Details

Lead Generation


Lead Generation

Methods and Strategies
Methods & Principles in Medicinal Chemistry 1. Aufl.

von: Jörg Holenz, Raimund Mannhold, Hugo Kubinyi, Gerd Folkers

273,99 €

Verlag: Wiley-VCH
Format: EPUB
Veröffentl.: 16.03.2016
ISBN/EAN: 9783527677061
Sprache: englisch
Anzahl Seiten: 824

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Beschreibungen

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. <br> 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.<br> The result is a prime knowledge resource for medicinal chemists and for every scientist involved in lead generation.<br>
<p>Dedication V</p> <p>List of Contributors XXI</p> <p>Preface XXVII</p> <p>A Personal Foreword XXXI</p> <p><b>Volume 68a</b></p> <p><b>Part I Introduction to Lead Generation 1</b></p> <p><b>1 Introduction: Learnings from the Past – Characteristics of Successful Leads 3</b><br /><i>Mike Hann</i></p> <p>Acknowledgments 10</p> <p>References 10</p> <p><b>2 Modern Lead Generation Strategies 13</b><br /><i>Jörg Holenz and Dean G. Brown</i></p> <p>2.1 Lead Generation Greatly Influences Clinical Candidate Quality 14</p> <p>2.2 Screening of Compound Libraries has Undergone a Major Paradigm Change 15</p> <p>2.3 New Chemical Modalities are Available to Tackle Difficult Targets 15</p> <p>2.4 As Demands have Increased, New Lead Generation Methods Emerged 16</p> <p>2.5 How do Lead Generation Chemists Meet These Challenges and Subsequently Provide Their Lead Optimization Colleagues with High-Quality Lead Series? 17</p> <p>2.5.1 Learnings can be Drawn from LG Project Failures 17</p> <p>2.5.2 How Many Compounds to Screen to Generate High-Quality Leads? 18</p> <p>2.5.3 Which Compounds to Screen to Generate High-Quality Leads? 19</p> <p>2.5.4 Developing Project-Customized, Concerted, and Comprehensive Lead Generation Strategies will Increase LG Success Rates: the CREATION of Leads 20</p> <p>2.5.5 Selecting the Target Defines LG Success Rates 21</p> <p>2.5.6 Lead Generation should be Complemented by Auxiliary Technologies to Characterize Hits 21</p> <p>2.5.7 Phenotypic Screens are Often Complemented by a Chemical Biology Arm 22</p> <p>2.5.8 The Lead Generation Strategy is Defined by the Budget Allocated 22</p> <p>2.5.9 Cost-Efficient but Information-Rich Lead Generation Strategies 23</p> <p>2.5.10 The Revival of Potency as the Most Important Lead Criterion? 24</p> <p>2.5.11 When has a LG Campaign Delivered Successfully? 27</p> <p>References 31</p> <p><b>Part II The Importance of Target Identification for Generating Successful Leads 35</b></p> <p><b>3 “Ligandability” of Drug Targets: Assessment of Chemical Tractability via Experimental and In Silico Approaches 37</b><br /><i>Udo Bauer and Alexander L. Breeze</i></p> <p>3.1 Introduction 37</p> <p>3.2 The Concept of Ligandability 39</p> <p>3.2.1 General Characteristics of Ligandable Targets 39</p> <p>3.3 The Intersection of Ligandability and Human Disease Target Space 40</p> <p>3.3.1 Experimental Techniques for Assessing Target Ligandability 42</p> <p>3.3.1.1 High-Throughput Screening and Subset/“Validation Set” Screening 43</p> <p>3.3.1.2 Fragment Screening 44</p> <p>3.4 Practical Examples of the Use of Fragment Screening for Ligandability Assessment 50</p> <p>3.4.1 Chemical Tractability Assessment by in silico Approaches 54</p> <p>3.4.1.1 Pocket-Finding