future directions in drug design & discovery - mgms … · future directions in drug design...

Future Directions in Drug Future Directions in Drug Design & DiscoveryDesign & Discovery

[email protected]@[email protected]@[email protected]@email.com

Jonathan S. MasonJonathan S. MasonHead of Computational ChemistryHead of Computational Chemistry

HeptaresHeptares Therapeutics, Welwyn Garden City, UK &Therapeutics, Welwyn Garden City, UK &

Chief ScientistChief Scientist (Predictive Technologies & Drug Design) Medicinal Chemistry(Predictive Technologies & Drug Design) Medicinal Chemistry

Lundbeck Research, Lundbeck Research, ValbyValby, Copenhagen, Denmark, Copenhagen, Denmark

The menuThe menu……

The drug discovery problemsThe drug discovery problemsThe drug design problemsThe drug design problemsThe opportunitiesThe opportunities

Attrition / ProductivityAttrition / Productivity

The Drug Discovery ProblemThe Drug Discovery Problem

Need to Need to -- choose the right targetschoose the right targets

-- identify suitable hitsidentify suitable hits-- progress rapidly to a molecule with the progress rapidly to a molecule with the

desired activity and propertiesdesired activity and propertiesthat does not fail (that does not fail (attritattrit) during ) during development development

Attrition / ProductivityAttrition / Productivity –– Issues Issues OpportunitiesOpportunities

The Drug Discovery ProblemThe Drug Discovery Problem

Toxicity Toxicity –– Safety IssuesSafety Issues-- large 5 year EU funded project large 5 year EU funded project

(IMI (IMI eToxeTox) to develop models based on ) to develop models based on pooled data from all major pooled data from all major pharmapharmacompanies companies (4 week rat)(4 week rat)

Drug DiscoveryDrug Discovery

NCELeadOptimization

Hit LeadIdentificationGenomics Target

IdentificationTarget

Validation

Phase I & IIPhase I & IIPhase I & II Phase IIIPhase IIIPhase III

IdeaIdeaIdea DrugDrugDrug

Drug/Biological Target Space

CompoundIdentification

TargetIdentification

TargetValidation

Target equityTarget equity

Chemical equityChemical equity

LeadSelectivity

Lead Differentiation

Lead equityLead equity

Risk managementRisk management

Design, make & screen compounds that are Design, make & screen compounds that are ““drugdrug--likelike”” & & ““leadlead--likelike””–– and have biological activity !and have biological activity !

Tackle Tackle attrition attrition && productivity at an early stage productivity at an early stage 100 Ideas 100 Ideas --------------------------1010------------------------ 11 NCENCE

8080 Ideas Ideas --------------------------1010------------------------ 22 NCENCE

Medicinal Chemistry / Drug DesignMedicinal Chemistry / Drug Design

Fragments Fragments leads for difficult targetsleads for difficult targets



Number 1:Number 1:Drive design with experimental data!Drive design with experimental data!Synergise, not compete..Synergise, not compete..

Biophysical Biophysical ScreeningScreening

++SiteSite--directeddirectedMutagenesisMutagenesis

BPMBPM

FragmentFragmentBiophysical Biophysical ScreeningScreening

++De novoDe novoSBDDSBDD

OffOff--target target screeningscreening

++In In silicosilico

Prediction ofPrediction ofoffoff--targettarget

profilesprofiles

Future trends: The opportunitiesFuture trends: The opportunities……

DrugabilityDrugabilityAssessmentAssessmentnew targetsnew targets

In In silicosilico++

Fragments etcFragments etc

Number 2:Number 2:Continue to think as much about Continue to think as much about properties as properties as

potency (physicochemical, LE, LLE etc)potency (physicochemical, LE, LLE etc)MultiMulti--parametric optimisationparametric optimisation

But nowBut now with kinetics with kinetics (off(off--rates etc)rates etc) from an from an early stage early stage –– from biophysical screening from biophysical screening (Surface Plasmon (Surface Plasmon Resonance(SPR)/BiacoreResonance(SPR)/Biacore etc)etc)



BPMBPM




Number 3:Number 3:Apply Apply ““rational designrational design””, SBDD to the major , SBDD to the major drug target class drug target class GPCRsGPCRsStabilise the GPCR to the desired conformation Stabilise the GPCR to the desired conformation (agonist, antagonist etc)(agonist, antagonist etc)Finally gain understanding at the atomic level of Finally gain understanding at the atomic level of antagonismantagonism--agonismagonism & use that in design& use that in designSubSub--type selectivity type selectivity SubSub--state selectivitystate selectivity

Fragment Fragment screeningscreening

for mono or polyfor mono or poly--pharmacologypharmacology

Biophysical Biophysical mapping mapping to to

determine binding determine binding modes , optimise modes , optimise

modelsmodels

Biophysical Biophysical screening screening

for kinetics for kinetics –– off ratesoff rates

XX--ray ray structures structures with with ligandsligands


Number 4:Number 4:Drive dataDrive data--driven design driven design in in cerebrocerebroAid intuition, experience, knowledge with Aid intuition, experience, knowledge with target derived information target derived information ((egeg hotspots for hotspots for functional groups, unfavourable waters etc)..functional groups, unfavourable waters etc)..

GRID GRID energetic energetic survey of survey of

binding sitebinding site

BindingBinding--site site water water

energeticsenergetics(GRID, (GRID,

WatermapWatermap……))

Using 3D stereo!Using 3D stereo!Now possible with NO Now possible with NO

loss of quality or loss of quality or interferenceinterference

(PLANAR)(PLANAR)


Number 5:Number 5:New energy and datasets to model toxicityNew energy and datasets to model toxicityIMI IMI eToxeTox project with input from many key project with input from many key players and data pooled from all major players and data pooled from all major PharmaPharmawith European site.with European site.

