Chemoinformatics in Drug Discovery

498 Pages·2005·5.283 MB·English

by  Raimund Mannhold, Hugo Kubinyi, Gerd Folkers(eds.)

Chemoinformatics
inDrugDiscovery
Editedby
TudorI.Oprea
MethodsandPrinciplesinMedicinalChemistry
EditedbyR.Mannhold,H.Kubinyi,G.Folkers
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H.-D.Ho¨ltje,H.Timmerman,J.Vacca,H.vandeWaterbeemd,T.Wieland
RecentlyPublishedVolumes:
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T.Lengauer(ed.) H.-J.Bohm,G.Schneider(eds.)
Bioinformatics – Protein-LigandInteractions
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ProteinCrystallography
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Chemoinformatics in Drug Discovery
Edited by
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ISBN-13:978-3-527-30753-1
ISBN-10:3-527-30753-2
V
Contents
APersonalForeword XV
Preface XVII
ListofContributors XIX
1 IntroductiontoChemoinformaticsinDrugDiscovery–
APersonalView 1
GarlandR.Marshall
1.1 Introduction 1
1.2 HistoricalEvolution 4
1.3 KnownversusUnknownTargets 5
1.4 GraphTheoryandMolecularNumerology 6
1.5 Pharmacophore 7
1.6 Active-AnalogApproach 8
1.7 Active-SiteModeling 9
1.8 ValidationoftheActive-AnalogApproachandActive-SiteModeling 10
1.9 PLS/CoMFA 11
1.10 PredictionofAffinity 12
1.11 ProteinStructurePrediction 13
1.12 Structure-BasedDrugDesign 15
1.13 RealWorldPharmaceuticalIssues 15
1.14 CombinatorialChemistryandHigh-throughputScreens 16
1.15 DiversityandSimilarity 16
1.16 PredictionofADME 17
1.17 FailurestoAccuratelyPredict 17
1.18 Summary 18
References 19
ChemoinformaticsinDrugDiscovery.EditedbyTudor I. Oprea
Copyright2004WILEY-VCHVerlagGmbH&Co.KGaA,Weinheim
ISBN:3-527-30753-2
VI Contents
PartI VirtualScreening 23
2 ChemoinformaticsinLeadDiscovery 25
TudorI.Oprea
2.1 ChemoinformaticsintheContextofPharmaceuticalResearch 25
2.2 LeadsintheDrugDiscoveryParadigm 27
2.3 IsThereaTrendforHighActivityMolecules? 29
2.4 TheConceptofLeadlikeness 32
2.5 Conclusions 37
References 38
3 ComputationalChemistry,MolecularComplexityandScreening
SetDesign 43
MichaelM.Hann,AndrewR.Leach,andDarrenV.S.Green
3.1 Introduction 43
3.2 BackgroundConcepts:theVirtual,TangibleandRealWorldsof
Compounds,the‘‘KnowledgePlot’’andTargetTractability 44
3.3 TheConstructionofHighThroughputScreeningSets 45
3.4 CompoundFilters 47
3.5 ‘‘Leadlike’’ScreeningSets 48
3.6 FocusedandBiasedSetDesign 54
3.7 Conclusion 55
References 56
4 AlgorithmicEnginesinVirtualScreening 59
MatthiasRarey,ChristianLemmen,andHansMatter
4.1 Introduction 59
4.2 SoftwareToolsforVirtualScreening 61
4.3 PhysicochemicalModelsinVirtualScreening 62
4.3.1 IntermolecularForcesinProtein–LigandInteractions 63
4.3.2 ScoringFunctionsforProtein–LigandRecognition 66
4.3.3 CoveringConformationalSpace 67
4.3.4 ScoringStructuralAlignments 68
4.4 AlgorithmicEnginesinVirtualScreening 69
4.4.1 MathematicalConcepts 69
4.4.2 AlgorithmicConcepts 76
4.4.3 DescriptorTechnology 81
4.4.4 GlobalSearchAlgorithms 85