Algorithms 54</p> <p>3.4.1.2 Discrimination Functions and Validation Sets 55</p> <p>3.4.1.3 Simulation-Based Methods for Identifying Interaction Potentials 56</p> <p>3.5 Conclusions and Outlook 56</p> <p>References 58</p> <p><b>4 Chemistry-Driven Target Identification 63</b><br /><i>Iván Cornella-Taracido, Ryan Hicks, Ola Engkvist, Adam Hendricks, Ronald Tomlinson, and M. Paola Castaldi</i></p> <p>4.1 Introduction 63</p> <p>4.2 Chemistry-Driven Target Discovery: Enabling Biology 65</p> <p>4.2.1 Biological Samples 65</p> <p>4.2.2 Cells Cultured in 2D 66</p> <p>4.2.3 Cells Cultured in 3D, Organoids, and Tissues 67</p> <p>4.2.4 Nonhuman Cells and Whole-Organism Screening 68</p> <p>4.2.5 Functional Assays and Readouts 68</p> <p>4.3 Chemistry for Target Discovery 71</p> <p>4.3.1 Screening Deck Selection 71</p> <p>4.3.2 Triaging and Prioritization of Chemical Matter 72</p> <p>4.3.3 SAR Expansion and Probe Synthesis for Target Deconvolution 73</p> <p>4.4 Small-Molecule Target Identification Techniques 75</p> <p>4.4.1 In Silico Target Deconvolution 75</p> <p>4.4.2 Biochemical Profiling 77</p> <p>4.4.3 Target Deconvolution Correlational Tools 78</p> <p>4.4.4 Subcellular Localization 79</p> <p>4.4.5 Chemical Genetics 79</p> <p>4.4.6 Affinity Chemical Proteomics 81</p> <p>4.4.7 Target Corroboration 84</p> <p>4.5 Conclusions 86</p> <p>References 89</p> <p><b>Part III Hit Generation Methods 93</b></p> <p><b>5 Lead Generation Based on Compound Collection Screening 95</b><br /><i>Dirk Weigelt and Ismet Dorange</i></p> <p>5.1 Introduction 95</p> <p>5.2 Screening of Existing Collections: the General Workflow 96</p> <p>5.2.1 High-Throughput Screening 96</p> <p>5.2.2 Medium-Throughput Screening: Selection Methods 98</p> <p>5.3 Generation of New Screening Compounds 99</p> <p>5.3.1 Collection Enhancement Programs 102</p> <p>5.3.2 Library Design and Compound Selection 102</p> <p>5.3.2.1 Number of Dimensions 103</p> <p>5.3.2.2 Enumeration and Filtering 104</p> <p>5.3.2.3 Layout 106</p> <p>5.3.3 Focus on Synthetic Feasibility 107</p> <p>5.3.3.1 Multicomponent Reactions 107</p> <p>5.3.3.2 Click Chemistry 108</p> <p>5.3.3.3 Diversity-oriented Synthesis 108</p> <p>5.3.4 Structure-driven Approaches 109</p> <p>5.3.4.1 Privileged Structures 110</p> <p>5.3.4.2 Structure-driven Approaches Toward Unchartered Territory 112</p> <p>5.3.5 Target Focus 114</p> <p>5.3.5.1 Kinases 114</p> <p>5.3.5.2 G-Protein-Coupled Receptors 115</p> <p>5.3.5.3 Ion Channels 116</p> <p>5.3.5.4 Protein–Protein Interactions 117</p> <p>5.4 Other Concepts 117</p> <p>5.4.1 Natural Products 118</p> <p>5.4.2 DNA-Encoded Libraries 119</p> <p>5.4.3 Spatially Addressed Libraries 120</p> <p>5.4.4 On-bead Screening 120</p> <p>5.4.5 Dynamic Combinatorial Chemistry 121</p> <p>5.4.6 Cocktails and Mixtures 121</p> <p>5.5 Summary and Outlook 122</p> <p>References 123</p> <p><b>6 Fragment-Based Lead Generation 133</b><br /><i>Ivan V. Efremov and Daniel A. Erlanson</i></p> <p>6.1 Introduction 133</p> <p>6.2 Screening Methods 135</p> <p>6.3 Hit Validation 137</p> <p>6.4 Ligand Efficiency and Other Metrics 138</p> <p>6.5 Hit Optimization 139</p> <p>6.6 Fragment Growing 140</p> <p>6.7 Fragment Linking 144</p> <p>6.8 Protein–Protein Interactions 147</p> <p>6.9 GPCRs 151</p> <p>6.10 Computational Approaches 152</p> <p>6.11 Conclusions 153</p> <p>References 154</p> <p><b>7 Rational