Hopefully models based on more than chemical Hopefully models based on more than chemical substructures substructures ……


Number 6:Number 6:Think about structures based on how proteins Think about structures based on how proteins see them, not how we synthesise them !see them, not how we synthesise them !2D 2D 3D 3D Biological profile/fingerprintBiological profile/fingerprint





profilesprofiles

Number 7:Number 7:

SimulationSimulationGet back to using molecular dynamics etc,Get back to using molecular dynamics etc,

-- bothboth the lock and the key are flexible & solvated!the lock and the key are flexible & solvated!

ModelModel RefineRefine Predict freePredict free--energy energy of bindingof binding


Number 8:Number 8:Integration of data Integration of data –– now plenty available!now plenty available!Integration of methods, use to solve what the Integration of methods, use to solve what the real problem/bottleneck is, not restricted to real problem/bottleneck is, not restricted to ““traditionaltraditional”” software & methodssoftware & methods

ChemoinformaticsChemoinformaticsBioinformaticsBioinformatics

Chemical BiologyChemical BiologySystems Biology/ChemistrySystems Biology/Chemistry

Structural BiologyStructural BiologyBiophysical ScreeningBiophysical Screening

Bioassay data for activity, Bioassay data for activity, ADME, ADME, ToxicicityToxicicity

External databasesExternal databases


““Computational chemistryComputational chemistry””””Computational Medicinal Chemistry Computational Medicinal Chemistry ComputerComputer--Aided Drug Design/Discovery (CADD)Aided Drug Design/Discovery (CADD)

Number 9:Number 9:

PharmacophorePharmacophore--based concepts:based concepts:-- now for both proteins & now for both proteins & ligandsligands-- GRID energetic analysis of binding sites with GRID energetic analysis of binding sites with

functional groups present in drug moleculesfunctional groups present in drug moleculesVirtual ScreeningVirtual Screening-- more structuremore structure--based but based but ligandligand--based with based with relevant descriptors still useful for hit/tool relevant descriptors still useful for hit/tool findingfinding

Physicochemical properties (Physicochemical properties (logPlogP……))

Future trends:Future trends: Still GoodStill Good……

GRID mapsGRID maps--The real onesThe real ones……

PharmacophoresPharmacophores from from LigandsLigands & Proteins& ProteinsFLAPFLAP(new(new method from Mol. Discovery / U. Perugia)method from Mol. Discovery / U. Perugia)a)a) Molecular Interaction Fields (MIF) calculated in the active siteMolecular Interaction Fields (MIF) calculated in the active site of a of a

protein structure using GRIDprotein structure using GRIDb)b) MIF is condensed into a few TargetMIF is condensed into a few Target--based based pharmacophoricpharmacophoric points. points. c)c) All possible arrangements of 4 All possible arrangements of 4 pharmacophoricpharmacophoric points are generatedpoints are generated

StericSteric hindrance as a hindrance as a filter for the many filter for the many solutions found for solutions found for each each ligandligand when when ““dockeddocked”” in the in the protein active site.protein active site.

A A moleculemolecule/fragment /fragment willwill bebe posedposed//fittedfittedusingusing meaningfulmeaningfulcontactscontacts ……((pharmacophoricpharmacophoric) b) b

An early example of fragment An early example of fragment screening screening better leadsbetter leads

Factor Factor XaXa serine protease serine protease –– the transformation binding mode the transformation binding mode ““flipflip””

NH2 N H

NN

O

S

O

O

S C lS

O

O

S

C l

N H2

N H

N

N

O

π-cationinteraction

Displaces an energetically “unhappy” water in a lipophilic hotspot

Hydrophobic / lipophilicinteractions

Cation-anion intertaction withCatalytic aspartate

--

A great fragment, that could have been A great fragment, that could have been foundfound……..

An early example of fragment An early example of fragment screening screening better leadsbetter leads

GRID maps show GRID maps show lipophiliclipophilic hotspot in S1hotspot in S1-- needed to ignore dogma, forceneeded to ignore dogma, force--fittingfitting

-- Through dogma of S1 needing a basic group did not screen widely Through dogma of S1 needing a basic group did not screen widely or follow up on or follow up on in in silicosilico reversed binding and hotspotsreversed binding and hotspots

PolypharmacologyPolypharmacology / promiscuous behaviour is one of the / promiscuous behaviour is one of the many issues that is more probable with many issues that is more probable with clogPclogP > 3> 3

The Protein PerspectiveThe Protein Perspective: : PolypharmacologyPolypharmacology && ““Off TargetOff Target”” EffectsEffects

Another big challenge:Increasing Potency by

Adding Grease correlates with Increased Clearance

1

10

100

1000

10000

-1 0 1 2 3 4 5 6Log D7.4

ml/

min

/kg

….& promiscuity, hERG, phospholipidosis, PPB, P450,insolubility, metabolic,exposure (Vd)…etc

clogP…

Rod McKenzie, Leader Summit, Rod McKenzie, Leader Summit, MontreuxMontreux, June 2008, June 2008




BPMBPM






profilesprofiles


Weak binding

Strong binding

Fragments: Why small is beautifulFragments: Why small is beautiful

““FragmentsFragments”” or or ““ComponentsComponents”” of a drug molecule are reduced of a drug molecule are reduced complexity starting points complexity starting points --Enable a much larger proportion / diversity of relevant drug spaEnable a much larger proportion / diversity of relevant drug space ce to be exploredto be explored::

-- new targets, new indications (new targets, new indications (egeg CNS) without screening file biasCNS) without screening file bias

Fragments: Reduced complexity screening Fragments: Reduced complexity screening

-- Good highGood high--LE starting points, even though existing within compoundsLE starting points, even though existing within compoundsin the screening file are often missed in the screening file are often missed ““dressed updressed up”” wrongly wrongly (( greatergreater chances for chances for HH--bondbond mismatchmismatch oror stericsteric clashclash etc.etc.))

