Polypharmacology in Drug Discovery E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 963

Veröffentlichungsjahr: 2012

Beschreibung

An essential outline of the main facets of polypharmacology in drug discovery research Extending drug discovery opportunities beyond the "one drug, one target" philosophy, a polypharmacological approach to the treatment of complex diseases is emerging as a hot topic in both industry and academic research. Polypharmacology in Drug Discovery presents an overview of the various facets of polypharmacology and how it can be applied as an innovative concept for developing medicines for treating bacterial infections, epilepsy, cancer, psychiatric disorders, and more. Filled with a collection of instructive case studies that reinforce the material and illuminate the subject, this practical guide: * Covers the two-sided nature of polypharmacology--its contribution to adverse drug reactions and its benefit in certain therapeutic drug classes * Addresses the important topic of polypharmacology in drug discovery, a subject that has not been thoroughly covered outside of scattered journal articles * Overviews state-of-the-art approaches and developments to help readers understand concepts and issues related to polypharmacology * Fosters interdisciplinary drug discovery research by embracing computational, synthetic, in vitro and in vivo pharmacological and clinical aspects of polypharmacology A clear road map for helping readers successfully navigate around the problems involved with promiscuous ligands and targets, Polypharmacology in Drug Discovery provides real examples, in-depth explanations and discussions, and detailed reviews and opinions to spark inspiration for new drug discovery projects.

Leseprobe

Contents

Cover

Title Page

Copyright

Contributors

Preface

Introduction: The Case for Polypharmacology

Part A: Polypharmacology: A Safety Concern in Drug Discovery

Chapter 1: The Relevance of Off-Target Polypharmacology

Chapter 2: Screening for Safety-Relevant Off-Target Activities

2.1 Introduction

2.2 General Aspects

2.3 Selection of Off Targets

2.4 In Silico Approaches to (Off-Target) Profiling

2.5 Summary and Conclusions

2.6 Acknowledgment

References

Chapter 3: Pharmacological Promiscuity and Molecular Properties

3.1 Introduction: Pharmacological Promiscuity In The History Of Drug Discovery

3.2 Lipophilicity

3.3 Molecular Weight

3.4 Ionization State

3.5 Other Molecular Descriptors and Structural Motifs

3.6 Implications for Drug Discovery

References

Chapter 4: Kinases as Antitargets in Genotoxicity

4.1 Protein Kinases and Inhibitor-Binding Sites

4.2 Cyclin-Dependent Kinases Controlling Unregulated Cell Proliferation

4.3 Mitotic Kinases as Guardians Protecting Cells from Aberrant Chromosome Segregation

4.4 Conclusion

References

Chapter 5: Activity at Cardiovascular Ion Channels: A Key Issue for Drug Discovery

5.1 Introduction

5.2 Screening Methods

5.3 Structural Insights into the Interaction Between Drugs and Cardiovascular Ion Channels

5.4 Medicinal Chemistry Approaches

5.5 Conclusion

References

Chapter 6: Prediction of Side Effects Based on Fingerprint Profiling and Data Mining

6.1 Introduction to BioPrint

6.2 The Pharmacological Fingerprint

6.3 Antidepressant Example

6.4 Profile Similarity at Nontherapeutic Targets

6.5 Interpreting the Polypharmacology Profile

6.6 Methods

6.7 Patterns of Activity

6.8 Integrating Function Profile Data with Traditional Pharmacological Binding Data

6.9 Analysis of the Antifungal Tioconazole

6.10 Conclusions

References

Part B: Polypharmacology: An Opportunity for Drug Discovery

Chapter 7: Polypharmacological Drugs: “Magic Shotguns” for Psychiatric Diseases

7.1 Introduction

7.2 Definition

7.3 Discovery and Extent of Promiscuity Among Psychiatric Drugs

7.4 Why are so many psychiatric drugs promiscuous?

7.5 Conclusions

References

Chapter 8: Polypharmacological Kinase Inhibitors: New Hopes for Cancer Therapy

8.1 Targeted Therapies: A New Era in The Treatment of Cancer

8.2 Single-Targeted Therapy

8.3 From Single- to MultiTargeted Drugs in Cancer Therapy

8.4 Polypharmacology Kinase Inhibitors in Clinical Practice and Under Development

References

Chapter 9: Polypharmacology as an Emerging Trend in Antibacterial Discovery

9.1 Introduction

9.2 Classical Antibacterial Polypharmacology

9.3 New Approaches to Multitargeted Single Pharmacophores

9.4 Synthetic Lethals

9.5 Hybrid Molecules

9.6 Conclusions

References

Chapter 10: A “Magic Shotgun” Perspective on Anticonvulsant Mechanisms

10.1 Introduction

10.2 Anticonvulsant Mechanism

10.3 Defining Promiscuity

10.4 Lessons for Promiscuity

10.5 Use of Anticonvulsants in Disorders other than Epilepsy

10.6 Experimental and Theoretical Support for a “Magic Shotgun” Approach

10.7 Current Multitarget Strategies

10.8 Practical Considerations

10.9 Conclusion

Acknowledgments

References

Chapter 11: Selective Optimization of Side Activities (SOSA): A Promising Way for Drug Discovery