Hit Generation 159</b><br /><i>Bernd Wellenzohn and Alexander Weber</i></p> <p>7.1 Introduction 159</p> <p>7.2 Lead Generation: Transition State and Substrate Analogs 161</p> <p>7.3 Hit Generation by Rational Library Design 165</p> <p>7.4 Hit Generation by Virtual Screening 167</p> <p>7.4.1 Structure-based VS in Enumerated Molecules 170</p> <p>7.4.2 Ligand-based VS in Nonenumerated Virtual Chemical Spaces 171</p> <p>7.5 Hit Generation by Scaffold Replacement Technologies 173</p> <p>7.6 Hit Generation by Chemogenomics Approaches 174</p> <p>7.7 Summary 178</p> <p>References 178</p> <p><b>8 Competitive Intelligence–based Lead Generation and Fast Follower Approaches 183</b><br /><i>Yu Jiang, Ziping Liu, Jörg Holenz, and Hua Yang</i></p> <p>8.1 Introduction 183</p> <p>8.2 Competitive Intelligence-based Approach 185</p> <p>8.2.1 Example A: A Case Study for the Hybrid Strategy 190</p> <p>8.2.2 Example C: A Case Study for the Fused Strategy 192</p> <p>8.2.3 Example C: A Case Study for the Fused Strategy 193</p> <p>8.2.4 Example D: A Case Study for the Fused Strategy 196</p> <p>8.2.5 Example E: A Case Study for the Chimera Strategy 197</p> <p>8.3 Fast Follower Approach 201</p> <p>8.3.1 Salfanilamide-based Fast Follower Approaches 202</p> <p>8.3.2 Omeprazole-based Fast Follower Approaches 203</p> <p>8.3.3 Rimonabant-based Fast Follower Approach 210</p> <p>References 214</p> <p><b>9 Selective Optimization of Side Activities: An Alternative and Promising Strategy for Lead Generation 221</b><br /><i>Norbert Handler, Andrea Wolkerstorfer, and Helmut Buschmann</i></p> <p>9.1 Introduction 221</p> <p>9.1.1 Drug Selectivity and Unwanted or Desired Side Effects 222</p> <p>9.2 Definition, Rational, and Concept of the SOSA Approach 223</p> <p>9.2.1 Multiple Ligands and Polypharmacology 224</p> <p>9.2.2 Safety and Bioavailability 225</p> <p>9.3 Drugs in Other Drugs: Drug as Fragments 225</p> <p>9.4 Drug Repositioning and Drug Repurposing 226</p> <p>9.4.1 Old Drugs 226</p> <p>9.5 The SOSA Approach and Analog Design 227</p> <p>9.6 Patentability and Interference Risk of the SOSA Approach 230</p> <p>9.6.1 Analogization, Optimization, and Isosterism 230</p> <p>9.7 Case Studies and Examples 231</p> <p>9.7.1 Sulfonamides 231</p> <p>9.7.2 Morphine Analogs 232</p> <p>9.7.3 Warfarin 232</p> <p>9.7.4 Sildenafil (Viagra) 232</p> <p>9.7.5 Thalidomide Analogs 233</p> <p>9.7.6 Bupropion 234</p> <p>9.7.7 Chlorpromazine 235</p> <p>9.7.8 Chlorothiazide 235</p> <p>9.7.9 Propranolol 235</p> <p>9.7.10 Minaprine Analogs 236</p> <p>9.7.11 Viloxazine Analogs 237</p> <p>9.7.12 Methylation in the SOSA Strategy of Drug Design 237</p> <p>9.7.13 Discovery of New Antiplasmodial Compounds 239</p> <p>9.7.14 Drugs Acting on Central Nervous System Targets as Leads for Non-CNS Targets 241</p> <p>9.7.15 Mexiletine Derivatives as Orally Bioavailable Inhibitors of Urokinase-Type Plasminogen Activator 242</p> <p>9.7.16 Amiloride Analogs as Inhibitors of the Urokinase-type Plasminogen Activator 245</p> <p>9.7.17 Flavonoids with an Oligopolysulfated Moiety: A New Class of Anticoagulant Agents 246</p> <p>9.7.18 Clioquinol 249</p> <p>9.8 Conclusions 251</p> <p>References 252</p> <p><b>10 Lead Generation for Challenging Targets 259</b><br /><i>Jinqiao Wan, Dengfeng Dou, Hongmei Song, Xian-Hui Wu, Xuemin Cheng, and Jin Li</i></p> <p>10.1 Introduction 259</p> <p>10.2 