Hit and Lead Profiling

519 Pages·2009·3.931 MB·English

by  Faller B., Urban L.

Hit and Lead Profiling
Edited by
Bernard Faller and Laszlo Urban
Methods and Principles in Medicinal Chemistry
Editedby R. Mannhold,H.Kubinyi, G.Folkers
EditorialBoard
H.Timmerman, J.Vacca, H.van de Waterbeemd, T.Wieland
Previous Volumes of this Series:
WolfgangJahnke, Daniel A.Erlanson EckhardOttow,HilmarWeinmann(Eds.)
Fragment-based Approaches Nuclear Receptors as Drug
in Drug Discovery Targets
Vol.34 Vol.39
2006,ISBN:978-3-527-31291-7 2008,ISBN:978-3-527-31872-8
Jörg Hüser(Ed.) Hanvan de Waterbeemd,
High-Throughput Screening BernardTesta (Eds.)
Drug Bioavailability
in Drug Discovery
EstimationofSolubility,Permeability,
Vol.35
AbsorptionandBioavailability
2006,ISBN:978-3-527-31283-2
2.,CompletelyRevisedEdition
Vol.40
KlausWanner,Georg Höfner (Eds.)
2008,ISBN:978-3-527-32051-6
MassSpectrometryinMedicinal
Chemistry
Roberto Todeschini, Viviana Consonni
ApplicationsinDrugDiscovery
Molecular Descriptors for
Vol.36
Chemoinformatics
2007,ISBN:978-3-527-31456-0
VolumeI:AlphabeticalListing
VolumeII:Appendices,References
Raimund Mannhold (Ed.)
Vol.41
Molecular Drug Properties
2009,ISBN:978-3-527-31852-0
MeasurementandPrediction
Vol.37
WolfgangSippl, Manfred Jung (Eds.)
2007,ISBN:978-3-527-31755-4
Epigenetic Targets in Drug
Discovery
Roy J.Vaz,Thomas Klabunde (Eds.)
Vol.42
Antitargets
2009,ISBN:978-3-527-32355-5
PredictionandPreventionofDrug
SideEffects
Vol.38
2008,ISBN:978-3-527-31821-6
Hit and Lead Profiling
Identification and Optimization
of Drug-like Molecules
Edited by
Bernard Faller and Laszlo Urban
SeriesEditors AllbookspublishedbyWiley-VCHarecarefully
produced.Nevertheless,authors,editors,and
Prof.Dr.RaimundMannhold publisherdonotwarranttheinformationcontained
MolecularDrugResearchGroup inthesebooks,includingthisbook,tobefreeof
Heinrich-Heine-Universität errors.Readersareadvisedtokeepinmindthat
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40225Düsseldorf otheritemsmayinadvertentlybeinaccurate.
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theDeutscheNationalbibliothek
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CollegiumHelveticum publicationintheDeutscheNationalbibliografie;
STW/ETHZurich detailed bibliographicdataareavailableonthe
8092Zurich Internetathttp://dnb.d-nb.de
Switzerland
[email protected] #2009WILEY-VCHVerlagGmbH&Co.KGaA,
Weinheim
VolumeEditors Allrightsreserved(includingthoseoftranslationinto
otherlanguages).Nopartofthisbookmaybe
Dr.BernardFaller reproducedinanyform–byphotoprinting,
NovartisInstitutesforBioMedicalResearch microfilm,oranyothermeans–nortransmittedor
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Dr.LaszloUrban
NovartisInstitutesforBioMedicalResearchInc. PrintedintheFederalRepublicofGermany
250MassachusettsAve. Printedonacid-freepaper
Cambridge,MA02139
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ISBN: 978-3-527-32331-9
V
Contents
List of Contributors XIX
Preface XXV
A Personal Foreword XXVII
PartI
1 ProcessLogistics,TestingStrategiesandAutomationAspects 3
HansjoergHaas,RobertS.DeWitte,RobertDunn-Dufault,
andAndreasStelzer
1.1 Introduction 3
1.2 TheProcessfromRawIngredientstoData 3
1.2.1 CompoundManagement 5
1.2.2 CellBiology 6
1.2.3 LeadProfiling 7
1.2.4 LiquidChromatography/MassSpectrometry 7
1.3 DMPKTestingStrategies:theProcessfromDatatoDecisions 8
1.4 NewQuestions,NewAssaysandNewTechnologiesChallenge
theProcess 10