11.1 Introduction

11.2 Definition and Principle

11.3 Rationale of SOSA

11.4 Establishing the SOSA Approach

11.5 A Successful Example of the SOSA Approach

11.6 Other Examples of SOSA Switches

11.7 Discussion

11.8 Computer-Assisted Design Using Pharmacophores

11.9 Conclusions

References

Part C: Selected Approaches to Polypharmacological Drug Discovery

Chapter 12: Selective Multitargeted Drugs

12.1 Introduction

12.2 Lead Generation

12.3 Lead Optimization

12.4 Case Studies

12.5 Summary

References

Chapter 13: Computational Multitarget Drug Discovery

13.1 Introduction

13.2 The Pharmacological Hunt of Yesteryear

13.3 Established Technological Advancements

13.4 Computational Drug Discovery

13.5 More Recent Technical Improvements

13.6 Emerging Concepts

13.7 Summary

PostScript

References

Chapter 14: Behavior-Based Screening as an Approach to Polypharmacological Ligands

14.1 The Challenges of CNS Drug Discovery

14.2 In Vivo High-Throughput Screening

14.3 Screening Libraries of Compounds

14.4 Relationship between Molecular Properties and In Vivo CNS Activity

14.5 Following Screening Hits in Secondary Assays

14.6 Potential Therapeutic Value of Dual-Adenosine Compounds

14.7 Summary

References

Chapter 15: Multicomponent Therapeutics

15.1 Introduction

15.2 Why Drug Synergies are Statistically More Context-Dependent

15.3 How a Synergistic Mechanism Can Lead to Therapeutic Selectivity

15.4 Discussion

References

Part D: Case Studies

Chapter 16: Discovery of Sunitinib as a Multitarget Treatment of Cancer

16.1 A Brief Introduction to Tumor Angiogenesis

16.2 Discovery of Sunitinib from Drug Design to First Evidence of Clinical Activity

16.3 Pharmacology of Sunitinib

16.4 Safety of Sunitinib

16.5 Activity of Sunitinib

16.6 Surrogate Imaging Techniques to Capture Vascular Changes

16.7 Surrogate Biomarkers

16.8 Conclusion

References

Chapter 17: Antipsychotics

17.1 Definition and Diagnosis of Schizophrenia

17.2 Etiology and Pathophysiology of Schizophrenia

17.3 Epidemiology

17.4 Medical Practice and Treatment Options

17.5 Case Studies

17.6 CATIE

17.7 Conclusions

References

Chapter 18: Triple-Uptake Inhibitors (Broad-Spectrum Antidepressants)

18.1 Introduction

18.2 The Rationale for Developing Triple-Uptake Inhibitors as Antidepressants

18.3 Preclinical Data

18.4 Clinical Data

18.5 Concluding Remarks

Postscript

References

Chapter 19: Therapeutic Potential of Small Molecules Modulating the Cyclooxygenase–5-Lipoxygenase Pathway

19.1 Introduction

19.2 Targets of the Eicosanoid Pathway

19.3 Rationale for Development of Dual Inhibitors of the Cyclooxygenase–5-Lipoxygenase Pathway

19.4 Dual Inhibitors of the Cyclooxygenase–5-Lipoxygenase Pathway

19.5 Development of Licofelone

19.6 Conclusions

References

Chapter 20: Drug Research Leading to Imatinib and Beyond to Nilotinib

20.1 Introduction

20.2 Historical Background

20.3 BCR-ABL1 as the Molecular Target for CML Therapy

20.4 Conclusion

References

Chapter 21: Towards Antimalarial Hybrid Drugs

21.1 Introduction

21.2 The History of Malaria Treatment

21.3 Use of Artemisinin and Its Derivatives

21.4 The Search for Hybrid Antimalarials

21.5 Conclusion

Acknowledgments

References

Chapter 22: Multitargeted Drugs for Treatment of Alzheimer's Disease

22.1 Introduction

22.2 Case studies

22.3 Conclusions and Perspectives

References

Chapter 23: Carbonic Anhydrases: Off Targets, Add-on Activities, or Emerging Novel Targets?