DNA-Encoded Library Technology in Lead Generation 260</p> <p>10.2.1 Background 260</p> <p>10.2.2 DNA-Recorded Synthesis-Assisted Libraries 262</p> <p>10.2.3 DNA-Templated Synthesis-Assisted Libraries 264</p> <p>10.2.4 Encoded Self-Assembling Chemical Libraries 266</p> <p>10.2.5 Summary and Perspective 267</p> <p>10.3 Stapled Peptide 276</p> <p>10.3.1 Background 276</p> <p>10.3.2 Structure, Design, and Synthesis of Stapled Peptide 278</p> <p>10.3.2.1 Stapled Peptide Structure 278</p> <p>10.3.2.2 Stapled Peptide Design 280</p> <p>10.3.2.3 Stapled Peptide Synthesis 282</p> <p>10.3.3 Stapled Peptide Solution α-Helix Conversion Measurement 283</p> <p>10.3.4 Stapled Peptide Affinity Evaluation and α-Helix Content Correlation 284</p> <p>10.3.4.1 Surface Plasmon Resonance Binding Assays 284</p> <p>10.3.4.2 Fluorescence Polarization Assay 284</p> <p>10.3.4.3 Stapled Peptide Affinity and α-Helix Content Correlation 285</p> <p>10.3.5 Stapled Peptide Permeability 286</p> <p>10.3.6 Peptide Stability Assay 288</p> <p>10.3.7 Outlook 288</p> <p>10.4 Phenotypic Screening 289</p> <p>10.4.1 Introduction 289</p> <p>10.4.2 Basics for Establishing a Phenotypic Screen 291</p> <p>10.4.2.1 Identify a “Druggable” Phenotype and the Type of Readout 291</p> <p>10.4.2.2 Assay Design 291</p> <p>10.4.2.3 Hit Selection and Secondary Assay 291</p> <p>10.4.3 Typical Phenotypic Assays 292</p> <p>10.4.3.1 Cell-Viability Assay 292</p> <p>10.4.3.2 Fluorescent Imaging Plate Reader Technology 293</p> <p>10.4.3.3 High-Content Screening 293</p> <p>10.4.4 In Vitro Phenotypic Screening 293</p> <p>10.4.4.1 Classic Phenotypic Screening 293</p> <p>10.4.4.2 Patient-Derived Stem Cell in Drug Discovery 294</p> <p>10.4.4.3 Phenotypic Screening on iPSC-Derived Disease Models 295</p> <p>10.4.4.4 High-Content Cytotoxicity Screening by iPSC-Derived Hepatocytes 296</p> <p>10.5 Summary 297</p> <p>References 298</p> <p><b>11 Collaborative Approaches to Lead Generation 307</b><br /><i>Fabrizio Giordanetto, Anna Karawajczyk, and Graham Showell</i></p> <p>11.1 Introduction 307</p> <p>11.2 Creativity 308</p> <p>11.3 Speed 308</p> <p>11.4 Risk Sharing 308</p> <p>11.5 Intellectual Property 309</p> <p>11.6 Costs 309</p> <p>11.7 Management 310</p> <p>11.8 Lilly’s Open Innovation Drug Discovery 310</p> <p>11.9 Molecular Library Program 312</p> <p>11.10 EU Openscreen 314</p> <p>11.11 European Lead Factory 315</p> <p>11.12 Medicines for Malaria Venture 317</p> <p>11.13 Open Source Malaria Project 320</p> <p>11.14 Drugs for Neglected Diseases Initiative 320</p> <p>11.15 Open Lab Foundation 321</p> <p>11.16 Scientists Against Malaria 322</p> <p>11.17 Open Source Drug Discovery 323</p> <p>11.18 TB Alliance 323</p> <p>11.19 Summary 324</p> <p>References 325</p> <p><b>Volume 68b</b></p> <p>Dedication V</p> <p>List of Contributors XXI</p> <p><b>Part IV Converting Hits to Successful Leads 329</b></p> <p><b>12 A Medicinal Chemistry Perspective on the Hit-to-Lead Phase in the Current Era of Drug Discovery 331</b><br /><i>Dean G. Brown</i></p> <p>12.1 Introduction 331</p> <p>12.2 Active to Hit Processes 333</p> <p>12.3 Target Potency: Energetics of Binding 336</p> <p>12.4 Addressing Vast Chemical Space: HtL Strategies 345</p> <p>12.5 Matched Pair Analysis 348</p> <p>12.6 The Role of Hydrophobicity and HtL 351</p> <p>12.7 Probing H-Bond Donors and Acceptors 353</p> <p>12.8 