LowerLower hithit--raterate for for HTSHTS--sizedsized cpdscpds, , highhigh--LELE fragments fragments rarelyrarely show show upup in hits.in hits.

ReducedReduced ligandligand complexitycomplexity increasesincreases thethechances chances ofof a match but binding a match but binding willwill bebe lowlowFragment screening delivers Fragment screening delivers highhigh effectiveeffectivechemicalchemical diversitydiversity from small from small librarieslibraries

Some of the questions to considerSome of the questions to consider……

Can we find Can we find ““betterbetter”” leads ? leads ? –– OptimisableOptimisable (non(non--flat SAR) flat SAR) -- Better properties, high Better properties, high ligandligand efficiency (LE), efficiency (LE),

& & ligandligand lipophiliclipophilic efficiencefficienc (LLE: (LLE: --logKilogKi –– clogPclogP or or clogDclogD))-- AllostericAllosteric binding sitesbinding sites……

Can we finding a hit/lead when HTS fails ? Can we finding a hit/lead when HTS fails ? –– Sampling of drug relevant chemical spaceSampling of drug relevant chemical space-- SensitiveSensitive screening method (screening method (llabelabel--free: biophysical)free: biophysical)

What do we need to be successful ?What do we need to be successful ?–– LearningsLearnings from the pastfrom the past--New methods for membrane proteins New methods for membrane proteins –– stabilization of stabilization of conformation(sconformation(s) of interest ) of interest biophysical screening, kinetics & biophysical screening, kinetics & XX--ray structuresray structures

Can we use on the major drug class of Can we use on the major drug class of GPCRsGPCRs ??–– Better leads Better leads (as above)(as above)-- Control Control polypharmacologypolypharmacology

A recent example of fragment screening A recent example of fragment screening better leads: BACE better leads: BACE aspartateaspartate proteaseprotease

Poor/no HTS hits Poor/no HTS hits (many companies...)(many companies...)HydroxyethylamineHydroxyethylamine (HEA) compounds difficult to (HEA) compounds difficult to

optimise to clean brain optimise to clean brain penetrantpenetrant compounds compounds (many companies)(many companies)

Fragment screening by many different biophysical Fragment screening by many different biophysical methods able to find diverse new different / reduced methods able to find diverse new different / reduced basicitybasicity ““warheadswarheads””

-- XX--ray cocktail soaking, SPR, NMR, TINSray cocktail soaking, SPR, NMR, TINS

ElanElan leadleadFor BACEFor BACE

Fragment screenFragment screenSBDDSBDD

AZ LeadAZ Lead

Poor DrugPoor Drug--Like PropertiesLike Properties Lipinski Ro5 CompliantLipinski Ro5 Compliant

N

N

CH3

OCH3

NH2

CH3

O

BiophysicalBiophysical screening platforms (screening platforms (e.ge.g. . XX--rayray, SPR, TINS) , SPR, TINS) usedused to to identifyidentify & & facilitatefacilitate evolution evolution ofof weakweak mMmM fragments to fragments to nMnM leadsleads

Fragments: Are all the screening Fragments: Are all the screening libraries similar ? libraries similar ?

Analysis of a partially built inAnalysis of a partially built in--house house ““handhand--pickedpicked””fragment library and the fragments from 3 companies fragment library and the fragments from 3 companies offering fragment screening gave surprising results:offering fragment screening gave surprising results:

-- Practically no overlap at the compound level between any Practically no overlap at the compound level between any of the commercial vendor librariesof the commercial vendor libraries

Different hits will be obtained by fragment screening at multipDifferent hits will be obtained by fragment screening at multiple le vendors (as well as any differences from different methods)vendors (as well as any differences from different methods)

-- Overlap at the compound level between inOverlap at the compound level between in--house library house library and all vendor librariesand all vendor libraries

-- All 3 vendor libraries contained significant numbers of All 3 vendor libraries contained significant numbers of medchemmedchem desirable/acceptable hitsdesirable/acceptable hits

Number 2:Number 2:Continue to think as much about Continue to think as much about properties as properties as

potency (physicochemical, LE, LLE etc)potency (physicochemical, LE, LLE etc)

But nowBut now with kinetics with kinetics (off(off--rates etc)rates etc) from an from an early stage early stage –– from biophysical screening from biophysical screening (Surface Plasmon (Surface Plasmon Resonance(SPR)/BiacoreResonance(SPR)/Biacore etc)etc)



BPMBPM




Kinetics of binding is an important factor for the Kinetics of binding is an important factor for the in in vivovivo efficacy of many drugsefficacy of many drugs-- Methods already set up for fragment screening & optimization, Methods already set up for fragment screening & optimization,

such as immobilised protein with SPR screening (such as immobilised protein with SPR screening (BiaCoreBiaCore) can be ) can be directly used to measure on and off rates during optimizationdirectly used to measure on and off rates during optimization

Better Leads (from Fragments) ? Better Leads (from Fragments) ?

Better Leads from Fragments ? Better Leads from Fragments ?