1.5 OrganizationalModelstoScaleUptheProcess 11
1.5.1 FoodCourt 11
1.5.1.1 TheFastFoodRestaurant 12
1.5.1.2 TheFamilyRestaurantChain 12
1.6 CriticalFactorstoImprovetheProcess 13
1.7 MaterialsinADME/ToxScreening 14
1.8 MachinesandEquipmentinADME/ToxScreening 17
1.8.1 LiquidHandlers 17
1.8.2 DetectionandAnalysis 17
1.9 Software,DataRetrieval,Analysis,ManipulationandInterpretation 18
1.10 EnvironmentandManagement¼OrganizationalStructurein
ADME/ToxScreening 19
HitandLeadProfiling.EditedbyBernardFallerandLaszloUrban
Copyright(cid:1)2009WILEY-VCHVerlagGmbH&Co.KGaA,Weinheim
ISBN:978-3-527-32331-9
VI Contents
1.11 MethodsinADME/ToxScreening 20
1.11.1 ExamplesofWhole-ProcessApproaches 20
1.11.1.1 AutomationIslandswithManualDataUploadtoaLIMSSystem 21
1.11.1.2 CompletePhysicalIntegrationandAutomation 21
1.11.1.3 FederatedPhysicalAutomationwithSoftwareIntegration 22
1.12 Conclusions 22
References 23
2 PredictionofDrug-LikenessanditsIntegrationintotheDrug
DiscoveryProcess 25
AnsgarSchuffenhauerandMeirGlick
2.1 Introduction 25
2.2 ComputationalPredictionofDrug-Likeness 26
2.2.1 MachineLearning 26
2.2.2 EmpiricalRulesandTheirBasis 30
2.2.3 Drug-LikenessofNaturalProducts 32
2.2.4 DoLigandsofDifferentTargetClassesDifferinTheirDrug-Like
Properties? 34
2.2.5 UnwantedStructuralElements 34
2.3 WhatistheBestPracticeinUtilizingDrug-LikenessinDrug
Discovery? 35
2.4 ConcludingDiscussions 37
References 38
3 IntegrativeRiskAssessment 41
BernardFallerandLaszloUrban
3.1 TheTargetCompoundProfile 41
3.1.1 Introduction 41
3.1.2 TheImportanceoftheProjectedClinicalCompoundProfile
inEarlyDrugDiscovery 42
3.1.3 TheImpactofDeliveryOntheDesignoftheDrugDiscoveryProcess 43
3.2 TheConceptofHierarchicalTestinginPrimaryandFollow-Up
Assays 45
3.2.1 ImpactofTurn-AroundTime 47
3.2.2 AssayValidationandReferenceCompounds 47
3.2.3 RequirementsofProfilingAssayQuality 48
3.2.4 TheImportanceofFollow-UpAssays 48
3.3 ExposureAssays 49
3.3.1 BasicAbsorptionAssays 49
3.3.1.1 SolubilityAssays 50
3.3.1.2 PermeabilityAssays 50
3.3.2 ActiveTransportsandEfflux 51
3.3.3 Metabolism 51
3.3.4 DistributionandElimination 51
3.3.5 Drug–DrugInteractions 53
Contents VII
3.3.6 ivivCorrelations 53
3.4 IterativeAssays:LinkBetweenAssays 54
3.5 SpecificSafetyProfilingAssays 56
3.5.1 SensitivityandSpecificityofSafetyAssaysshouldbeAdjusted
tothePhaseofDrugDiscovery 58
3.5.2 AddressingSpeciesSpecificityinEarlyInVitroAssays 58
3.6 DataReportingandDataMining 59
3.6.1 DecisionMaking:TrendAnalysis,Go/NoGoDecisions 60
3.7 IntegrativeRiskAssessment 61
References 64
PartII
4 SolubilityandAggregation 71
WilliamH.Streng
4.1 ImportanceofSolubility 71
4.2 FactorsInfluencingSolubility 72
4.3 MethodsUsedtoDetermineSolubility 74
4.4 ApproachestoSolubility 76
4.5 SolubilityinNon-AqueousSolventsandCo-Solvents 78
4.6 SolubilityasaFunctionofpH 79
4.7 EffectofAggregationUponSolubility 83
4.8 DependenceofDissolutionuponSolubility 86
4.9 PartitioningandtheEffectofAggregation 87
4.10 SolubilityinSimulatedBiologicalFluids 89
References 90
5 InSilicoToolsandInVitroHTSApproachestoDetermine
LipophilicityDuringtheDrugDiscoveryProcess 91
SophieMartel,VincentGasparik,andPierre-AlainCarrupt
5.1 Introduction 91
5.2 VirtualFiltering:InSilicoPredictionoflogPandlogD 92
5.2.1 LipophilicityofNeutralSubstances:InSilicoMethodsto
PredictlogPN 92
oct
5.2.1.1 2DFragmentalApproaches 92
5.2.1.2 PredictionMethodsBasedon3-DMolecularStructure 95
5.2.1.3 GeneralCommentsonthePredictionoflogP 96
