidate

Non-Confidential29

Less Druggable Sites Still Tractable to SBDD

GPCR Compared to Protease

CXCR4 has a more challenging site:

Structure shows the “hot-spot” for binding to be

less deep / druggable (lipophilic, less buried

ionic interaction)

BACE has delocalised druggable site

– hot-spots linked by SBDD

New insights from structural biology into the druggability of G protein-coupled receptors. Mason, Bortolato, Congreve, Marshall. Trends Pharmacol Sci. 2012;33(5):249-60.

Non-Confidential30

Conserved mechanism suggests orthosteric agonists

should be attainable for any GPCR

Inactive Active

Druggable A2A Antagonist site Druggable A2A Agonist site

Non-Confidential

First GPCR Candidate Wholly Derived from SBDD

Superior adenosine A2A antagonists

Entirely novel chemotypes

Candidate licensed to Shire

Treatment of multiple neuro disorders

Radical binding mode with highly

optimised receptor interactions

Features– Non-furan, non-xanthine

– Very low molecular weight

– Relatively polar

Benefits– Attractive safety profile

– Improved oral bioavailability and PK

– Excellent in vivo efficacy

Candidate series (blue) binds very efficiently to receptor

Langmead, C. et al. (2012) J. Med. Chem. Mar 8;55(5):1904-9Congreve, M. et al. (2012) J. Med. Chem. Mar 8;55(5):1898-903

Hal

operid

ol

Istrad

efyl

line

Pre

laden

ant

HTL

0

20

40

60

80

1001h post-dose

2h post-dose

Effect of istradefylline, preladenant or HTL(1 mg/kg, PO) on haloperidol-induced catalepsy in rats

% 0

.8 m

g/k

g h

alo

peri

do

l re

sp

on

se

31

Non-Confidential32

Using GRID hotspots enabled the first full GPCR SBDD

to give a clinical candidate for the Adenosine A2a

A2A antag

ZM24138

New insights from structural biology into the druggability of G protein-coupled receptors. Mason, Bortolato, Congreve, Marshall. Trends Pharmacol Sci. 2012;33(5):249-60.

The highly ligand efficient designed structures displaces a cluster

of unhappy waters deep in the pocket, missed by previous ZM-like

ligands (from HTS etc)

Non-Confidential33

Biophysical MappingTM uses StaRs to map the binding

sites of GPCRs & conf

10-30 Mutations to theBinding site region

Mutant StaRs screened on Biacore chips

Detection of binding of different ligands to each

mutant StaR

Biophysical Map

of binding site

Ligand refined homology model and prediction of protein-ligand binding modes

Correlating binding data from multiple ligands with multiple

StaR proteins

Zhukov, A. et al., J. Med. Chem. 2011, 54, 4312.

Site directed mutagenesis

on StaR®

Non-Confidential

Experimentally Enhanced Homology Models

Biophysical

Mapping

Existing structures

Virtual screeningFragment screening

Further X-ray

structures

Knowledge of conformations

Reported variants

StaR mutagenesisFirst

homology

model

34

Multiple generations of

Experimentally Enhanced

Homology Models

Non-Confidential35

Structure-Based Lead Optimisation

BP

- Structure can enable small ligand efficient

changes to modulate selectivity & potency

• Models of A2A, refined using the biophysical mapping, & of A1 used -

dockings prioritized from large virtual libraries (1,2,4-triazines)

– Used GRID hotspots to design compounds that efficiently displaced the

“unhappy “ waters deep in the site

– Used GRID surfaces of A2 vs A1 to probe for subltle differences to efficiently

design improved selectivity

Non-Confidential36

Waters & GPCR SBDD / Druggability

• New perspective on druggability possible by analysis of binding site using water free energies & 3D physicochemical properties (GRID)

• Looking at pertubation of all waters, including those remaining, is looking promising

• Multiple approaches possible, with combined approaches often useful

- for apo structure generate water network with WaterMap or GRID- for complexes generate initial complete water network with SZMAP

& optimize with WaterMap- binding site preferences from GRID analysis with functional groups- scoring (displacement and perturbation) by all 3 methods:

(WaterMap, SZMAP, GRID/CRY probe)

Non-Confidential37

Heptares Therapeutics Ltd.Computational Chemistry

Protein Engineering

Structural Sciences

Pharmacology

Medicinal Chemistry

Management

MRC LMB, CambridgeRichard Henderson

Chris Tate

Guillaume Lebon

Tony Warne

Jessica Li

Jenny Miller

Paul Scherrer InstituteGebhard Schertler

U. of Leiden / ZoBioGregg Siegal

Francis Figaroa

Johan Hollander

Eiso AB

BiofocusChris Richardson

Acknowledgements

U. of Utah / Biosensor ToolsDavid Myszka

Rebecca Rich