Build up a molecule that has multiple properties optimised Build up a molecule that has multiple properties optimised for the desired for the desired target(starget(s):):

-- Kinetics Kinetics [require method & suitable protein, [require method & suitable protein, egeg SPR/SPR/BiacoreBiacore]]

-- Selectivity / Selectivity / PolypharmacologyPolypharmacology

-- LigandLigand efficiency, properties efficiency, properties [[egeg for CNS for for CNS for ““difficultdifficult”” targets]targets]

To identify, characterize and optimize the fragment binding To identify, characterize and optimize the fragment binding a purified protein sufficiently stable for immobilization / a purified protein sufficiently stable for immobilization / screening is neededscreening is needed-- Ok in general for enzymes Ok in general for enzymes -- Previously very difficult for membrane bound proteins Previously very difficult for membrane bound proteins

such as such as GPCRsGPCRs: now possible (: now possible (StaRStaR™™: : Stabilized Receptors)Stabilized Receptors)

Number 3:Number 3:Apply Apply ““rational designrational design””, SBDD to the major , SBDD to the major drug target class drug target class GPCRsGPCRsStabilise the GPCR to the desired Stabilise the GPCR to the desired conformation (agonist, antagonist etc)conformation (agonist, antagonist etc)Finally gain understanding at the atomic level Finally gain understanding at the atomic level of antagonismof antagonism--agonismagonism & use that in design& use that in design

Fragment Fragment screeningscreeningfor mono or for mono or

polypoly--pharmacologypharmacology

Biophysical Biophysical mapping mapping to to determine determine

binding modes , binding modes , optimise modelsoptimise models

Biophysical Biophysical screening screening

for for kinetics kinetics ––off ratesoff rates

XX--ray ray structures structures

with with ligandsligands


Use of new stabilized receptors (Use of new stabilized receptors (StaRsStaRs) ) technology with technology with GPCRsGPCRs for biophysical mapping for biophysical mapping & X& X--ray structures with ray structures with ligandsligands

full SBDD full SBDD (Structure(Structure--Based Drug Design)Based Drug Design)


Heptares Therapeutics

GPCR Drug Discovery CompanyGPCR Drug Discovery CompanyIntegrated GPCR drug discovery capabilityIntegrated GPCR drug discovery capabilityUnique stabilised receptor (Unique stabilised receptor (StaRStaR™™) technology and strong IP ) technology and strong IP Cross TherapeuticCross Therapeutic

Breakthrough stabilised receptor Breakthrough stabilised receptor StaRStaRTMTM technologytechnologyAddressing deficiencies in GPCR drug pipelines caused by poorly Addressing deficiencies in GPCR drug pipelines caused by poorly tractable GPCR tractable GPCR targetstargetsEnables FULL suite of contemporary drug discovery technologies tEnables FULL suite of contemporary drug discovery technologies to be applied to o be applied to GPCRsGPCRs

StaRStaRTMTM technology is being used to progress a pipeline of best or firstechnology is being used to progress a pipeline of best or first t in class molecules across the GPCR in class molecules across the GPCR superfamilysuperfamily

Small molecule and antibodies Small molecule and antibodies –– twintwin--track approachtrack approachAim to progress promising drug leads internally and through straAim to progress promising drug leads internally and through strategic collaborationstegic collaborations

WellWell--funded through funded through ££21M Series A fund raise completed Feb 200921M Series A fund raise completed Feb 200940 employees located in 40 employees located in BioparkBiopark, Hertfordshire UK, Hertfordshire UK

Receptors embedded in cell membrane exist in multiple Receptors embedded in cell membrane exist in multiple conformations conformations

Highly unstable when removedHighly unstable when removedNot suitable for structure based drug discovery methodsNot suitable for structure based drug discovery methods

HeptaresHeptares’’ technology is used to make a stabilized technology is used to make a stabilized versions of target versions of target GPCRsGPCRs ('('StaRStaRTMTM') held in a specific ') held in a specific chosen conformationchosen conformation

Stable in functionallyStable in functionally--relevant, purified formrelevant, purified form

Bindingassay

FunctionalAssay

AR AR* AR*G

R R* R*G

Heptares StaRTM Technology

Heptares StaRTM Technology

●● Receptor embedded in cell membrane, highly unstable when Receptor embedded in cell membrane, highly unstable when removedremoved•• Aggregates and loses function when purified in detergentAggregates and loses function when purified in detergent•• Current drug discovery approaches rely on cellCurrent drug discovery approaches rely on cell--based assaysbased assays

●● General method required to engineer stabilized, less flexible General method required to engineer stabilized, less flexible receptor held in specified functional conformationreceptor held in specified functional conformation

●● HeptaresHeptares’’ proprietary technology is used to make a stabilized proprietary technology is used to make a stabilized version of target GPCR ('version of target GPCR ('StaRStaRTMTM') held in a chosen conformation') held in a chosen conformation•• Stable in functionallyStable in functionally--relevant, purified formrelevant, purified form•• Dependent on Dependent on ligandligand usedused

RR RRnn R*R*InactiveInactive Partially Active Partially Active Fully ActiveFully Active

•• A GPCR containing a small number of point mutations A GPCR containing a small number of point mutations that greatly improve its that greatly improve its thermostabilitythermostability

-- Stable in purified, detergent solubilised formStable in purified, detergent solubilised form-- Functional and drugFunctional and drug--binding characteristics preservedbinding characteristics preserved-- Completely novel and proprietaryCompletely novel and proprietary-- Suitable for Suitable for uHTSuHTS, , BiacoreBiacore (kinetics), crystallisation etc.(kinetics), crystallisation etc.-- Transferrable across GPCR familiesTransferrable across GPCR families

0 10 20 30 40 50 60 70

0

20

40

60

80

100

120

A2A-WT

A2A-Rant22

A2A-SS3

Temperature oC

% s

pec

ific

[3H

] Z

M24

1385

bo

un

d

What is a StaRTM

Types of Types of StaRsStaRs

Antagonist Antagonist StaRStaR

Agonist state 1Agonist state 1StaRStaR

NAM NAM StaRStaRPAM PAM StaRStaR

Agonist state 2Agonist state 2StaRStaR

Inverse Agonist Inverse Agonist StaRStaR

StaRStaR proteins are locked in the conformation derived from the proteins are locked in the conformation derived from the pharmacology of the pharmacology of the ligandligand used in their creationused in their creation

Proprietary Process for Creating StaRs to stabilise GPCRs Fragment screening Kinetics,

Biophysical mapping, X-ray structures etc

UnstableNative receptor

SelectConformation

SelectLigand

Purifyprotein

CrystalliseNewGPCR structure

SPR/BiacoreTINS/Zobio...