4.5 EnteringtheRealWorld:VirtualScreeningApplications 89
4.5.1 PracticalConsiderationsonVirtualScreening 89
4.5.2 SuccessfulApplicationsofVirtualScreening 91
4.6 PracticalVirtualScreening:SomeFinalRemarks 99
References 101
Contents VII
5 StrengthsandLimitationsofPharmacophore-BasedVirtual
Screening 117
DragosHorvath,BoryeuMao,RafaelGozalbes,Fre´de´riqueBarbosa,
andSherryL.Rogalski
5.1 Introduction 117
5.2 The‘‘Pharmacophore’’Concept:PharmacophoreFeatures 117
5.3 PharmacophoreModels:ManagingPharmacophore-related
Information 118
5.4 TheMainTopicofThisPaper 119
5.5 TheCox2DataSet 119
5.6 PharmacophoreFingerprintsandSimilaritySearches 120
5.7 MolecularFieldAnalysis(MFA)-BasedPharmacophore
Information 123
5.8 QSARModels 125
5.9 HypothesisModels 125
5.10 TheMinimalistOverlay-IndependentQSARModel 126
5.11 MinimalistandConsensusOverlay-BasedQSARModels 128
5.12 DiversityAnalysisoftheCox2CompoundSet 131
5.13 DoHypothesisModelsActuallyTellUsMoreThanSimilarityModels
AbouttheStructuralReasonsofActivity? 131
5.14 WhyDidHypothesisModelsFailtoUnveiltheKeyCox2Site–Ligand
Interactions? 134
5.15 Conclusions 136
References 137
PartII HitandLeadDiscovery 141
6 EnhancingHitQualityandDiversityWithinAssayThroughput
Constraints 143
IainMcFadyen,GaryWalker,andJuanAlvarez
6.1 Introduction 143
6.1.1 WhatMakesaGoodLeadMolecule? 144
6.1.2 CompoundCollections – SuitabilityasLeads 144
6.1.3 CompoundCollections – Diversity 145
6.1.4 DataReliability 146
6.1.5 SelectionMethods 149
6.1.6 EnhancingQualityandDiversityofActives 153
6.2 Methods 154
6.2.1 ScreeningLibrary 155
6.2.2 DeterminationofActivityThreshold 156
6.2.3 Filtering 156
6.2.4 High-ThroughputScreenClusteringAlgorithm(HTSCA) 157
6.2.5 DiversityAnalysis 160
VIII Contents
6.2.6 DataVisualization 161
6.3 Results 162
6.3.1 PeptideHydrolase 162
6.3.2 ProteinKinase 167
6.3.3 Protein–ProteinInteraction 168
6.4 DiscussionandConclusion 169
References 172
7 MolecularDiversityinLeadDiscovery:FromQuantitytoQuality 175
CullenL.Cavallaro,DoraM.Schnur,andAndrewJ.Tebben
7.1 Introduction 175
7.2 LargeLibrariesandCollections 176
7.2.1 MethodsandExamplesforLargeLibraryDiversityCalculations 177
7.3 Medium-sized/Target-classLibrariesandCollections 181
7.3.1 ComputationalMethodsforMedium-andTarget-classLibrariesand
Collections 183
7.4 SmallFocusedLibraries 189
7.4.1 ComputationalMethodsforSmallandFocusedLibraries 190
7.5 Summary/Conclusion 191
References 192
8 InSilicoLeadOptimization 199
ChrisM.W.Ho
8.1 Introduction 199
8.2 TheRiseofComputer-aidedDrugRefinement 200
8.3 RACHELSoftwarePackage 201
8.4 ExtractionofBuildingBlocksfromCorporateDatabases 201
8.5 IntelligentComponentSelectionSystem 203
8.6 DevelopmentofaComponentSpecificationLanguage 205
8.7 FiltrationofComponentsUsingConstraints 207
8.8 Template-drivenStructureGeneration 208
8.9 ScoringFunctions – MethodstoEstimateLigand–Receptor
Binding 209
8.10 TargetFunctions 212
8.11 LigandOptimizationExample 214
References 219
Contents IX
PartIII DatabasesandLibraries 221
