Wiley-VCH, August 2004



        Content
Preface    XV

A Personal Foreword    XVII

List of Contributors    XXI

Introduction    1
Gerhard Müller and Hugo Kubinyi    
	References    4

I	General Aspects    5

1	Target Family-directed Masterkeys in Chemogenomics    7
	Gerhard Müller    
	1.1	Introduction    7
	1.2	Medicinal Chemistry-based Chemogenomics Approach    15
	1.3	Densely Populated Target Families    16
	1.4	Privileged Structures: A Brief Historical Assessment    18
	1.5	Privileged Structures with Undesired Target Profiles    19
	1.6	File Enrichment Strategies with Recurring Substructures    21
	1.7	Recurring Structures Devoid of Target Family Correlations    22
	1.8	Convergent Pharmacophores for Target-hopping    27
	1.9	Target Family-directed Masterkey Concept    31
	1.10	Conclusions and Perspective    36
	References    38

2	Drug Discovery from Side Effects    43
	Hugo Kubinyi    
	2.1	A Historical Perspective: The Great Time of Serendipitous 
			Observations     44
	2.2	Clinical Observations of Side Effects    47
	2.3	Privileged Structures Bind to Many Different Targets    51
	2.4	Optimizing the Selectivity of Nonselective Lead Structures    55
	2.5	Selective Optimization of Side Activities    59
	2.6	Summary and Conclusions    65
	References    65

3	The Value of Chemical Genetics in Drug Discovery    69
	Keith Russell and William F. Michne    
	3.1	Introduction    69
	3.2	Knowledge Management in Drug Discovery    70
	3.3	Knowledge Gaps, Their Importance, and How to Address Them    71
	3.4	Target Validation: The Foundation of Drug Discovery    72
	3.5	Chemical Genetics - How Chemistry Can Contribute to Target 	
			Identification and Validation    72
	3.6	Integration of Chemistry and Biology: Importance and Issues    75
	3.7	Finding New Chemical Tools and Leads    75
	3.8	Is Biological Selectivity an Illusion?    86
	3.9	Synthesis of Chemical Genetics Libraries: New Organic Synthesis
 			Approaches to the Discovery of Biological Activity    89
	3.10	Information and Knowledge Management Issues    91
	3.11	Annotation of Small Molecules    92
	3.12	Summary    94
	References    94

4	Structural Aspects of Binding Site Similarity: A 3D Upgrade for 
	Chemogenomics    97
	Andreas Bergner and Judith Günther    
	4.1	Introduction    97
	4.1.1	Binding Sites: The Missing Link    97
	4.1.2	Target Assessment    98
	4.1.3	Lead Finding    99
	4.1.4	Lead Optimization    100
	4.2	Structural Biology of Binding Sites    101
	4.2.1	Energetic, Thermodynamic, and Electrostatic Aspects    102
	4.2.2	Functional Aspects    104
	4.2.3	Specificity versus Function    105
	4.2.4	Evolutionary Aspects    105
	4.3	Methods for Identifying Binding Sites    106
	4.3.1	Integrated Methods for the Prediction of Binding Sites    106
	4.3.2	Sampling the Protein Surface    107
	4.4	Methods for Detecting Binding Site Similarity    107
	4.4.1	Searches for Specific Structural Motifs    108
	4.4.2	General Methods for Searching Similar Structural Motifs    108
	4.4.3	Similar Shape and Property Searches    111
	4.5	Applications of Binding Site Analyses and Comparisons in Drug 
			Design     114
	4.5.1	Protein Kinases and Protein Phosphatases as Drug Targets    114
	4.5.2	Relationships of Fold, Function, and Sequence Similarities    115
	4.5.3	Druggability    117
	4.5.4	Relationship between Ligand Similarity and Binding Site 
			Similarity    118
	4.5.5	Selectivity Issues    120
	4.5.6	Caveats    123
	4.5.7	Protein Flexibility    124
	4.5.8	Ambiguities in Atom Type Assignment    125
	4.5.9	Versatility of Interaction Types    127
	4.5.10	Crystallographic Packing Effects    128
	4.6	Summary and Outlook    129
	References    132

