Lead Generation: Volume 67 - Methods and Strategies (Methods and Principles in Medicinal Chemistry)

Lead Generation: Volume 67 - Methods and Strategies (Methods and Principles in Medicinal Chemistry)

By: Markus Haeberlein (editor), Jorg Holenz (editor), Raimund Mannhold (series_editor), Gerd Folkers (series_editor), Hugo Kubinyi (series_editor)Hardback

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In this comprehensive two-volume resource on the topic senior lead generation medicinal chemists present a coherent view of the current methods and strategies in industrial and academic lead generation. This is the first book to combine both standard and innovative approaches in comparable breadth and depth, including several recent successful lead generation case studies published here for the first time. Beginning with a general discussion of the underlying principles and strategies, individual lead generation approaches are described in detail, highlighting their strengths and weaknesses, along with all relevant bordering disciplines like e.g. target identification and validation, predictive methods, molecular recognition or lead quality matrices. Novel lead generation approaches for challenging targets like DNA-encoded library screening or chemical biology approaches are treated here side by side with established methods as high throughput and affinity screening, knowledge- or fragment-based lead generation, and collaborative approaches. Within the entire book, a very strong focus is given to highlight the application of the presented methods, so that the reader will be able to learn from 'real life? examples. The final part of the book presents several lead generation case studies taken from different therapeutic fields, including diabetes, cardiovascular and respiratory diseases, neuroscience, infection and tropical diseases. The result is a prime knowledge resource for medicinal chemists and for every scientist involved in lead generation.

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About Author

Joerg Holenz is a trained organic and medicinal chemist and acquired his PhD in Germany on the synthesis of alkaloids as antimalarial agents. After leading the preclinical activities of the marketed analgesic Tapentadol (Grunenthal Pharmaceuticals GmbH), he headed the medicinal chemistry department of Barcelona-based Laboratorios Esteve. He then moved to AstraZeneca's CNS/ pain research unit in Sweden to head lead generation chemistry. In 2012, Joerg was selected to join AZ's newly formed 'virtual' neuroscience unit in Boston as director of discovery and preclinical sciences. As a project leader he is responsible for pioneering a novel concept of driving research and development projects via increased use of academic and industry collaborative networks. In his career, Joerg worked predominantly with peripheral and central targets in the pain and neuroscience disease areas. He has edited, authored or contributed to more than 45 publications, 50 patent applications and several books and book chapters.

Contents