23.1 Introduction

23.2 Carbonic Anhydrase Inhibition

23.3 Topiramate and Zonisamide, Antiepileptics with Potent Antiobesity Action

23.4 Sulfonamide Coxibs with Antitumor Activity Due to CA IX/XII Inhibition

23.5 Sulfamates with Steroid Sulfatase and Carbonic Anhydrase Inhibitory Action as Anticancer Agents in Clinical Development

23.6 Lacosamide, an Antiepileptic with a Strange Binding Mode to CA ISOFORMS

23.7 The Protein Tyrosine Kinase Inhibitors Imatinib and Nilotinib as Strong Inhibitors of Several Mammalian CA Isoforms

23.8 Conclusions

Acknowledgments

References

Index

Colour Plates

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Library of Congress Cataloging-in-Publication Data:

Polypharmacology in drug discovery / edited by Jens-Uwe Peters

p. cm.

Includes bibliographical references and index.

ISBN 978-0-470-59090-4 (cloth)

Contributors

Wolfgang Albrecht, c-a-i-r Biosciences GmbH, Paul-Ehrlich-Strasse 15, 72076 Tübingen, Germany ([email protected])

Vadim Alexandrov, Psychogenics, Tarrytown, NY 10591

Kamal Azzaoui, Novartis Institutes for BioMedical Research Inc., Fabrikstrasse, Basel, Switzerland ([email protected])

Ian M. Bell, Department of Medicinal Chemistry, Merck Research Laboratories, Merck & Co., PO Box 4, West Point, PA 19486 ([email protected])

Brady Bernard, Institute for Systems Biology, 401 Terry Ave N, Seattle, WA 98109 ([email protected])

Matt Bianchi, Neurology Department, Massachusetts General Hospital, 55 Fruit Street, Wang Ambulatory, Boston, MA 02114 ([email protected])

Bertrand Billemont, Service Inter-Hospitalier de Cancérologie, Laboratoire de Pharmacobiologie des Anticancereux (RayLab), U 728 Inserm Université Paris VII, Hôpital Beaujon, 92110 Clichy, France ([email protected])

Mark T. Bilodeau, Department of Medicinal Chemistry, Merck Research Laboratories, Merck & Co., PO Box 4, West Point, PA 19486 ([email protected])

Maria Laura Bolognesi, Department of Pharmaceutical Sciences, University of Bologna, Via Belmeloro 6, I-40126 Bologna, Italy ([email protected])

Alexis A. Borisy, Third Rock Ventures, 29 Newbury Street, Boston, MA 02116 ([email protected])

Dani Brunner, Psychogenics, Tarrytown, NY 10591 ([email protected])

Barbara Caldarone, Psychogenics, Tarrytown, NY 10591

Bruce D. Car, Bristol-Myers Squibb Co., Princeton, NJ 08543 ([email protected])

Andrea Cavalli, Department of Pharmaceutical Sciences, University of Bologna, Via Belmeloro 6, I-40126 Bologna, Italy and Department of Drug Discovery and Development, Italian Institute of Technology, Via Morego 30, I-16163 Genoa, Italy ([email protected])

Jayaraman Chandrasekhar, Psychogenics, Tarrytown, NY 10591

Kathy Chuang, Neurology Department, Massachusetts General Hospital, 55 Fruit Street, Wang Ambulatory, Boston, MA 02114 ([email protected])

Camelia Colichi, Service Inter-Hospitalier de Cancérologie, Laboratoire de Pharmacobiologie des Anticancereux (RayLab), U 728 Inserm Université Paris VII, Hôpital Louis Mourier, 92701 Colombes, France ([email protected])

Catherine Delbaldo, Service Inter-Hospitalier de Cancérologie, Laboratoire de Pharmacobiologie des Anticancereux (RayLab), U 728 Inserm Université Paris VII, Hôpital Beaujon, 92110 Clichy, France ([email protected])

Chantal Dreyer, Service Inter-Hospitalier de Cancérologie, Laboratoire de Pharmacobiologie des Anticancereux (RayLab), U 728 Inserm Université Paris VII, Hôpital Beaujon, 92110 Clichy, France ([email protected])

Sandrine Faivre, Service Inter-Hospitalier de Cancérologie, Laboratoire de Pharmacobiologie des Anticancereux (RayLab), U 728 Inserm Université Paris VII, Hôpital Beaujon, 92110 Clichy, France ([email protected])