II	Target Families    137

5	The Contribution of Molecular Informatics to Chemogenomics. 
	Knowledge-based Discovery of Biological Targets and Chemical 
	Lead Compounds    139
	Edgar Jacoby, Ansgar Schuffenhauer, and Pierre Acklin    
	5.1	Introduction    140
	5.2	Molecular Information Systems for Targets and Ligands    141
	5.3	Bioinformatics Discovery of Target Subfamilies with Conserved 	
			Molecular Recognition    145
	5.4	Cheminformatics Discovery of Potential Ligands of Target 
			Subfamilies with Conserved Molecular Recognition    149
	5.5	Knowledge-based Combinatorial Library Design Strategies 
			within Homogenous Target Subfamilies    155
	5.6	Conclusions    161
	References    162

6	Chemical Kinomics    167
	Bert M. Klebl, Henrik Daub, and György Kéri    
	6.1	Introduction    167
	6.2	Chemical Biology: The Hope    169
	6.3	Chemical Kinomics: A Target Gene Family Approach in Chemical 
			Biology    169
	6.3.1	Protein Kinase Inhibitor History    171
	6.3.2	Chemical Kinomics: An Amenable Approach    172
	6.3.2.1	Examples of Traditional Chemical Genomics Using 
			Kinase Inhibitors    172
	6.3.2.2	Forward Chemical Genomics Using a Kinase-biased 
			Compound Library     174
	6.3.2.3	Chemical Validation    174
	6.3.3	Orthogonal Chemical Genetics    176
	6.3.3.1	ASKAs: Analog-sensitive Kinase Alleles    176
	6.3.3.2	Cohen's Inhibitor-insensitive p38 Mutants    178
	6.3.3.3	Active Inhibitor-insensitive Kinase Mutants 
			(Orthogonal Protein Kinases)    179
	6.3.4	Chemical Proteomics for Kinases: KinaTorTM    182
	6.4	Conclusions    187
	References    188

7	Structural Aspects of Kinases and Their Inhibitors    191
	Rogier Buijsman    
	7.1	Introduction    191
	7.2	Structural Aspects of Kinases    194
	7.2.1	The General Structure of an Activated Kinase    194
	7.2.2	Kinase Activation    197
	7.3	Kinase Inhibition Principles    198
	7.3.1	Substrate-competitive Inhibitors    198
	7.3.2	ATP-competitive Inhibitors    200
	7.3.3	Activation Inhibitors/Allosteric Modulators    200
	7.3.4	Irreversible Inhibitors    203
	7.4	Structural Aspects of Kinase Inhibitors    205
	7.4.1	Kinase Inhibitor Scaffolds    205
	7.4.2	Selectivity Issues    212
	7.4.2.1	The Selectivity Dogma    212
	7.4.2.2	The Gatekeeper    212
	7.4.2.3	Hinge-directed Selectivity    214
	7.4.2.4	Binding Region II-directed Selectivity    215
	7.5	Outlook    216
	References    216

8	A Chemical Genomics Approach for Ion Channel Modulators    221
	Karl-Heinz Baringhaus and Gerhard Hessler    
	8.1	Introduction    221
	8.2	Structural Information on Ion Channels: Ion Channel Families    223
	8.3	Lead-finding Strategies for Ion Channel Modulators    227
	8.3.1	Ligand-based Lead Finding    228
	8.3.2	Structure-based Lead Finding    230
	8.4	Design of Ion Channel Focused Libraries: Chemical Genomics    233
	8.4.1	Design Principles    233
	8.4.2	Example: Building the Aventis Ion Channel Library    236
	8.5	Conclusions    239
	References    240

9	Phosphodiesterase Inhibitors: A Chemogenomic View    243
	Martin Hendrix and Christopher Kallus    
	9.1	Introduction    243
	9.2	PDE Isoenzymes and Subtypes    244
	9.3	Potential Therapeutic Applications of PDE Inhibitors    247
	9.4	Nonspecific PDE Inhibitors    247
	9.5	Inhibitors of the cGMP-specific PDE5 and PDE6    249
	9.5.1	Substrate-analogous PDE5 Inhibitors    249
	9.5.2	Inhibitors Carrying a Chloromethoxybenzyl Substituent    253
	9.5.3	Indole-type PDE5 Inhibitors    255
	9.6	PDE6 Inhibitors    258
	9.7	Inhibitors of cAMP-metabolizing PDE4 and PDE3    259
	9.7.1	Dual PDE4/3 Inhibitors    268
	9.7.2	PDE3 Inhibitors    269
	9.8	Inhibitors of Other Phosphodiesterases    272
	9.8.1	PDE1    272
	9.8.2	PDE2    275
	9.8.3	PDE7    277
	9.8.4	Recently Discovered PDEs 8-11    278
	9.9	Summary: A Chemogenomic View of PDE Inhibitors    280
	References    281