9 WOMBAT:WorldofMolecularBioactivity 223
MariusOlah,MariaMracec,LilianaOstopovici,RamonaRad,AlinaBora,
NicoletaHadaruga,IonelaOlah,MagdalenaBanda,ZenoSimon,
MirceaMracec,andTudorI.Oprea
9.1 Introduction – BriefHistoryoftheWOMBATProject 223
9.2 WOMBAT2004.1Overview 224
9.3 WOMBATDatabaseStructure 227
9.4 WOMBATQualityControl 228
9.5 UncoveringErrorsfromLiterature 231
9.6 DataMiningwithWOMBAT 234
9.7 ConclusionsandFutureChallenges 235
References 237
10 Cabinet–ChemicalandBiologicalInformaticsNetwork 241
VeraPovolna,ScottDixon,andDavidWeininger
10.1 Introduction 241
10.1.1 IntegrationEfforts,WWWasInformationResourceand
Limitations 241
10.1.2 Goals 243
10.2 MeritsofFederationRatherthanUnification 243
10.2.1 TheMeritsofUnification 244
10.2.2 TheMeritsofFederation 244
10.2.3 UnifyingDisparateDataModelsisDifficult,Federatingthem
isEasy 245
10.2.4 LanguageisaNaturalKey 246
10.3 HTTPisAppropriateCommunicationTechnology 248
10.3.1 HTTPisSpecificallyDesignedforCollaborativeComputing 248
10.3.2 HTTPistheDominantCommunicationProtocolToday 248
10.3.3 HTMLProvidesaUniversallyAccessibleGUI 249
10.3.4 MIME‘‘Text/Plain’’and‘‘Application/Octet-Stream’’areImportant
Catch-alls 249
10.3.5 OtherMIMETypesareUseful 250
10.3.6 OneSignificantHTTPWork-aroundisRequired 250
10.4 Implementation 251
10.4.1 DaylightHTTPToolkit 251
10.4.2 Metaphorics’CabinetLibrary 252
10.5 SpecificExamplesofFederatedServices 252
10.5.1 Empath – MetabolicPathwayChart 253
10.5.2 Planet – Protein–ligandAssociationNetwork 254
10.5.3 ECBook – EnzymeCommissionCodebook 254
10.5.4 WDI – WorldDrugIndex 254
X Contents
10.5.5 WOMBAT – WorldofMolecularBioactivity 255
10.5.6 TCM(TraditionalChineseMedicines),DCM(DictionaryofChinese
Medicine),PARK(PhotoARKive)andzi4 255
10.5.7 Cabinet‘‘Download’’Service 256
10.5.8 CabinetUsageExample 256
10.6 DeploymentandRefinement 262
10.6.1 LocalDeployment 264
10.6.2 IntranetDeployment 264
10.6.3 InternetDeployment 265
10.6.4 OnlineDeployment 266
10.7 Conclusions 266
References 268
11 StructureModificationinChemicalDatabases 271
PeterW.KennyandJensSadowski
11.1 Introduction 271
11.2 Permute 274
11.2.1 ProtonationandFormalCharges 274
11.2.2 Tautomerism 275
11.2.3 NitrogenConfigurations 276
11.2.4 DuplicateRemoval 276
11.2.5 NestedLoop 276
11.2.6 ApplicationStatistics 277
11.2.7 ImpactonDocking 277
11.3 Leatherface 279
11.3.1 ProtonationandFormalCharges 279
11.3.2 Tautomerism 280
11.3.3 IonizationandTautomerModel 281
11.3.4 RelationshipsbetweenStructures 282
11.3.5 SubstructuralSearchingandAnalysis 283
11.4 ConcludingRemarks 283
References 284
12 RationalDesignofGPCR-specificCombinationalLibraries
BasedontheConceptofPrivilegedSubstructures 287
NikolayP.Savchuk,SergeyE.Tkachenko,andKonstantinV.Balakin
12.1 Introduction – CombinatorialChemistryandRationalDrug
Design 287
12.2 RationalSelectionofBuildingBlocksBasedonPrivilegedStructural
Motifs 288
12.2.1 PrivilegedStructuresandSubstructuresintheDesignof
PharmacologicallyRelevantCombinatorialLibraries 288