Fragment screeningKinetics

Thermostabilityand Selection

AATCAGCTTGTCGAA

Mutagenesis

Iteration

StaRRecombination

of mutants

StaRsAg/Antag

Conformations

5 10 15 20 25 30 35 40 45 500

25

50

75

100

Temperature

Enabling technology for GPCR Drug Discovery

Cell Based AssaysHigh Throughput Screening

RecombinantReceptorMembraneAssays

In vitroPharmacologySelectivity

In vivoPharmacology Efficacy andReceptor Occupancy

SPR KineticsandThermodynamics

Modelling bySDM withRadioligand

Modelling byBiophysicalMappingTM

Fragment ScreeningSPR / NMR direct binding

In vitroPharmacologyIsolated ReceptorConformations

TherapeuticAntibodiesTarget Validation

Protein-LigandComplexes

BetaBeta--1 1 AdrenoceptorAdrenoceptor StaRStaRTM Crystal Crystal StructureStructure

Warne et al, Nature July 24th 2008

Entrance to ligand binding site well defined – high resolution

Drug binding pocket

Activation and G-protein binding region retainedMultiple loop conformations resolved cf biased agonism

9 drug co-crystal structures now solved in detergentAgonists and AntagonistsLow and High Affinity

R68S

M90V

F338M

F327A

A282L

Y227A

Biophysical Screening on GPCRs

StaRsStaRs broadly applicable to biophysical approachesbroadly applicable to biophysical approaches•• StabilityStability•• Protein productionProtein production

●● Investigating multiple methodsInvestigating multiple methods•• SPR (SPR (BiacoreBiacore))•• NMR screening methods (TINS)NMR screening methods (TINS)•• Thermal Thermal denaturationdenaturation approachesapproaches

●● GPCR targeted fragment libraryGPCR targeted fragment library•• In In silicosilico for virtual screeningfor virtual screening•• In vitro In vitro for diversity screeningfor diversity screening

Common Drug Binding site in all Common Drug Binding site in all GPCRsGPCRs

Family AFamily Aamine, nucleotide,amine, nucleotide,Lipid, Lipid, eicosanoideicosanoid

Family A/BFamily A/BPeptidePeptide

ReceptorsReceptors

Family CFamily CMetabotropicMetabotropic glutamateglutamate

Drug Binding Site located in Drug Binding Site located in transmembranetransmembrane domaindomain

Considered Considered ‘‘allostericallosteric sitesite’’ for Family B and Cfor Family B and C

Family A Family A allostericallosteric site overlaps with site overlaps with ligandligand binding pocketbinding pocket

LigandLigand




BPMBPM






profilesprofiles


Biophysical Mapping using Biophysical Mapping using BiacoreBiacore

Site directed mutagenesisSite directed mutagenesis 1010--30 Mutations to the30 Mutations to theBinding site regionBinding site region

Mutant Mutant StaRsStaRs displayed displayed on a on a BiacoreBiacore chipchip

Detection of binding Detection of binding of different of different ligandsligands to to each mutant each mutant StaRStaR

Biophysical MapBiophysical Map

of binding siteof binding site

LigandLigand refined refined Homology Model and Homology Model and prediction of proteinprediction of protein--ligandligand binding modesbinding modes

Correlating binding data from Correlating binding data from Multiple Multiple ligandsligands with multiplewith multipleMutant Mutant StaRStaR proteinsproteins Label freeLabel free

Direct binding methodDirect binding method

Biophysical Biophysical MappingMappingTM: Definition : Definition of binding modes of binding modes

Matrix of Matrix of ligandligand--construct binding construct binding

datadata

DataDatainterpretation interpretation and modellingand modelling

Biophysical maps for each Biophysical maps for each chemical serieschemical series

Decide between Decide between alternative docked alternative docked

posesposes

FragmentFragment--based drug discovery/design (FBDD) based drug discovery/design (FBDD) for for membrane proteins: membrane proteins: GPCRsGPCRs

Fragment screening has been performed using Fragment screening has been performed using stabilized stabilized GPCRsGPCRs, giving results comparable to that , giving results comparable to that obtained using soluble (enzyme) targetsobtained using soluble (enzyme) targets

The stabilized GPCR can be immobilized and used The stabilized GPCR can be immobilized and used for fragment screening using:for fragment screening using:-- BiacoreBiacore /SPR: /SPR: Surface Plasma Resonance BiosensorSurface Plasma Resonance Biosensor-- TINS (TINS (ZobioZobio): ): Target Immobilized NMR ScreeningTarget Immobilized NMR Screening

Fragment Screening: Fragment Screening: The new possibilities for enzymes & The new possibilities for enzymes & GPCRsGPCRs

GPCRsGPCRs

Select Select conformationconformation

StabilizeStabilize

StaRStaR™™

StaRStaR proteins are locked in the proteins are locked in the conformation derived from the conformation derived from the pharmacology of the pharmacology of the ligandligand used used

in their creationin their creation

PAM PAM NAMNAM

Biophysical mapping Biophysical mapping (SPR),(SPR), Competition Competition

studies studies (SPR & TINS) (SPR & TINS) & & XX--ray structuresray structures

Identify binding Identify binding position / modeposition / mode

EnzymesEnzymes

Immobilized protein Immobilized protein fragment screeningfragment screening

SPRSPRTINS (TINS (ZobioZobio))

TINS method for finding hits: TINS method for finding hits: fragment screening fragment screening