10	Proteochemometrics: A Tool for Modeling the Molecular Interaction 
	Space    289
	Jarl E. S. Wikberg, Maris Lapinsh, and Peteris Prusis    
	10.1	Introduction    289
	10.2	Definition and Principles of Proteochemometrics    290
	10.3	Modeling and Interpretation of Interaction Space    292
	10.4	Examples of Proteochemometric Modeling    295
	10.4.1	Proteochemometric Modeling of Chimeric MC Receptors 
			Interacting with MSH Peptides    295
	10.4.2	Proteochemometric Modeling of ?1 Adrenoceptors Using 
			z Scale Descriptors for Amino Acids    296
	10.4.3	Proteochemometric Modeling Using Wild-type Amine GPCRs    298
	10.4.4	Interaction of Organic Compounds with Melanocortin 
			Receptor Subtypes    302
	10.4.5	Modeling of Interactions between 'Proprietary Drug-like 
			Compounds' and 'Proprietary Proteins'    302
	10.5	Large-scale Proteochemometrics    303
	References    307

III	Chemical Libraries    311

11	Some Principles Related to Chemogenomics in Compound Library and 
	Template Design for GPCRs    313
	Thomas R. Webb    
	11.1	Introduction    313
	11.2	Diverse Libraries versus Targeted Libraries    314
	11.3	Design of Targeted Libraries via Ligand-based Design    315
	11.4	Ligand-based Template Design for GPCR-targeted Libraries    315
	References    320

12	Computational Filters in Lead Generation: Targeting Drug-like 
	Chemotypes    325
	Wolfgang Guba and Olivier Roche    
	12.1	Introduction    325
	12.2	Hard Filters    326
	12.2.1	Reducing the Number of False Positive Hits    326
	12.2.2	Lead-likeness, Drug-likeness    327
	12.3	Soft Filters    329
	12.3.1	Prediction of Physicochemical Properties    329
	12.3.2	Prediction of ADME and Toxicity Properties    330
	12.4	Prioritization of Chemotypes Based on Multivariate Profiling    331
	12.5	Concluding Remarks    334
	References    337

13	Navigation in Chemical Space: Ligand-based Design of Focused 
	Compound Libraries    341
	Gisbert Schneider and Petra Schneider    
	13.1	Defining Reference and Target    342
	13.2	A Straightforward Approach: Similarity Searching    346
	13.3	Fuzzy Pharmacophore Models    355
	13.4	Fast Binary Classifiers for Library Shaping    358
	13.4.1	Artificial Neural Networks    360
	13.4.2	Support Vector Machines    361
	13.4.3	An Important Step: Data Scaling    362
	13.4.4	Application to Library Design    362
	13.5	Mapping Chemical Space by Self-organizing Maps: A Pharmacophore 
			Road Map    366
	13.6	Concluding Remarks    371
	References    372

14	Natural Product-derived Compound Libraries and Protein Structure 
	Similarity as Guiding Principles for the Discovery of Drug 
	Candidates    377
	Marcus A. Koch and Herbert Waldmann    
	14.1	Introduction    377
	14.2	Protein Folds and Protein Function    378
	14.3	Implications for Library Design: Nature's Structural 
			Conservatism and Diversity    379
	14.4	Development of Natural Product-based Inhibitors for 
			Enzymes Belonging to the Same Family    381
	14.4.1	Nakijiquinone Derivatives as Selective Receptor 
			Tyrosine Kinase Inhibitors    381
	14.4.2	Dysidiolide Derivatives as Cdc25 Phosphatase Inhibitors    383
	14.5	Development of Natural Product-based Small-molecule Binders 
			to Proteins with Low Sequence Homology yet Exhibiting the Same 
			Fold      386
	14.5.1	Development of Leukotriene A4 Hydrolase Inhibitors    386
	14.5.2	Development of Sulfotransferase Inhibitors    389
	14.5.3	Development of Nuclear Hormone Receptor Modulators    393
	14.6	Conclusion: A New Guiding Principle for Chemical Genomics?    399
	References    401

15	Combinatorial Chemistry in the Age of Chemical Genomics    405
	Reni Joseph and Prabhat Arya    
	15.1	Introduction    405
	15.2	Combinatorial Approaches to Natural Product Analogs    406
	15.3	Diversity-oriented Synthesis of Natural-product-like 
			Libraries    418
	15.4	Conclusions    430
	References    430
	
Index    433


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