Jacques Hamon, Novartis Institutes for BioMedical Research Inc., Fabrikstrasse, Basel, Switzerland ([email protected])

Taleen Hanania, Psychogenics, Tarrytown, NY 10591

Andrew L. Hopkins, Department of Biological Chemistry and Drug Discovery, College of Life Sciences, University of Dundee, Dundee, DD1 5EH, United Kingdom ([email protected])

Jeremy A. Horst, Department of Orofacial Sciences, University of California San Francisco, 513 Parnassus Avenue, San Francisco, CA 94122 ([email protected])

Stephan Kirchner, F. Hoffmann-La Roche Ltd., Building 73/207B, CH-4070 Basel, Switzerland ([email protected])

Wesley K. Kroeze, Department of Pharmacology, University of North Carolina, Chapel Hill, NC 27514 ([email protected])

Armando A. Lagrutta, Department of Safety Assessment, Merck Research Laboratories, Merck & Co., PO Box 4, West Point, PA 19486 ([email protected])

Thierry Langer, Prestwick Chemical, Boulevard Gonthier d'Andernach, Parc d'Innovation Illkirch-Graffenstaden, 67400 Illkirch, France ([email protected])

Stefan Laufer, Institute of Pharmacy, University of Tübingen, Tübingen, Germany ([email protected])

Adrian Laurenzi, Rosen Building, University of Washington, 960 Republican, Seattle, WA 98109 ([email protected])

Joseph Lehár, Department of Bioinformatics, Boston University, 44 Cummington Street, Boston, MA 02215 ([email protected])

David Lowe, Psychogenics, Tarrytown, NY 10591

Paul W. Manley, Oncology Department, Novartis Institutes for BioMedical Research, Basel, Switzerland ([email protected])

Bernard Meunier, Palumed, 3 Rue de l'Industrie, 31320 Castanet-Tolosan, France ([email protected])

Jacques Migeon, Cerep Inc., 15318 NE 95th Street, Redmond, WA 98052 ([email protected])

Dmitri Mikhailov, Novartis Institutes for BioMedical Research, 250 Massachusetts Avenue, Cambridge, MA 02139 ([email protected])

Richard Morphy, Medicinal Chemistry Department, MSD Newhouse, Lanarkshire, ML1 5SH, United Kingdom ([email protected])

Jens-Uwe Peters, F. Hoffmann-LaRoche Ltd., Pharmaceuticals Division, Discovery Chemistry, Building/Room 92/3.64C, CH-4070 Basel, Switzerland ([email protected])

Annalisa Petrelli, Institute for Cancer Research and Treatment, Division of Molecular Oncology, University of Turin Medical School, Strada Provinciale 142, 10060 Candiolo, Italy ([email protected])

Eric Raymond, Service Inter-Hospitalier de Cancérologie Beaujon-Bichat, Laboratoire de Pharmacobiologie des Anticancereux (RayLab), U 728 Inserm Université Paris VII, Hôpital Beaujon, 100 Boulevard du Général Leclerc, 92118 Clichy, France ([email protected])

Claus Riemer, F. Hoffmann-LaRoche Ltd., Pharmaceuticals Division, Discovery Chemistry, Building/Room 92/3.10C, CH-4070 Basel, Switzerland ([email protected])

Bryan L. Roth, Department of Pharmacology, University of North Carolina and Department of Psychiatry and Lineberger Cancer Center, School of Medicine, Division of Medicinal Chemistry, School of Pharmacy, and National Institute of Mental Health Psychoactive Drug Screening Program, University of North Carolina, Chapel Hill, NC 27514 ([email protected])

Marie-Paule Sablin, Service Inter-Hospitalier de Cancérologie, Laboratoire de Pharmacobiologie des Anticancereux (RayLab), U 728 Inserm Université Paris VII, Hôpital Beaujon, 92110 Clichy, France ([email protected])

Ram Samudrala, Rosen Building, University of Washington, 960 Republican, Seattle, WA 98109 ([email protected])

Jeff Schneider, Psychogenics, Tarrytown, NY 10591

Lynn L. Silver, LL Silver Consulting, LLC, Springfield, NJ 07081 ([email protected])

Phil Skolnick, National Institute on Drug Abuse, National Institutes of Health, Division of Pharmacotherapies and Medical Consequences of Drug Abuse, Bethesda, MD 20892 ([email protected])

Claudiu T. Supuran, Dipartimento di Chimica, Laboratorio di Chimica Bioinorganica, University of Florence, Via della Lastruccia, 3, Polo Scientifico, 50019—Sesto Fiorentino (Firenze), Italy ([email protected])