Structure Based DD in HtL 356</p> <p>12.9 Statistical Molecular Design 358</p> <p>12.10 Hit to Lead is not Lead Optimization 359</p> <p>12.11 Summary 362</p> <p>References 363</p> <p><b>13 Molecular Recognition and Its Importance for Fragment-Based Lead Generation and Hit-to-Lead 367</b><br /><i>Thorsten Nowak</i></p> <p>13.1 Introduction 367</p> <p>13.2 Brief Summary of the Main Factors that Govern Molecular Interactions 368</p> <p>13.3 Thermodynamics of Molecular Interactions and Impact on Hit Finding and Optimization 369</p> <p>13.4 Enthalpy as a Key Decision Tool in Medicinal Chemistry 371</p> <p>13.5 Importance of Enthalpic Interactions: Drivers of Selectivity and Specificity? 373</p> <p>13.6 Fragment Screening Hit Optimization: Fragment Linking 374</p> <p>13.7 Interstitial Waters and Their Usefulness: Case Studies on HSP-90 381</p> <p>13.8 Fragments to Find Hot Spots in Binding Pockets 385</p> <p>13.9 Nonclassical Hydrogen Bonds – Interactions of Halogen Atoms with Π-Systems and Carbonyl Groups: Factor Xa and Cathepsin L 386</p> <p>13.10 Binding Mode Dependency of the Experimental Conditions and Chemical Framework of Ligand 390</p> <p>13.11 Cooperativity in Binding: DAO or DAAO D-Amino Acid Oxidase 391</p> <p>References 394</p> <p><b>14 Affinity-Based Screening Methodologies and Their Application in the Hit-to-Lead Phase 401</b><br /><i>Stefan Geschwindner</i></p> <p>14.1 Introduction 401</p> <p>14.2 Nuclear Magnetic Resonance Spectroscopy 402</p> <p>14.3 Optical Biosensors: Surface Plasmon Resonance and Optical Waveguide Grating 404</p> <p>14.4 Isothermal Titration Calorimetry 407</p> <p>14.5 Thermal Shift Assay 411</p> <p>14.6 Mass Spectrometry Approaches 412</p> <p>14.7 Encoded Library Technologies 414</p> <p>14.8 Emerging Technologies: Microscale Thermophoresis and Backscattering Interferometry 417</p> <p>References 418</p> <p><b>15 Predictive Methods in Lead Generation 425</b><br /><i>Matthew D. Segall and Peter Hunt</i></p> <p>15.1 Introduction 425</p> <p>15.2 Compound Property Prediction 427</p> <p>15.3 Multiparameter Optimization: Identifying High-Quality Compounds 430</p> <p>15.3.1 Drug-like Properties 430</p> <p>15.3.2 Filters 431</p> <p>15.3.3 Desirability Functions and Probabilistic Scoring 432</p> <p>15.3.4 Pareto Optimization 435</p> <p>15.3.5 Example 436</p> <p>15.4 De Novo Design: Guiding the Exploration of Novel Chemistry 439</p> <p>15.4.1 Example Application 442</p> <p>15.5 Selection: Balancing Quality with Diversity 443</p> <p>15.6 Conclusions 445</p> <p>References 447</p> <p><b>16 Lead Quality 451</b><br /><i>J. Willem M. Nissink, Sebastien Degorce, and Ken Page</i></p> <p>16.1 Introduction 451</p> <p>16.2 Properties in Drug Design 452</p> <p>16.2.1 Primary Activity Assays 453</p> <p>16.2.2 Physicochemical Properties 453</p> <p>16.2.3 DMPK 454</p> <p>16.2.4 Safety 454</p> <p>16.2.5 Overall Profiles 456</p> <p>16.3 Optimizing Properties: Useful Rules, Guides, and Simple Metrics for Early-Stage Projects 457</p> <p>16.3.1 Rules for Potency: Ligand Efficiency Measures 457</p> <p>16.3.2 Rules for Safety 462</p> <p>16.3.3 Rules for DMPK and Mode of Administration: Early-Stage Structure-Based Profiling 464</p> <p>16.3.3.1 Simple Design Rules for Good DMPK 464</p> <p>16.3.3.2 Other DMPK Design Rules 465</p> <p>16.3.4 Multiobjective Optimization 466</p> <p>16.4 Predicted Dose to