Dedication V List of Contributors XXI Preface XXVII A Personal Foreword XXXI Volume 68a Part I Introduction to Lead Generation 1 1 Introduction: Learnings from the Past Characteristics of Successful Leads 3 Mike Hann Acknowledgments 10 References 10 2 Modern Lead Generation Strategies 13 Jorg Holenz and Dean G. Brown 2.1 Lead Generation Greatly Influences Clinical Candidate Quality 14 2.2 Screening of Compound Libraries has Undergone a Major Paradigm Change 15 2.3 New Chemical Modalities are Available to Tackle Difficult Targets 15 2.4 As Demands have Increased, New Lead Generation Methods Emerged 16 2.5 How do Lead Generation Chemists Meet These Challenges and Subsequently Provide Their Lead Optimization Colleagues with High-Quality Lead Series? 17 2.5.1 Learnings can be Drawn from LG Project Failures 17 2.5.2 How Many Compounds to Screen to Generate High-Quality Leads? 18 2.5.3 Which Compounds to Screen to Generate High-Quality Leads? 19 2.5.4 Developing Project-Customized, Concerted, and Comprehensive Lead Generation Strategies will Increase LG Success Rates: the CREATION of Leads 20 2.5.5 Selecting the Target Defines LG Success Rates 21 2.5.6 Lead Generation should be Complemented by Auxiliary Technologies to Characterize Hits 21 2.5.7 Phenotypic Screens are Often Complemented by a Chemical Biology Arm 22 2.5.8 The Lead Generation Strategy is Defined by the Budget Allocated 22 2.5.9 Cost-Efficient but Information-Rich Lead Generation Strategies 23 2.5.10 The Revival of Potency as the Most Important Lead Criterion? 24 2.5.11 When has a LG Campaign Delivered Successfully? 27 References 31 Part II The Importance of Target Identification for Generating Successful Leads 35 3 Ligandability of Drug Targets: Assessment of Chemical Tractability via Experimental and In Silico Approaches 37 Udo Bauer and Alexander L. Breeze 3.1 Introduction 37 3.2 The Concept of Ligandability 39 3.2.1 General Characteristics of Ligandable Targets 39 3.3 The Intersection of Ligandability and Human Disease Target Space 40 3.3.1 Experimental Techniques for Assessing Target Ligandability 42 3.3.1.1 High-Throughput Screening and Subset/ Validation Set Screening 43 3.3.1.2 Fragment Screening 44 3.4 Practical Examples of the Use of Fragment Screening for Ligandability Assessment 50 3.4.1 Chemical Tractability Assessment by in silico Approaches 54 3.4.1.1 Pocket-Finding Algorithms 54 3.4.1.2 Discrimination Functions and Validation Sets 55 3.4.1.3 Simulation-Based Methods for Identifying Interaction Potentials 56 3.5 Conclusions and Outlook 56 References 58 4 Chemistry-Driven Target Identification 63 Ivan Cornella-Taracido, Ryan Hicks, Ola Engkvist, Adam Hendricks, Ronald Tomlinson, and M. Paola Castaldi 4.1 Introduction 63 4.2 Chemistry-Driven Target Discovery: Enabling Biology 65 4.2.1 Biological Samples 65 4.2.2 Cells Cultured in 2D 66 4.2.3 Cells Cultured in 3D, Organoids, and Tissues 67 4.2.4 Nonhuman Cells and Whole-Organism Screening 68 4.2.5 Functional Assays and Readouts 68 4.3 Chemistry for Target Discovery 71 4.3.1 Screening Deck Selection 71 4.3.2 Triaging and Prioritization of Chemical Matter 72 4.3.3 SAR Expansion and Probe Synthesis for Target Deconvolution 73 4.4 Small-Molecule Target Identification Techniques 75 4.4.1 In Silico Target Deconvolution 75 4.4.2 Biochemical Profiling 77 4.4.3 Target Deconvolution Correlational Tools 78 4.4.4 Subcellular Localization 79 4.4.5 Chemical Genetics 79 4.4.6 Affinity Chemical Proteomics 81 4.4.7 Target Corroboration 84 4.5 Conclusions 86 References 89 Part III Hit Generation Methods 93 5 Lead Generation Based on Compound Collection Screening 95 Dirk Weigelt and Ismet Dorange 5.1 Introduction 95 5.2 Screening of Existing Collections: the General Workflow 96 5.2.1 High-Throughput Screening 96 5.2.2 Medium-Throughput Screening: Selection Methods 98 5.3 Generation of New Screening Compounds 99 5.3.1 Collection Enhancement Programs 102 5.3.2 Library Design and Compound Selection 102 5.3.2.1 Number of Dimensions 103 5.3.2.2 Enumeration and Filtering 104 5.3.2.3 Layout 106 5.3.3 Focus on Synthetic Feasibility 107 5.3.3.1 