Laszlo Urban, Novartis Institutes for BioMedical Research, 250 Massachusetts Avenue, Cambridge, MA 02139 ([email protected])

Camille Georges Wermuth, Prestwick Chemical, Boulevard Gonthier d'Andernach, Parc d'Innovation Illkirch-Graffenstaden, 67400 Illkirch, France ([email protected])

Steven Whitebread, Novartis Institutes for BioMedical Research, 250 Massachusetts Avenue, Cambridge, MA 02139 ([email protected])

Grant R. Zimmermann, Zalicus Incorporated, 245 First Street, Cambridge, MA 02142 ([email protected])

Jürg Zimmermann, Oncology Department, Novartis Institutes for BioMedical Research, Basel, Switzerland ([email protected])

Preface

Polypharmacology, the activity of compounds at multiple targets, has been gaining increasing attention since the 1990s, and is currently a hot topic in industrial drug discovery, as well as in academia. The 1990s witnessed the withdrawal of several drugs due to severe adverse effects, which led to permanent injury or deaths, with multi-billion-dollar legal damages. Some of these adverse effects have been linked to unintended interactions with specific off-targets, namely, the serotonin 5HT2B receptor for fenfluramine; the cardiac hERG channel for astemizole, terfenadine, and grepafloxacin; and the M2 receptor for rapacuronium. During this time, large screening panels were established by drug discovery and contract research organizations, which made it possible to recognize a wide range of off-target activities during the discovery process. As a consequence, more recent research has focused on identifying exquisitely selective drugs, with an expectation to avoid adverse drug reactions (ADRs), to improve compliance, and to gain a competitive advantage over less selective drugs.

On the other hand, the “one drug–one target” paradigm has been increasingly challenged in recent years. Not only has it been associated with a productivity decline throughout the pharmaceutical industry; it has also been increasingly being recognized that the therapy for polygenic diseases benefits more from a polypharmacological approach, which modulates a network of disease-related targets, rather than “switching” a single target on or off. For instance, despite a long quest for selective drugs, all clinically established antipsychotics today are polypharmacological drugs, with the gold standard clozapine having nanomolar activities at more than 25 targets. Polypharmacological therapies are often superior in the prevention of drug resistance, which is a major issue in the treatment of infections and cancer. In some disease areas, such as inflammatory diseases, the parallel inhibition of redundant disease-relevant pathways may be an attractive strategy for pharmacological intervention. In many instances, the inhibition of several targets may have synergistic therapeutic effects and may thus lead to more efficacious drugs. Additionally, polypharmacological drug discovery provides an opportunity to diversify research, to obtain drug candidates with unique pharmacological profiles, and to avoid a heavy focus on single targets that are often pursued across the whole industry at the same time.

Moreover, the idea that highly selective drugs are inherently safer and better tolerated than multitargeted drugs has been questioned. Rofecoxib may be a point in case; this drug, as well as other “coxibs,” was designed to more selective, and thus to be safer, than older antiinflammatory drugs such as ibuprofen. Rofecoxib was, however, found to increase the risk for cardiovascular events such as myocardial infarction and stroke. These cardiovascular risks are believed to be the result of rofecoxib's selectivity for one cyclooxygenase isoform, and have led to the withdrawal of this multi-billion-dollar drug in 2004. Another example are the selective serotonin reuptake inhibitiors (SSRIs) and serotonin / norepinephrine reuptake inhibitiors (SNRIs); although they are considered to be very safe antidepressants, they have a high incidence of unpleasant side effects, which contribute to a high discontinuation rate. These side effects, such as disrupted sleep, sexual dysfunction, and acute nausea and anxiety, are thought to be alleviated by intervention at additional targets. Consequently, several ongoing research programs aim to combine reuptake inhibition with, for example, antagonism at certain serotonin receptors for an improved tolerability. As a more general concept, it has been argued that polypharmacological drugs can even have a safety advantage, because the modulation of target networks, without permanent, full blockade or activation of a single target, may reduce target-related adverse effects, or may lead to lower efficacious doses.