Man as a Measure of Early- and Late-Stage Lead Quality 467</p> <p>16.4.1 Introduction 467</p> <p>16.4.2 Description of Models and Data 469</p> <p>16.4.3 Data Supporting Technique 471</p> <p>16.4.3.1 Matching eD2M Doses with Normalized Observed Clinical Doses 472</p> <p>16.4.3.2 Matching Cmax Values from eD2M and Clinical Studies 472</p> <p>16.4.4 Flagging Potential Candidate Drugs Using eD2M 473</p> <p>16.4.5 Determining Properties that Drive eD2M Predictions for a Series 474</p> <p>16.5 Summary 480</p> <p>References 481</p> <p><b>Part V Hypothesis-driven Lead Optimization 487</b></p> <p><b>17 The Strategies and Politics of Successful Design, Make, Test, and Analyze (DMTA) Cycles in Lead Generation 489</b><br /><i>Steven S. Wesolowski and Dean G. Brown</i></p> <p>17.1 DMTA Cycles: Perspectives from History 490</p> <p>17.2 Test: What Assays, in What Order, and Why? 494</p> <p>17.3 Additional Advice for “Test” Component of DMTA 496</p> <p>17.4 Design: What to Make and Why? 496</p> <p>17.5 Additional Advice for “Design” Component of DMTA 500</p> <p>17.6 Make: Challenges and Strategies for Synthesis 501</p> <p>17.7 Additional Advice for the “Make” Component of DMTA 502</p> <p>17.8 Analyze: Making Sense of What’s Been Done and Formulating Sensible Plans for the Next Designs 502</p> <p>17.9 Additional Advice for “Analyze” Component of DMTA 508</p> <p>17.10 Results: Do Lead Optimization Teams Get What They Need? 508</p> <p>References 509</p> <p><b>Part VI Recent Lead Generation Success Stories 513</b></p> <p><b>18 Lead Generation Paved the Way for the Discovery of a Novel H3 Inverse Agonist Clinical Candidate 515</b><br /><i>Christophe Genicot and Laurent Provins</i></p> <p>18.1 Introduction 515</p> <p>18.2 Hit Identification 517</p> <p>18.3 Lead Generation 521</p> <p>18.3.1 Exploration of Oxazoline Substitution 523</p> <p>18.3.2 Rigidification of Propoxy Linker 531</p> <p>18.3.3 Oxazoline/Oxazole Surrogates: Lactams 533</p> <p>18.3.4 Conclusions 536</p> <p>18.4 Lead Optimization and Candidate Selection 537</p> <p>18.5 Conclusions 543</p> <p>Acknowledgments 544</p> <p>References 544</p> <p><b>19 Vorapaxar: From Lead Identification to FDA Approval 547</b><br /><i>Samuel Chackalamannil and Mariappan Chelliah</i></p> <p>19.1 Introduction 547</p> <p>19.2 Background Information on Antiplatelet Agents 549</p> <p>19.3 Thrombin Receptor (Protease-activated Receptor-1) Antagonists as a Novel Class of Antiplatelet Agents 550</p> <p>19.4 Mechanism of Thrombin Receptor Activation 550</p> <p>19.5 Preclinical Data Supporting the Antiplatelet Effect of Thrombin Receptor Antagonists 551</p> <p>19.6 Himbacine-derived Thrombin Receptor Antagonists 552</p> <p>19.6.1 Lead Identification 552</p> <p>19.6.2 Lead Generation of Himbacine-derived Thrombin Receptor Antagonist Hit 553</p> <p>19.6.2.1 Structure–Activity Relationship Studies 555</p> <p>19.6.2.2 First-Generation Thrombin Receptor Antagonists 556</p> <p>19.6.2.3 In vivo Metabolism of Himbacine Derivatives 558</p> <p>19.6.2.4 Generation of Aryl Himbacine Leads 561</p> <p>19.6.2.5 Second-Generation Leads that Incorporate Heteroatoms in the C-ring 562</p> <p>19.6.2.6 Identification of nor-seco Himbacine Lead 564</p> <p>19.6.3 Discovery of Vorapaxar (SCH 530348) 565</p> <p>19.6.3.1 Clinical Studies of Vorapaxar 567</p> <p>19.7 Conclusions 569</p> <p>Abbreviations 