Multicomponent Reactions 107 5.3.3.2 Click Chemistry 108 5.3.3.3 Diversity-oriented Synthesis 108 5.3.4 Structure-driven Approaches 109 5.3.4.1 Privileged Structures 110 5.3.4.2 Structure-driven Approaches Toward Unchartered Territory 112 5.3.5 Target Focus 114 5.3.5.1 Kinases 114 5.3.5.2 G-Protein-Coupled Receptors 115 5.3.5.3 Ion Channels 116 5.3.5.4 Protein Protein Interactions 117 5.4 Other Concepts 117 5.4.1 Natural Products 118 5.4.2 DNA-Encoded Libraries 119 5.4.3 Spatially Addressed Libraries 120 5.4.4 On-bead Screening 120 5.4.5 Dynamic Combinatorial Chemistry 121 5.4.6 Cocktails and Mixtures 121 5.5 Summary and Outlook 122 References 123 6 Fragment-Based Lead Generation 133 Ivan V. Efremov and Daniel A. Erlanson 6.1 Introduction 133 6.2 Screening Methods 135 6.3 Hit Validation 137 6.4 Ligand Efficiency and Other Metrics 138 6.5 Hit Optimization 139 6.6 Fragment Growing 140 6.7 Fragment Linking 144 6.8 Protein Protein Interactions 147 6.9 GPCRs 151 6.10 Computational Approaches 152 6.11 Conclusions 153 References 154 7 Rational Hit Generation 159 Bernd Wellenzohn and Alexander Weber 7.1 Introduction 159 7.2 Lead Generation: Transition State and Substrate Analogs 161 7.3 Hit Generation by Rational Library Design 165 7.4 Hit Generation by Virtual Screening 167 7.4.1 Structure-based VS in Enumerated Molecules 170 7.4.2 Ligand-based VS in Nonenumerated Virtual Chemical Spaces 171 7.5 Hit Generation by Scaffold Replacement Technologies 173 7.6 Hit Generation by Chemogenomics Approaches 174 7.7 Summary 178 References 178 8 Competitive Intelligence based Lead Generation and Fast Follower Approaches 183 Yu Jiang, Ziping Liu, Jorg Holenz, and Hua Yang 8.1 Introduction 183 8.2 Competitive Intelligence-based Approach 185 8.2.1 Example A: A Case Study for the Hybrid Strategy 190 8.2.2 Example C: A Case Study for the Fused Strategy 192 8.2.3 Example C: A Case Study for the Fused Strategy 193 8.2.4 Example D: A Case Study for the Fused Strategy 196 8.2.5 Example E: A Case Study for the Chimera Strategy 197 8.3 Fast Follower Approach 201 8.3.1 Salfanilamide-based Fast Follower Approaches 202 8.3.2 Omeprazole-based Fast Follower Approaches 203 8.3.3 Rimonabant-based Fast Follower Approach 210 References 214 9 Selective Optimization of Side Activities: An Alternative and Promising Strategy for Lead Generation 221 Norbert Handler, Andrea Wolkerstorfer, and Helmut Buschmann 9.1 Introduction 221 9.1.1 Drug Selectivity and Unwanted or Desired Side Effects 222 9.2 Definition, Rational, and Concept of the SOSA Approach 223 9.2.1 Multiple Ligands and Polypharmacology 224 9.2.2 Safety and Bioavailability 225 9.3 Drugs in Other Drugs: Drug as Fragments 225 9.4 Drug Repositioning and Drug Repurposing 226 9.4.1 Old Drugs 226 9.5 The SOSA Approach and Analog Design 227 9.6 Patentability and Interference Risk of the SOSA Approach 230 9.6.1 Analogization, Optimization, and Isosterism 230 9.7 Case Studies and Examples 231 9.7.1 Sulfonamides 231 9.7.2 Morphine Analogs 232 9.7.3 Warfarin 232 9.7.4 Sildenafil (Viagra) 232 9.7.5 Thalidomide Analogs 233 9.7.6 Bupropion 234 9.7.7 Chlorpromazine 235 9.7.8 Chlorothiazide 235 9.7.9 Propranolol 235 9.7.10 Minaprine Analogs 236 9.7.11 Viloxazine Analogs 237 9.7.12 Methylation in the SOSA Strategy of Drug Design 237 9.7.13 Discovery of New Antiplasmodial Compounds 239 9.7.14 Drugs Acting on Central Nervous System Targets as Leads for Non-CNS Targets 241 9.7.15 Mexiletine Derivatives as Orally Bioavailable Inhibitors of Urokinase-Type Plasminogen Activator 242 9.7.16 Amiloride Analogs as Inhibitors of the