Immobilized protein Immobilized protein –– only small amounts needed (~1mg)only small amounts needed (~1mg)Very sensitive: higher Very sensitive: higher nMnM hits identified hits identified (not found by SPR)(not found by SPR)

TINS = Target Immobilized NMR Screening: Zobio

TINS method for finding hitsTINS method for finding hits

Fragment Screening: Fragment Screening: NNew possibilities for ew possibilities for GPCRsGPCRs (+(+ enzymes) enzymes)

GPCRsGPCRs egeg::ββ11--ARARAA2A2A

ProteaseProteasePhosphoPhospho--diesterasediesterase

TINS screening of TINS screening of ZobioZobiofragment library for 2 fragment library for 2 enzyme targets + enzyme targets + ββ11--AR AR GPCRGPCR ::

Sensible looking hits for Sensible looking hits for all targets all targets

8080--100 from ~1400100 from ~1400for enzyme targetsfor enzyme targets

~80 from 580 ~80 from 580 for for ββ11--ARAR

Specific for each targetSpecific for each target-- Only one fragment hit in Only one fragment hit in common between GPCR & common between GPCR & enzyme target hitsenzyme target hits

FBDD FBDD onon MembraneMembrane ProteinsProteins: GPCR(1): : GPCR(1): ββ1AR1AR

StaR™ technology used to generate thermostabile mutant of β1AR.‐ Stable in purified, detergent solubilised form

‐ Functional and drug‐binding characteristics preserved

‐ Completely novel and proprietary

Approach: TINS - Screen immobilized, DDM solubilized β1AR vs OmpA

TINS screening using stabilized TINS screening using stabilized ββ1AR was able to 1AR was able to identify ~80 hits from 580 fragments screened:identify ~80 hits from 580 fragments screened:-- reasonable looking structuresreasonable looking structures-- including compounds where activity could be confirmed including compounds where activity could be confirmed by biochemical screeningby biochemical screening

Are the GPCR Fragment Screening Hits from Are the GPCR Fragment Screening Hits from TINS (TINS (ZobioZobio) generally reasonable / valid ?) generally reasonable / valid ?

Yes !Yes !

Many reasonable / interesting hitsMany reasonable / interesting hits

Activity confirmed for many by biochemical assayActivity confirmed for many by biochemical assay

Not the same as found for the other targetsNot the same as found for the other targets

Further work ongoingFurther work ongoing

GPCR Fragment Screening ExamplesGPCR Fragment Screening Examples

●● ββ11-- AdrenoceptorAdrenoceptor by TINS NMRby TINS NMR•• ZoBioZoBio library (Gregg library (Gregg SiegalSiegal))•• TINS screening using stabilized TINS screening using stabilized ��1AR was able to identify ~80 hits 1AR was able to identify ~80 hits

from 580 fragments screenedfrom 580 fragments screened•• Promising chemical structuresPromising chemical structures•• Including compounds where activity could be confirmed by biochemIncluding compounds where activity could be confirmed by biochemical ical

screeningscreening●● Adenosine AAdenosine A2A2A by SPR/by SPR/BiacoreBiacore

•• University of Utah (David University of Utah (David MyszkaMyszka))•• XanthineXanthine derivatives identified as hitsderivatives identified as hits•• 200 200 μμMM screening concentrationscreening concentration

A2A Rant224 mutations

StaRStaR immobilised on chipimmobilised on chip Challenged with FragmentsChallenged with Fragments(~150(~150--250 250 DaDa))

Highly sensitive Highly sensitive detection detection -- low low affinity bindersaffinity binders

Fragments progressed Fragments progressed to structure modelto structure model

FragmentFragment--basedbased

Drug DiscoveryDrug Discovery

Fragments Fragments ‘‘growngrown’’ to to fill active site and fill active site and give potent novel leadsgive potent novel leads

O

N

NH

N

N NH2

N

N

N

NH

O

O

Fragment Screening using Biacore

SPR fragment screeningAnalysis of hits

Hits are further analysed byHits are further analysed byDetection of nonDetection of non--specific binding on control specific binding on control surface (surface (egeg denatured protein)denatured protein)Full concentration response curvesFull concentration response curvesBiophysical Biophysical mappingmappingTMTM

Analysis Analysis vsvs receptor with binding site mutationsreceptor with binding site mutationsCoCo--crystal structurescrystal structures

3D Structural Information on Industrial Timescale 3D Structural Information on Industrial Timescale HeptaresHeptares GPCR CrystallographyGPCR Crystallography

State of the art facility for GPCR crystallisation set upState of the art facility for GPCR crystallisation set upVapour diffusion crystallographyVapour diffusion crystallographyCoCo--crystallisation with multiple crystallisation with multiple ligandsligandsNanolitreNanolitre lipidiclipidic cupid phase roboticscupid phase roboticsSynchrotron sources at Diamond, ESRF, SLSSynchrotron sources at Diamond, ESRF, SLS

StaR Drug Discovery Applications

StaRsStaRsAg/Ag/AntagAntag

ConformationsConformations

SPR/SPR/BiacoreBiacore

Fragment screeningFragment screeningKineticsKinetics

LigandLigand coco--structuresstructuresBinding site definitionBinding site definition

XX--ray structureray structure

Mutagenesis dataMutagenesis dataBinding site mutantsBinding site mutants

Refined homologyRefined homologyModelModel

Virtual screeningVirtual screening

DockingDockingVirtual screeningVirtual screening

NMRNMR

Fragment screeningFragment screeningBinding site definitionBinding site definition

Residues involved in Residues involved in LigandLigand bindingbinding

Pharmacology Pharmacology vsvsBinding modesBinding modes

Compound mechanismCompound mechanismof actionof action

Ultra HTSUltra HTS

TINSTINS

Biophysical MappingBiophysical Mapping™™

Need to be careful about correlations…

Courtesy of Arthur Doweyko, BMS

And about biases in how we see data

Courtesy of Arthur Doweyko, BMS

Number 6:Number 6:Think about structures based on how proteins Think about structures based on how proteins see them, not how we synthesise them !see them, not how we synthesise them !2D 2D 3D 3D Biological profile/fingerprintBiological profile/fingerprint





profilesprofiles

Describing molecules:Describing molecules:The Protein View The Protein View

2D structure ?2D structure ?