570</p> <p>Acknowledgments 570</p> <p>References 571</p> <p><b>20 Lead Generation Approaches Delivering Inhaled β2-Adrenoreceptor Agonist Drug Candidates 575</b><br /><i>Michael Stocks and Lilian Alcaraz</i></p> <p>20.1 Introduction 575</p> <p>20.2 Lead Generation Exercises to Discover β2AR Agonist Clinical Candidates 577</p> <p>20.3 AstraZeneca Lead Generation Exercises to Discover β2AR Agonist Clinical Candidates 587</p> <p>20.4 Summary 593</p> <p>References 593</p> <p><b>21 GPR81 HTS Case Study 597</b><br /><i>Eric Wellner and Ola Fjellström</i></p> <p>21.1 General Remarks 597</p> <p>21.2 The Target 598</p> <p>21.3 Screening Cascade 599</p> <p>21.4 Compound Selection (10 K Validation Set) 602</p> <p>21.5 HTS 606</p> <p>21.5.1 CSE 608</p> <p>21.5.2 Single-Concentration Counterscreen 614</p> <p>21.5.3 Clustering 615</p> <p>21.5.4 Cluster Expansion and Nearest Neighbours 618</p> <p>21.6 Hit Evaluation 618</p> <p>21.6.1 Potency, Efficacy, and Curves 618</p> <p>21.6.2 Binding Kinetics 621</p> <p>21.6.3 Concentration–Response Counterscreen 622</p> <p>21.6.4 Hit Assessment 622</p> <p>21.6.4.1 Size and Lipophilicity Efficiency Assessment 622</p> <p>21.6.4.2 Secondary Pharmacology Assessment 626</p> <p>21.6.5 Secondary Screening Cascade and Hit Expansion 630</p> <p>21.6.6 Biological Effect Assay 634</p> <p>21.7 Alternative Lead Generation Strategies 638</p> <p>21.7.1 Pepducins and Other Modified Peptides 641</p> <p>21.8 Conclusions 645</p> <p>References 646</p> <p><b>22 Development of Influenza Virus Sialidase Inhibitors 651</b><br /><i>Mauro Pascolutti, Robin J. Thomson, and Mark von Itzstein</i></p> <p>22.1 Introduction 651</p> <p>22.2 Targets for Anti-influenza Drug Development: Receptor Binding and Receptor Cleavage 652</p> <p>22.2.1 Targeting Receptor Binding by Haemagglutinin 654</p> <p>22.2.2 Targeting Receptor Destruction by Sialidase 655</p> <p>22.2.3 Influenza Virus Sialidase: Structure and Mechanism 656</p> <p>22.3 Development of Influenza Virus Sialidase Inhibitors 658</p> <p>22.3.1 The Development of Zanamivir: Proof of Concept and First-in-Class Sialidase Inhibitor Drug 659</p> <p>22.3.1.1 Template Selection 659</p> <p>22.3.1.2 Structure-based Inhibitor Design 662</p> <p>22.3.1.3 X-Ray Crystallographic Confirmation of Inhibitor Binding Mode 665</p> <p>22.3.1.4 Selectivity for Influenza Virus Sialidase over Human Sialidases 666</p> <p>22.3.1.5 Efficacy against Virus Replication 667</p> <p>22.3.1.6 Mode of Administration of the Highly Polar Drug 667</p> <p>22.3.1.7 Modifying the Presentation of Zanamivir: Prodrugs and Multivalency 668</p> <p>22.3.2 Sialidase Inhibitor Development on Noncarbohydrate Scaffolds 671</p> <p>22.3.2.1 A Sialidase Inhibitor Based on a Cyclohexene Scaffold: The Development of Oseltamivir 671</p> <p>22.3.2.2 A Sialidase Inhibitor Based on a Cyclopentane Scaffold: The Development of Peramivir 673</p> <p>22.3.3 Monitoring Resistance to Influenza Virus Sialidase Inhibitors 675</p> <p>22.4 Summary and Future Directions 676</p> <p>References 676</p> <p><b>23 The Discovery of Cathepsin A Inhibitors: A Project-Adapted Fragment Approach Based on HTS Results 687</b><br /><i>Sven Ruf, Christian Buning, Herman Schreuder, Wolfgang Linz, Dominik Linz, Hartmut Rütten, Georg Horstick, Markus Kohlmann, Katja Kroll, Klaus Wirth, and Thorsten Sadowski</i></p> <p>23.1 General Background 687</p> <p>23.2 