Urokinase-type Plasminogen Activator 245 9.7.17 Flavonoids with an Oligopolysulfated Moiety: A New Class of Anticoagulant Agents 246 9.7.18 Clioquinol 249 9.8 Conclusions 251 References 252 10 Lead Generation for Challenging Targets 259 Jinqiao Wan, Dengfeng Dou, Hongmei Song, Xian-Hui Wu, Xuemin Cheng, and Jin Li 10.1 Introduction 259 10.2 DNA-Encoded Library Technology in Lead Generation 260 10.2.1 Background 260 10.2.2 DNA-Recorded Synthesis-Assisted Libraries 262 10.2.3 DNA-Templated Synthesis-Assisted Libraries 264 10.2.4 Encoded Self-Assembling Chemical Libraries 266 10.2.5 Summary and Perspective 267 10.3 Stapled Peptide 276 10.3.1 Background 276 10.3.2 Structure, Design, and Synthesis of Stapled Peptide 278 10.3.2.1 Stapled Peptide Structure 278 10.3.2.2 Stapled Peptide Design 280 10.3.2.3 Stapled Peptide Synthesis 282 10.3.3 Stapled Peptide Solution -Helix Conversion Measurement 283 10.3.4 Stapled Peptide Affinity Evaluation and -Helix Content Correlation 284 10.3.4.1 Surface Plasmon Resonance Binding Assays 284 10.3.4.2 Fluorescence Polarization Assay 284 10.3.4.3 Stapled Peptide Affinity and -Helix Content Correlation 285 10.3.5 Stapled Peptide Permeability 286 10.3.6 Peptide Stability Assay 288 10.3.7 Outlook 288 10.4 Phenotypic Screening 289 10.4.1 Introduction 289 10.4.2 Basics for Establishing a Phenotypic Screen 291 10.4.2.1 Identify a Druggable Phenotype and the Type of Readout 291 10.4.2.2 Assay Design 291 10.4.2.3 Hit Selection and Secondary Assay 291 10.4.3 Typical Phenotypic Assays 292 10.4.3.1 Cell-Viability Assay 292 10.4.3.2 Fluorescent Imaging Plate Reader Technology 293 10.4.3.3 High-Content Screening 293 10.4.4 In Vitro Phenotypic Screening 293 10.4.4.1 Classic Phenotypic Screening 293 10.4.4.2 Patient-Derived Stem Cell in Drug Discovery 294 10.4.4.3 Phenotypic Screening on iPSC-Derived Disease Models 295 10.4.4.4 High-Content Cytotoxicity Screening by iPSC-Derived Hepatocytes 296 10.5 Summary 297 References 298 11 Collaborative Approaches to Lead Generation 307 Fabrizio Giordanetto, Anna Karawajczyk, and Graham Showell 11.1 Introduction 307 11.2 Creativity 308 11.3 Speed 308 11.4 Risk Sharing 308 11.5 Intellectual Property 309 11.6 Costs 309 11.7 Management 310 11.8 Lilly s Open Innovation Drug Discovery 310 11.9 Molecular Library Program 312 11.10 EU Openscreen 314 11.11 European Lead Factory 315 11.12 Medicines for Malaria Venture 317 11.13 Open Source Malaria Project 320 11.14 Drugs for Neglected Diseases Initiative 320 11.15 Open Lab Foundation 321 11.16 Scientists Against Malaria 322 11.17 Open Source Drug Discovery 323 11.18 TB Alliance 323 11.19 Summary 324 References 325 Volume 68b Dedication V List of Contributors XXI Part IV Converting Hits to Successful Leads 329 12 A Medicinal Chemistry Perspective on the Hit-to-Lead Phase in the Current Era of Drug Discovery 331 Dean G. Brown 12.1 Introduction 331 12.2 Active to Hit Processes 333 12.3 Target Potency: Energetics of Binding 336 12.4 Addressing Vast Chemical Space: HtL Strategies 345 12.5 Matched Pair Analysis 348 12.6 The Role of Hydrophobicity and HtL 351 12.7 Probing H-Bond Donors and Acceptors 353 12.8 Structure Based DD in HtL 356 12.9 Statistical Molecular Design 358 12.10 Hit to Lead is not Lead Optimization 359 12.11 Summary 362 References 363 13 Molecular Recognition and Its Importance for Fragment-Based Lead Generation and Hit-to-Lead 367 Thorsten Nowak 13.1 Introduction 367 13.2 Brief Summary of the Main Factors that Govern Molecular Interactions 368 13.3 Thermodynamics of Molecular Interactions and Impact on Hit Finding and Optimization 369 13.4 Enthalpy as a Key Decision Tool in Medicinal Chemistry 371 13.5 Importance of Enthalpic Interactions: Drivers of Selectivity and Specificity? 