3D structure ?3D structure ?XX

Better!Better!

Fingerprint of binding to 150 diverse targets?Fingerprint of binding to 150 diverse targets?

Better ?Better ?

O NH

S

Experimental biophysical characterization Experimental biophysical characterization (BPM, kinetics, X(BPM, kinetics, X--ray structure etc )ray structure etc )

Describing molecules:Describing molecules:The Protein View The Protein View

””BiologicalBiological fingerprintsfingerprints”” ? ? In VitroIn VitroProfileProfile

120120--150150 in vitroin vitropharmacological,pharmacological,

38 ADME(T) & 38 ADME(T) & pharmaceutical assayspharmaceutical assays

Gluccocorticoids

Benzodiazepenes

Estrogenics

MAO inhibitors

Opiates

AnticholinergicsBeta blockers

Antipsychotics, SSRIs,Tricyclics

etc.

NSAIDs

I15

I10

I04

E32

E12

E04 I1

3

R26

R91

R62

E09 I1

2

E25 I0

8

R55 I1

1

E18

E22

E31 I0

2

R16 I0

7

R82

R12

E14

E27 I0

5

I14

R24

E07

E11

R75

R29

R38

R47

R90 I0

1

R15

R01

R63

R89

R28

R51

R84

T05

T04

R17

R60

R22

R43

R19

R27

R39

R18

R21

R88

R44 I0

3

R13 I0

6

R78

R72

R14

R02

T02

Gluccocorticoids

Benzodiazepenes

Estrogenics

MAO inhibitors

Opiates

AnticholinergicsBeta blockers

Antipsychotics, SSRIs,Tricyclics

etc.

NSAIDs

I15

I10

I04

E32

E12

E04 I1

3

R26

R91

R62

E09 I1

2

E25 I0

8

R55 I1

1

E18

E22

E31 I0

2

R16 I0

7

R82

R12

E14

E27 I0

5

I14

R24

E07

E11

R75

R29

R38

R47

R90 I0

1

R15

R01

R63

R89

R28

R51

R84

T05

T04

R17

R60

R22

R43

R19

R27

R39

R18

R21

R88

R44 I0

3

R13 I0

6

R78

R72

R14

R02

T02

Predictive Predictive associationsassociations

In VivoIn VivoEffectEffect

CerepCerep BioPrintBioPrint®®

Experiences from Experiences from BioPrintBioPrint Broad Broad Pharmacological ProfilingPharmacological Profiling

TheseThese fragment fragment corescores areare in in potent hit potent hit compoundscompounds withwithundesirableundesirable offoff--targettargetactivitiesactivities thatthat couldcould not not beberemovedremoved

Cluster compounds in biological spaceCluster compounds in biological space XX

O

NH

Ar

Ar

O

NH

Ar

Ar

NH

O

Ar

Ar

N

O

Ar

Ar N

N HAr

Ar

N

NAr

Ar

2D2DRelatively Relatively selectiveselective

N

NH

Ar

ArN

NH

Ar

Ar

ThisThis fragment fragment corecore waswas in a in a ””cleanclean”” potent hit potent hit compoundcompoundwithoutwithout thethe undesirableundesirable offoff--targettarget activitiesactivities candidatecandidate

2D2D

CanCan bebe criticalcritical to to getget corecore (fragment) (fragment) startingstarting point rightpoint right

ExperiencesExperiences from from BioPrintBioPrintBroad Pharmacological ProfilingBroad Pharmacological Profiling

32 Submicromolar binding activities2 Submicromolar binding activities

+ 1 CYP

BioPrintBioPrint profiling:profiling:

extremely promiscuousextremely promiscuous

Het AromN

N OF

Het AromX X

X X

X X

X X

X X

NH

N

O

NH

N

ClogP 2ClogP 5IC50 = 4 nM, IC50 = 2 nM

VeryVery similarsimilar structuresstructures cancan have have veryvery differentdifferent polypharmacologypolypharmacology::

ExperiencesExperiences from from BioPrintBioPrintBroad Pharmacological ProfilingBroad Pharmacological Profiling

VeryVery differentdifferent polypharmacologypolypharmacology, , bothboth for for relatedrelated targetstargets and and broadlybroadly for for candidatescandidates for a 5HT for a 5HT targettarget::

(TOXIC)(TOXIC)

(TOXIC)(TOXIC)

(TOXIC)(TOXIC)

Correlation of toxic effect with BioPrintprofile was found for a CNS target

PDE target inhibitorsPDE target inhibitors

The prediction challengeThe prediction challenge

Potent hitsPotent hitsN

N H

Ar

Ar

N

N HAr

Ar

O

N H

Ar

Ar

NH

O

Ar

Ar

O

N

Ar

R

RefRef::

ClusterCluster usingusinga a circularcircularstructurestructure--basedbasedfingerprint ? fingerprint ? e.g. e.g. ScitegicScitegic FCFP6FCFP6

(not general)(not general)

Relatively Relatively selectiveselective

ClusterCluster usingusingin in vitrovitro biologicalbiologicalactivitesactivites, , diverse diverse targetstargetse.g. e.g. BioPrintBioPrint

cancan getget individualindividual models models for ~50%for ~50%

ClusterCluster usingusingstructuralstructuralfingerprints ? fingerprints ? e.g. e.g. DaylightDaylight

2D2D

O NH

S

In In SilicoSilico Prediction of Broad Profile for Prediction of Broad Profile for PolypharmacologyPolypharmacology ??