Thus, there are two sides of the polypharmacology coin: (1) unwanted off-target activities may lead to adverse drug reactions and need to be avoided, while (2) polypharmacological drugs with multiple activities across a disease-relevant target class, such as G-protein-coupled receptors (GPCRs), ion channels, or kinases represent opportunities for improved therapies, as illustrated by the approvals of asenapine (2009), dronedarone (2009), and sunitinib (2006), respectively. Both of these sides will be discussed in this book. For an easy orientation according to the reader's background and interests, the book is divided in four parts:

Part A. Unintended activities at “antitargets” are typically discovered late in the drug discovery process, and have been a reason for late-stage failures, or at least a major hurdle in late lead optimization. The first part of the book discusses concepts and tools that help to recognize, interpret, and address such “antitarget” liabilities early in the drug discovery process, and thus to reduce costly late-stage attrition. Part A opens with an introduction to the relevance of polypharmacology for the safety of drugs, illustrated with salient cases of drugs and drug candidates with off-target-related toxicity. This is followed by an insightful guide to why, when, and how to screen for off-target activities, and how to predict and mitigate potential ADRs. The avoidance of promiscuity-related molecular properties as a strategy to reduce the risk for promiscuity is discussed in the third chapter. Numerous important antitargets will be introduced in these first three chapters, with a focus on GPCR targets. Two other classes of frequently encountered antitargets, kinases and cardiac ion channels, are discussed next in dedicated chapters. Part A concludes with a chapter on data mining and pharmacological “fingerprint” profiling, which allows for the prediction of otherwise nonobvious ADRs. All this is supported by useful reference information, such as lists of off-targets associated with potential ADRs, frequently hit off-targets, and practical examples of lead optimization.

Part B. The productivity of the drug discovery industry as a whole has declined since the 1990s, with only 20 new chemical entities per year reaching the market, despite ever-increasing research budgets. New discovery paradigms are therefore necessary to deviate from established research strategies, and to address those unmet medical needs that do not succumb to the ubiquitous “small molecule–single target protein” approach. Multitargeted, or polypharmacological, drug discovery may present opportunities where conventional approaches have been failing, especially for the treatment of diseases with multiple pathogenic factors, and diseases where resistance poses an important problem. Part B highlights four such disease areas: psychiatric diseases, cancer, bacterial infections, and epilepsy. Although the introductory chapter is dedicated to psychiatric drugs, the concepts discussed are instructive and generally applicable. In contrast to the antischizophrenia drugs, which were originally discovered serendipitously without knowledge of their polypharmacological nature, more recently approved kinase inhibitors for the treatment of cancer were developed with the knowledge of their polypharmacology, or were even deliberately designed to be polypharmacological, as outlined in the second chapter. The third chapter shows that most clinically established antibiotics rely on the inhibition of several targets, or targets encoded by multiple genes. In contrast, targets encoded by single genes, such as those obtained from bacterial genomes, have not led to novel antibacterials, or are associated with rapid resistance mutations. The fourth chapter shows how antiepilepsy drugs often enhance or inhibit multiple ligand- or voltage-gated ion channels, and proposes a strategy for the discovery of novel, multitargeted antiepilesy therapies. The final chapter of the “opportunity” part of the book is not related to a disease area, but rather highlights an approach to lead finding that exploits the polypharmacology of existing drugs: the selective optimization of side activities (SOSA). This approach has been historically very successful, but has been neglected in more recent years in favor of high-throughput screening. The chapter shows how this concept can be revived and complemented with modern in silico methods. As Sir James Black states: “The most fruitful basis for the discovery of a new drug is to start with an old drug.”

Part C. Most of today's “multitargeted” drug discovery programs seem to have originated from the serendipitous discovery of dual, and sometimes multiple, ligands of often related disease-relevant targets. Apart from such obvious opportunities, multitargeted drug discovery is often perceived as not very feasible by industrial researchers, because of the more difficult lead finding, and the increased complexity of lead optimization. To illustrate how multitargeted drug discovery can be put into practice, a number of selected approaches are presented in Part C. The first chapter discusses how starting points for multitargeted drug discovery programs may be obtained either by screening or rational framework combination, and how such compounds can be optimized. This is illustrated with many examples. The in silico approaches for multitarget screening can be employed to find multitargeted drugs or repurposing opportunities for existing drugs. This is discussed in the second chapter, with a focus on the 2010 NIH Director's Pioneer Award–winning CANDO method. This chapter provides also a detailed introduction to in silico screening in general, and will certainly attract the interest of in silico experts and nonspecialists alike. The third chapter introduces an intriguing method of high-throughput in vivo screening, in which a large number of behavioral readouts are automatically recognized, processed, and compared with a database of behavioral signatures of central nervous system (CNS)-active drugs. Such methods may constitute a modern version of the physiologically based screening paradigm that was the mainstay of the golden era of drug discovery. Many other possibilities are perhaps more obvious and do not warrant a detailed discussion. For instance, the mining of proprietary high-throughput screening (HTS) or safety panel data, or commercial or public pharmacological databases may be a rich source of multitargeted leads as starting points for discovery projects. Also, the “anticonvulsants” chapter of Part B proposes a generally applicable screening strategy, where novel multitargeted leads are sought to mimic the profile of successful drugs. Finally, Part C is rounded off with an introduction to multicomponent therapeutics, and shows how combinations of drugs can be selectively synergistic for therapeutic versus adverse effects, because the drug targets of the components are expressed together only in the tissue that is responsible for the therapeutic effect.