373 13.6 Fragment Screening Hit Optimization: Fragment Linking 374 13.7 Interstitial Waters and Their Usefulness: Case Studies on HSP-90 381 13.8 Fragments to Find Hot Spots in Binding Pockets 385 13.9 Nonclassical Hydrogen Bonds Interactions of Halogen Atoms with -Systems and Carbonyl Groups: Factor Xa and Cathepsin L 386 13.10 Binding Mode Dependency of the Experimental Conditions and Chemical Framework of Ligand 390 13.11 Cooperativity in Binding: DAO or DAAO D-Amino Acid Oxidase 391 References 394 14 Affinity-Based Screening Methodologies and Their Application in the Hit-to-Lead Phase 401 Stefan Geschwindner 14.1 Introduction 401 14.2 Nuclear Magnetic Resonance Spectroscopy 402 14.3 Optical Biosensors: Surface Plasmon Resonance and Optical Waveguide Grating 404 14.4 Isothermal Titration Calorimetry 407 14.5 Thermal Shift Assay 411 14.6 Mass Spectrometry Approaches 412 14.7 Encoded Library Technologies 414 14.8 Emerging Technologies: Microscale Thermophoresis and Backscattering Interferometry 417 References 418 15 Predictive Methods in Lead Generation 425 Matthew D. Segall and Peter Hunt 15.1 Introduction 425 15.2 Compound Property Prediction 427 15.3 Multiparameter Optimization: Identifying High-Quality Compounds 430 15.3.1 Drug-like Properties 430 15.3.2 Filters 431 15.3.3 Desirability Functions and Probabilistic Scoring 432 15.3.4 Pareto Optimization 435 15.3.5 Example 436 15.4 De Novo Design: Guiding the Exploration of Novel Chemistry 439 15.4.1 Example Application 442 15.5 Selection: Balancing Quality with Diversity 443 15.6 Conclusions 445 References 447 16 Lead Quality 451 J. Willem M. Nissink, Sebastien Degorce, and Ken Page 16.1 Introduction 451 16.2 Properties in Drug Design 452 16.2.1 Primary Activity Assays 453 16.2.2 Physicochemical Properties 453 16.2.3 DMPK 454 16.2.4 Safety 454 16.2.5 Overall Profiles 456 16.3 Optimizing Properties: Useful Rules, Guides, and Simple Metrics for Early-Stage Projects 457 16.3.1 Rules for Potency: Ligand Efficiency Measures 457 16.3.2 Rules for Safety 462 16.3.3 Rules for DMPK and Mode of Administration: Early-Stage Structure-Based Profiling 464 16.3.3.1 Simple Design Rules for Good DMPK 464 16.3.3.2 Other DMPK Design Rules 465 16.3.4 Multiobjective Optimization 466 16.4 Predicted Dose to Man as a Measure of Early- and Late-Stage Lead Quality 467 16.4.1 Introduction 467 16.4.2 Description of Models and Data 469 16.4.3 Data Supporting Technique 471 16.4.3.1 Matching eD2M Doses with Normalized Observed Clinical Doses 472 16.4.3.2 Matching Cmax Values from eD2M and Clinical Studies 472 16.4.4 Flagging Potential Candidate Drugs Using eD2M 473 16.4.5 Determining Properties that Drive eD2M Predictions for a Series 474 16.5 Summary 480 References 481 Part V Hypothesis-driven Lead Optimization 487 17 The Strategies and Politics of Successful Design, Make, Test, and Analyze (DMTA) Cycles in Lead Generation 489 Steven S. Wesolowski and Dean G. Brown 17.1 DMTA Cycles: Perspectives from History 490 17.2 Test: What Assays, in What Order, and Why? 494 17.3 Additional Advice for Test Component of DMTA 496 17.4 Design: What to Make and Why? 496 17.5 Additional Advice for Design Component of DMTA 500 17.6 Make: Challenges and Strategies for Synthesis 501 17.7 Additional Advice for the Make Component of DMTA 502 17.8 Analyze: Making Sense of What s Been Done and Formulating Sensible Plans for the Next Designs 502 17.9 Additional Advice for Analyze