ChEMBLChEMBL + + datasets: datasets: SFPSFPneighbours neighbours approachapproach

<100nM <1μM <10μM

Clinical candidate

Reference:Duloxetine

Cerep BioPrint data

Others all died with off-target

activities

NNH

Ar

Ar

N

N HAr

Ar

1 6

4

11

6

BioPrintPredicted Correct BioPrintFalse positivesNew predictions

3 12

2

1

6


Predictions from ChEMBL dataset (7.2K targets, 0.6 million compounds, 2.4 million activities) + IUPAR +

For project compounds not yet viable to replace For project compounds not yet viable to replace experimental screening experimental screening –– too many false positives / negativestoo many false positives / negatives

Warning: Warning: ““SimilarSimilar”” compounds often do not have compounds often do not have similar offsimilar off--target activities!target activities!

<100nM <1μM <10μM

In In SilicoSilico Prediction of Broad Profile for Prediction of Broad Profile for PolypharmacologyPolypharmacology

Experimentally validated examples of predicting new Experimentally validated examples of predicting new targets for drugs targets for drugs (richer chemical space than for many new (richer chemical space than for many new project compounds)project compounds) but but ““bigger bigger picturepicture””maymay be missed:be missed:

Paxil (Paxil (paroxetineparoxetine):):••SEA Predicted beta adrenergic blocker SEA Predicted beta adrenergic blocker ––confirmed at 10 confirmed at 10 μμM on M on ββ11••Experiment (Experiment (BioPrintBioPrint): ):

–– 4 Active at 100nM4 Active at 100nM--11μμM M –– 9 Active at 19 Active at 1--5 5 μμM M

9

1 5 14

3

4 6

7


Good prediction of BioPrint assays, + some interesting predictions of other activities but false positivesProzac (Prozac (fluoxetinefluoxetine):):

••SEA Predicted beta adrenergic blocker SEA Predicted beta adrenergic blocker ––confirmed at 4.4confirmed at 4.4μμM on M on ββ11••Experiment (Experiment (BioPrintBioPrint): ):

––5 Active at 100nM5 Active at 100nM--11μμMM––4 Active at 14 Active at 1--5 5 μμM M –– 6 Active at 56 Active at 5--1010μμMM

1 5 18

3

1 3


1

Difficult to predict BioPrint assays, false positives + some interesting

predictions of other activitiesGood prediction

In In SilicoSilico Prediction of Broad Profile for Prediction of Broad Profile for PolypharmacologyPolypharmacology

Use of docking into XUse of docking into X--ray structures an exciting ray structures an exciting future future ““de novode novo”” approachapproach

--BUT from results seen so far a current NOBUT from results seen so far a current NO--GO!GO!

SummarySummarySummary

Fragments & SBDD Fragments & SBDD cancan provideprovide ””betterbetter”” startingstartingpoints for points for bothboth enzymeenzyme & GPCR & GPCR targetstargets((wherewhere binding is relatively optimal & properties (LE etc) good binding is relatively optimal & properties (LE etc) good vsvssubsub--optimal but more potent hits from HTS etc)optimal but more potent hits from HTS etc)

Analyse & Analyse & useuse all all thethe data to drive data to drive betterbetter drugdrugdiscoverydiscovery decisions:decisions:

-- PhysicochemicalPhysicochemical propertiesproperties etcetc-- Protein Protein structurestructure (SBDD) & profiling ((SBDD) & profiling (BioPrintBioPrint etcetc))-- But But dondon’’tt forgetforget in in cerebrocerebro ! ! AidAid creativitycreativity, intuition, , intuition, knowledgeknowledge withwith 3D. 3D. ThinkThink aboutabout relevancerelevance & & bewarebeware ofofbias/bias/overfittingoverfitting

FullFull ””rational designrational design”” (SBDD) (SBDD) nownow possiblepossible for major for major drug drug classclass ofof GPCRsGPCRs

FragmentsFragmentsProperties: physicochemical, LE, LLE etc Properties: physicochemical, LE, LLE etc -- kineticskineticsBiophysical screening / mappingBiophysical screening / mappingGPCR knowledge antagonists GPCR knowledge antagonists –– agonists etcagonists etcIn In cerebrocerebro -- with 3Dwith 3DToxicity predictionToxicity predictionDescribe structures in a biologically relevant wayDescribe structures in a biologically relevant way

Simulation (MD etc) Simulation (MD etc) FEBFEBIntegration of data and approachesIntegration of data and approaches –– no boundsno bounds

Summary: Future trends & opportunitiesSummary: Future trends & opportunities

AcknowledgementsAcknowledgementsAcknowledgements

Gregg Gregg SiegalSiegal, Francis , Francis FigaroaFigaroa, Johan , Johan HollanderHollander, , EisoEiso AB (U. AB (U. LeidenLeiden & & ZobioZobio))TINSTINS

David David MyszkaMyszka, Rebecca Rich , Rebecca Rich ((UniversityUniversity of Utah)of Utah)SPRSPR

FBDD / Enzymes FBDD / Enzymes Lena Lena TagmoseTagmose (Lundbeck)(Lundbeck)

BioPrintBioPrintBioPrintBioPrint teams teams atat CerepCerep and Pfizerand Pfizer

FBDD/SBDD FBDD/SBDD -- GPCRsGPCRsAll the team All the team atat HeptaresHeptares (Platform(Platform--DiscoveryDiscovery--Management)Management)LMB: Richard Henderson, LMB: Richard Henderson, GebhardGebhard SchertlerSchertler, Chris Tate, Tony Warne, Chris Tate, Tony Warne

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