Part D. The last part is a collection of various instructive case studies. Most of the chapters in this part are dedicated to the discovery of polypharmacological or specifically multitargeted drugs, ranging from the highly promiscuous anticancer drug sunitinib and antipsychotics over broad-spectrum antidepressants to the dual-acting drug candidate licofelone for inflammatory diseases. The achievement of (reasonable) selectivity in the kinase field, and activity across mutant targets, is discussed in the imatinib case study. An untypical type of dual activity is displayed by the experimental drug PA1103, which is able to inhibit the polymerization of heme, as well as to alkylate heme, both validated concepts for the treatment of malaria. The penultimate chapter discusses multitargeted approaches to the treatment of Alzheimer's disease, and specific clinical and preclinical compounds. A final chapter is dedicated to the (off-target) activities of established drugs at carbonic anhydrases; this chapter illustrates the potential of target discovery, drug repurposing and the discovery of new drugs based on the polypharmacology of existing pharmaceuticals. Throughout Part D, many authors express their personal views on the future of polypharmacological drug discovery. These views, ranging from slight skepticism to enthusiasm, may provide the reader with a balanced and realistic impression of the promises and challenges of polypharmacological drug discovery.

This book is intended as a practical guide for drug hunters to successfully navigate around the dangers of promiscuous ligands and targets, as well as a source of inspiration for new polypharmacological drug discovery projects. However, this collection of reviews, opinions, and case studies is by no means an exhaustive treatment of all possible facets of polypharmacology. For instance, drug–drug interactions are not treated; although formally a polypharmacology issue, this is usually regarded as DMPK-related, and several excellent books cover this important topic. Similarly, pleiotropic effects through interaction with single targets, the achievement of selectivity across related targets or within target classes, or the contribution of active metabolites to the pharmacological spectra of drugs may be regarded as “polypharmacology topics,” but were considered to be beyond scope of this text.

I am very grateful to the contributing authors, who invested their time and expertise in this book. Also, I would like to thank Jonathan Rose at Wiley for proposing this book, and for his continuous advice and support throughout this project.

Note: Color versions of select figures are available at ftp://ftp.wiley.com/public/sci_tech_med/polypharmacology.

Jens-Uwe Peters

Basel, Switzerland

November 2011

Introduction: The Case for Polypharmacology

Andrew L. Hopkins

Should a drug be selective or promiscuous? The conventional goal of medicinal chemistry is to explore the structure–activity landscape to optimize the selectivity of a compound for a chosen drug target, over all others. Increasing the selectivity of a drug for one target over all others can lead to a reduction in safety liabilities. Designing drugs toward single-target profiles has been the dominant philosophy in drug design since the concept of chemoreceptors merged with molecular biology. Indeed, understanding the so-called off-target activities of a drug by prediction and experiment, and minimizing these is an important aspect of exploiting knowledge of a drug's promiscuity. More recent analysis of the physicochemical properties of failed and successful drug candidates have highlighted the relationships between target promiscuity, toxicity, and lipophilicity [1,2]. Indeed, promiscuous drugs are often labeled “dirty” drugs [3]. However, since the 2000s the assumption of the desirability of single drug target mechanisms has began to be questioned [4–6]. In certain circumstances, it may be advantageous for a drug to act on multiple drug targets, deliberately and specifically rather than be too selective.

This book explores the many different aspects of the concept of polypharmacology. Polypharmacology can be defined as the modulation of several drug targets to achieve a desired therapeutic effect. Polypharmacology stands in contrast to the dominant paradigm in current drug discovery of selectively targeting a single type of drug target. Recently there has been a growing interest in the concept of polypharmacology. Before proceeding to summarize the arguments for the importance of perturbing multiple drug targets, let's consider the concept of a drug target more generally. The concept of a drug target is as fundamental to modern pharmacology as the concept of the gene is to molecular biology. The transformation of the concept of the gene from units of phenotypic inheritance to individual protein-coding units coincides with the emergence of the concept of specific chemoreceptors as the targets for drugs. The concept of the gene transformed from the Mendalian unit of phenotypic inheritance [7] to units of protein coding, culminating in the Beadle–Tatum formation of the “one gene, one enzyme” model of 1941 [8], later modified to “one gene, one polypeptide,” with each gene responsible for producing a singe protein [9]. In parallel, the of the chemoreceptor concept was proposed by both Clark and Ehlrich in the first decade of the twentieth century [10], yet the theory of receptor-mediated drug interactions did not gain wide acceptance until Ahlquist demonstrated the differential action of adrenaline on two distinct receptor populations, in 1948.