oct
5.2.2 PredictionModelsforlogPinOtherSolvent/WaterSystemsof
NeutralCompounds 97
5.2.3 PredictionModelsforlogPofIonicSpecies(logPI) 97
5.3 ExperimentalFiltering:theADMETCharacterizationofa
HitCollection 98
5.3.1 HTSlogP/logDDeterminationBasedonMicrotiterplateFormat 98
5.3.2 ChromatographicMethods 100
VIII Contents
5.3.2.1 Reverse-PhaseLiquidChromatography 100
5.3.2.2 ImmobilizedArtificialMembranes 102
5.3.2.3 HydrophilicInteractionChromatography 103
5.3.2.4 CapillaryElectrophoresis 104
5.3.3 AGlobalViewOnInVitroHTSMethodstoMeasure
logP/logD 104
5.4 ConcludingRemarks:EfficacyorAccuracyDilemma 105
References 107
6 MembranePermeability–MeasurementandPrediction
inDrugDiscovery 117
KiyohikoSugano,LourdesCucurull-Sanchez,andJoanneBennett
6.1 OverviewofMembranePermeation 117
6.1.1 Structure,PhysiologyandChemistryoftheMembrane 117
6.1.2 PassiveTranscellularPathway:pHPartitionTheoryastheBasis
ofUnderstandingMembranePermeability 118
6.1.3 ParacellularPathway 119
6.1.4 ActiveTransporters 119
6.1.5 InVitro–InVivoExtrapolation 119
6.2 InVitroCellModels 121
6.2.1 IntestinalCellCultureModels 121
6.2.2 BBBCellCultureModels 122
6.2.3 CellModelstoStudyActiveTransporters 123
6.2.4 CorrelationofinVitroModelstoHumanP andFraction
eff
AbsorbedData 124
6.2.5 CorrelationofCellCultureModelswithInVivoBrain
Penetration 124
6.3 ArtificialMembranes 125
6.3.1 PartitionandPermeation 125
6.3.2 ParallelArtificialMembranePermeationAssay:Recent
Progress 126
6.3.2.1 UnderstandingPAMPA 126
6.3.2.2 VariationofPAMPA:RecentProgress 127
6.3.2.3 PhospholipidVesiclePAMPA 127
6.3.2.4 Phospholipid–OctanolPAMPA 127
6.3.2.5 Tri-LayerPAMPA 127
6.3.2.6 MucusLayerAdheredPAMPA 127
6.3.3 ApplicationofPAMPAforDrugDiscovery 128
6.4 LimitationofInVitroAssays 128
6.4.1 ImpactofUWLonPermeability 128
6.4.2 MembraneBinding 129
6.4.3 LowSolubility 129
6.4.4 DifferenceoftheParacellularPathway 129
6.4.5 InterlaboratoryVariability 129
6.5 ComputationalApproaches/InSilicoModeling 130
Contents IX
6.5.1 InVivoSystems 130
6.5.2 InVitroCellularMembraneSystems 132
6.5.3 ArtificialMembranes 134
6.5.4 Perspectives 135
6.6 Outlook 135
References 136
7 DrugMetabolismandReactiveMetabolites 145
AlanP.Watt
7.1 IntroductiontoDrugMetabolism 145
7.1.1 HistoricalPerspective 145
7.1.2 InVitroMetabolism 146
7.1.3 CytochromeP450 148
7.1.4 PredictionofDrugMetabolism 149
7.2 AdverseDrugReactions 149
7.2.1 ADRClassification 150
7.2.2 IdiosyncraticDrugReactions 150
7.3 Bioactivation 151
7.3.1 Definition 151
7.3.2 ReactionsofElectrophilicMetabolites 151
7.3.3 Glutathione 151
7.3.4 DetectionofGSHConjugates 151
7.3.5 AcylGlucuronides 152
7.3.6 FreeRadicalsandOxidativeStress 152
7.4 ReactiveMetabolitesandIdiosyncraticToxicity 153
7.4.1 TheHaptenHypothesis 153
7.4.1.1 Immune-MediatedCutaneousReactions 153
7.4.2 TheDangerHypothesis 153
7.4.3 AlternatePerspectivestoCovalentBinding 154
7.4.3.1 Non-ToxicologicalCovalentBinding 154
7.4.3.2 CovalentBindingasDetoxification 154
7.5 MeasurementofReactiveMetabolites 155
7.5.1 TrappingAssays 155
7.5.1.1 SoftNucleophiles 155
7.5.1.2 HardNucleophiles 155
7.5.2 MassSpectrometricDetectionofGSHConjugatesand
MercapturicAcids 155
7.5.3 RadiometricAssays 156
7.5.3.1 CovalentBindingtoLiverMicrosomes 157
7.5.3.2 ExVivoCovalentBinding 157
7.5.3.3 14CCyanideTrapping 157
7.5.3.4 RadiolabeledSoftNucleophileTrapping 158
7.5.4 AlternateApproaches 158
7.6 StrategiesforMinimizingReactiveMetaboliteRisk 159
7.6.1 DoseandExposure 159