Cathepsin A enzyme 687</p> <p>23.2.1 Structural Biology and Catalytic Mechanism 687</p> <p>23.2.2 Structural and Catalytic Functions of CatA 689</p> <p>23.2.3 Tissue Distribution and Substrates 689</p> <p>23.2.4 Natural Products and Synthetic Peptides as Inhibitors of CatA 690</p> <p>23.3 CatA and the Link to Cardiovascular Disease 691</p> <p>23.4 Lead Discovery 692</p> <p>23.4.1 High-Throughput Screening and Data Analysis 692</p> <p>23.4.2 Evaluation of Hit Series 693</p> <p>23.4.2.1 Covalent Inhibitor Series 693</p> <p>23.4.2.2 Malonamide Series 697</p> <p>23.4.2.3 Pyrazolone Hit Series 698</p> <p>23.4.3 Explorative Chemistry Delivers a Novel Lead Structure 699</p> <p>23.4.3.1 Crystal Structure of 9b Bound to CatA 705</p> <p>23.5 Lead Optimization 705</p> <p>23.6 Toward an in vivo Proof of Concept 711</p> <p>23.7 Summary and Conclusions 713</p> <p>References 714</p> <p><b>24 Lead Structure Discovery for Neglected Diseases: Product Development Partnerships Driving Drug Discovery 717</b><br /><i>Jeremy N. Burrows and Takushi Kaneko</i></p> <p>24.1 Introduction 717</p> <p>24.2 Malaria and Medicines for Malaria Venture 719</p> <p>24.3 Malaria Lead Generation Strategy 719</p> <p>24.4 Hit Identification Strategies 722</p> <p>24.5 Optimization of a Marketed Antimalarial Chemotype 723</p> <p>24.6 Target-Based Approaches 723</p> <p>24.7 Asexual Blood-Stage Phenotypic Screening 724</p> <p>24.8 Whole-Cell Screening: Results 725</p> <p>24.9 Repositioning of Clinical Candidates Developed for Other Indications 726</p> <p>24.10 Case Studies 727</p> <p>24.10.1 Dihydroorotate Dehydrogenase (DHODH) 727</p> <p>24.10.2 Whole-Cell Screening 728</p> <p>24.11 Screening for Malaria Eradication 729</p> <p>24.12 Tuberculosis and the Global Alliance for Tuberculosis Drug Development (TB Alliance) 729</p> <p>24.13 Target Product Profiles 730</p> <p>24.14 TB Alliance’s Mission 730</p> <p>24.15 Hit Generation Strategies for TB 732</p> <p>24.16 Examples of Phenotypic Screens 733</p> <p>24.17 Conclusions 741</p> <p>References 741</p> <p><b>25 A Fragmentation Enumeration Approach to Generating Novel Drug Leads 747</b><br /><i>Pravin S. Iyer and Manoranjan Panda</i></p> <p>25.1 Introduction 747</p> <p>25.2 Principle 748</p> <p>25.3 Research Methodology 748</p> <p>25.3.1 Fragmentation 749</p> <p>25.3.1.1 Origin of Parent Molecules 749</p> <p>25.3.1.2 Cores and Daughters 749</p> <p>25.3.1.3 Nonflat Cores 751</p> <p>25.3.2 Intelligent Recombination and Enumeration 754</p> <p>25.4 Evaluation 754</p> <p>25.4.1 Preliminary Experimental Evaluation 755</p> <p>25.4.2 In Silico Evaluation 755</p> <p>25.4.3 Virtual Screening Using Enzyme–Ligand Docking 756</p> <p>25.5 Summary 758</p> <p>References 759</p> <p>Index 761</p>
"it is certainly the most comprehensive and up-to-date resource currently available on the topic"......."is an excellent resource for any scientist working in lead generation"......."This is a tribute to rational<br />drug discovery, which combined with very thorough up-to-date literature references and emphasis on emerging technologies, makes it a book we would readily suggest taking a look at" <b>(Dr. Robert Webster, Dr. Nuria Ortega Hernandez Bayer Pharma AG, ChemMedChem, July 2017)</b>
<b>Joerg Holenz</b> 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.

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