Component of DMTA 508 17.10 Results: Do Lead Optimization Teams Get What They Need? 508 References 509 Part VI Recent Lead Generation Success Stories 513 18 Lead Generation Paved the Way for the Discovery of a Novel H3 Inverse Agonist Clinical Candidate 515 Christophe Genicot and Laurent Provins 18.1 Introduction 515 18.2 Hit Identification 517 18.3 Lead Generation 521 18.3.1 Exploration of Oxazoline Substitution 523 18.3.2 Rigidification of Propoxy Linker 531 18.3.3 Oxazoline/Oxazole Surrogates: Lactams 533 18.3.4 Conclusions 536 18.4 Lead Optimization and Candidate Selection 537 18.5 Conclusions 543 Acknowledgments 544 References 544 19 Vorapaxar: From Lead Identification to FDA Approval 547 Samuel Chackalamannil and Mariappan Chelliah 19.1 Introduction 547 19.2 Background Information on Antiplatelet Agents 549 19.3 Thrombin Receptor (Protease-activated Receptor-1) Antagonists as a Novel Class of Antiplatelet Agents 550 19.4 Mechanism of Thrombin Receptor Activation 550 19.5 Preclinical Data Supporting the Antiplatelet Effect of Thrombin Receptor Antagonists 551 19.6 Himbacine-derived Thrombin Receptor Antagonists 552 19.6.1 Lead Identification 552 19.6.2 Lead Generation of Himbacine-derived Thrombin Receptor Antagonist Hit 553 19.6.2.1 Structure Activity Relationship Studies 555 19.6.2.2 First-Generation Thrombin Receptor Antagonists 556 19.6.2.3 In vivo Metabolism of Himbacine Derivatives 558 19.6.2.4 Generation of Aryl Himbacine Leads 561 19.6.2.5 Second-Generation Leads that Incorporate Heteroatoms in the C-ring 562 19.6.2.6 Identification of nor-seco Himbacine Lead 564 19.6.3 Discovery of Vorapaxar (SCH 530348) 565 19.6.3.1 Clinical Studies of Vorapaxar 567 19.7 Conclusions 569 Abbreviations 570 Acknowledgments 570 References 571 20 Lead Generation Approaches Delivering Inhaled 2-Adrenoreceptor Agonist Drug Candidates 575 Michael Stocks and Lilian Alcaraz 20.1 Introduction 575 20.2 Lead Generation Exercises to Discover 2AR Agonist Clinical Candidates 577 20.3 AstraZeneca Lead Generation Exercises to Discover 2AR Agonist Clinical Candidates 587 20.4 Summary 593 References 593 21 GPR81 HTS Case Study 597 Eric Wellner and Ola Fjellstrom 21.1 General Remarks 597 21.2 The Target 598 21.3 Screening Cascade 599 21.4 Compound Selection (10 K Validation Set) 602 21.5 HTS 606 21.5.1 CSE 608 21.5.2 Single-Concentration Counterscreen 614 21.5.3 Clustering 615 21.5.4 Cluster Expansion and Nearest Neighbours 618 21.6 Hit Evaluation 618 21.6.1 Potency, Efficacy, and Curves 618 21.6.2 Binding Kinetics 621 21.6.3 Concentration Response Counterscreen 622 21.6.4 Hit Assessment 622 21.6.4.1 Size and Lipophilicity Efficiency Assessment 622 21.6.4.2 Secondary Pharmacology Assessment 626 21.6.5 Secondary Screening Cascade and Hit Expansion 630 21.6.6 Biological Effect Assay 634 21.7 Alternative Lead Generation Strategies 638 21.7.1 Pepducins and Other Modified Peptides 641 21.8 Conclusions 645 References 646 22 Development of Influenza Virus Sialidase Inhibitors 651 Mauro Pascolutti, Robin J. Thomson, and Mark von Itzstein 22.1 Introduction 651 22.2 Targets for Anti-influenza Drug Development: Receptor Binding and Receptor Cleavage 652 22.2.1 Targeting Receptor Binding by Haemagglutinin 654 22.2.2 Targeting Receptor Destruction by Sialidase 655 22.2.3 Influenza Virus Sialidase: Structure and Mechanism 656 22.3 Development of Influenza Virus Sialidase Inhibitors 658 22.3.1 The Development of Zanamivir: Proof of Concept and First-in-Class Sialidase Inhibitor Drug 659 22.3.1.1 Template Selection 659 22.3.1.2 Structure-based Inhibitor Design 662 22.3.1.3 X-Ray Crystallographic Confirmation of Inhibitor Binding Mode 665 22.3.1.4 Selectivity for Influenza Virus Sialidase over Human Sialidases 666 22.3.1.5 Efficacy against Virus Replication 667 22.3.1.6 Mode of Administration of the Highly Polar Drug 667 22.3.1.7 Modifying the Presentation of Zanamivir: Prodrugs and Multivalency 668 22.3.2 Sialidase Inhibitor Development on Noncarbohydrate Scaffolds 671 22.3.2.1 A Sialidase Inhibitor Based on a Cyclohexene Scaffold: The Development of Oseltamivir 671 22.3.2.2 A Sialidase Inhibitor Based on a Cyclopentane Scaffold: The Development of Peramivir 673 22.3.3 Monitoring Resistance to Influenza Virus Sialidase Inhibitors 675 22.4 Summary and Future Directions 676 References 676 23 The Discovery of Cathepsin A Inhibitors: A Project-Adapted Fragment Approach Based on HTS Results 687 Sven Ruf, Christian Buning, Herman Schreuder, Wolfgang Linz, Dominik Linz, Hartmut Rutten, Georg Horstick, Markus Kohlmann, Katja Kroll, Klaus Wirth, and Thorsten Sadowski 23.1 General Background 687 23.2 Cathepsin A enzyme 687 23.2.1 Structural Biology and Catalytic Mechanism 687 23.2.2 Structural and Catalytic Functions of CatA 689 23.2.3 Tissue Distribution and Substrates 689 23.2.4 Natural Products and Synthetic Peptides as Inhibitors of CatA 690 23.3 CatA and the Link to Cardiovascular Disease 691 23.4 Lead Discovery 692 23.4.1 High-Throughput Screening and Data Analysis 692 23.4.2 Evaluation of Hit Series 693 23.4.2.1 Covalent Inhibitor Series 693 23.4.2.2 Malonamide Series 697 23.4.2.3 Pyrazolone Hit Series 698 23.4.3 Explorative Chemistry Delivers a Novel Lead Structure 699 23.4.3.1 Crystal Structure of 9b Bound to CatA 705 23.5 Lead Optimization 705 23.6 Toward an in vivo Proof of Concept 711 23.7 Summary and Conclusions 713 References 714 24 Lead Structure Discovery for Neglected Diseases: Product Development Partnerships Driving Drug Discovery 717 Jeremy N. Burrows and Takushi Kaneko 24.1 Introduction 717 24.2 Malaria and Medicines for Malaria Venture 719 24.3 Malaria Lead Generation Strategy 719 24.4 Hit Identification Strategies 722 24.5 Optimization of a Marketed Antimalarial Chemotype 723 24.6 Target-Based Approaches 723 24.7 Asexual Blood-Stage Phenotypic Screening 724 24.8 Whole-Cell Screening: Results 725 24.9 Repositioning of Clinical Candidates Developed for Other Indications 726 24.10 Case Studies 727 24.10.1 Dihydroorotate Dehydrogenase (DHODH) 727 24.10.2 Whole-Cell Screening 728 24.11 Screening for Malaria Eradication 729 24.12 Tuberculosis and the Global Alliance for Tuberculosis Drug Development (TB Alliance) 729 24.13 Target Product Profiles 730 24.14 TB Alliance s Mission 730 24.15 Hit Generation Strategies for TB 732 24.16 Examples of Phenotypic Screens 733 24.17 Conclusions 741 References 741 25 A Fragmentation Enumeration Approach to Generating Novel Drug Leads 747 Pravin S. Iyer and Manoranjan Panda 25.1 Introduction 747 25.2 Principle 748 25.3 Research Methodology 748 25.3.1 Fragmentation 749 25.3.1.1 Origin of Parent Molecules 749 25.3.1.2 Cores and Daughters 749 25.3.1.3 Nonflat Cores 751 25.3.2 Intelligent Recombination and Enumeration 754 25.4 Evaluation 754 25.4.1 Preliminary Experimental Evaluation 755 25.4.2 In Silico Evaluation 755 25.4.3 Virtual Screening Using Enzyme Ligand Docking 756 25.5 Summary 758 References 759 Index 761

Product Details

  • publication date: 04/05/2016
  • ISBN13: 9783527333295
  • Format: Hardback
  • Number Of Pages: 824
  • ID: 9783527333295
  • weight: 2058
  • ISBN10: 3527333290

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