However, the concept of “one gene, one protein” was extended to “one gene, one protein, one disease” and become a major intellectual assumption behind target-based drug discovery [11]. This in part is linked to the discovery of the role of individual genes in Mendalian inherited disorders, such as Linus Pauling's 1949 discovery of the single-protein cause of sickle cell anemia [12]. The extended concept of “one gene, one protein, one disease” became a powerful assumption for molecular target-driven drug discovery and development [11,13]. However the recognition that complex traits are not the result of one gene but of several interacting genes has been long been recognized, as far back as Bridge's work on sex in Drosophila melanogaster in the early 1920s. Furthermore, as the concept of complex traits beyond single-gene phenotypes goes back to the foundation of molecular biology, so to, can the roots of polypharmacology be argued to extend back to Ehrlich's extension of the concept of chemoreceptors to include “polyceptors, with multiple binding sites” [10].

Large-scale functional genomics studies, in a variety of model organisms, have revealed that under laboratory conditions the vast majority of single-gene knockouts by themselves exhibit little or no effect on phenotype, with approximately 19% of genes being essential across a number of model organisms [14–16]. In addition to the 19% lethality rate, systematic genomewide homozygous gene deletion experiments in yeast reveal only 15% of knockouts resulting in a fitness defect, under ideal conditions [17]. A project intended to delete each of the druggable genes [18] in the mouse genome and profile each knockout across a battery of phenotypic assays has revealed that a proportion as low as 10% of knockouts demonstrate phenotypes that may be of value for drug target validation [14,19–21]. Phenotype robustness can be understood in terms of redundant functions and alternative compensatory signaling routes that enable individual nodes to be bypassed [22].

The robustness of individual gene perturbation is also revealed by metabolic flux analysis, where modulation of single components in a pathway rarely results in large changes in metabolic flux and therefore phenotype [13,23,24]. Greater phenotype perturbation is observed in systems where two or more gene products are modulated. The emergent phenotype that occurs from the perturbation of multiple nodes is demonstrated by the systematic experiments on synthetic behaviors: synthetic lethality, synthetic sickness, and synthetic rescue. Systematic experiments with dual knockouts in model systems have shown that, while the deletion of two genes in isolation may show no effect, the simultaneous deletion of two genes can lead to “synthetic lethality” or “synthetic sickness” [25]. When dual knockouts are introduced, by genetic or chemical perturbations, the number of essential genes in yeast is predicted to significantly expand the 19% of genes for which singleton gene knockouts are lethal. A large-scale study by Hillenmeyer et al. demonstrates the extent of synthetic lethality when gene deletions are augmented by chemical intervention [26]. Under ideal conditions only 34% of single-gene deletion results in lethality or sickness. When the whole-genome panel of yeast single-gene knockouts was screened against a diverse, small-molecule library and assayed against a wide range of environment conditions, an additional 63% of gene knockouts showed a growth phenotype [26]. Thus 97% of genes demonstrate a fitness defeat when challenged with a small molecule under at least environment conditions. The vast majority of genes may be redundant under any one environment, but there appears to be little redundancy across a spectrum of conditions when a genetic perturbation is combined with a chemical insult. Genes that may appear dormant and dispensable under one specific set of conditions may prove essential under other stresses [27,28].

Insight into the experimental results describing phenotype robustness to perturbation can be found from understanding the role of biological networks. The architecture of networks in the robustness, degeneracy and redundancy of biological systems is fueling a challenge to the dominant assumption of single-target drug discovery [5,29–32]. Network analysis of biological pathways and interactions has revealed that much of the robustness of biological systems can derive from the structure of the network [33,34]. The scale-free nature of many biological networks results in a system that is resilient against random deletion of any one node but is also critically dependent on a few highly connected hubs. Network biology analysis predicts that if, in most cases, deletion of individual nodes may have little effect on disease networks, modulating multiple proteins may be required to perturb robust phenotypes [5,33,35].

The inherent robustness of interaction networks, as an underlaying property, has profound implications for drug discovery; instead of searching for the “disease-causing gene,” network biology suggests that the strategy should be to perturb the disease network [36,37]. Hellerstein has argued the true targets of drugs are not individal proteins but functionally important biochemical pathways embedded in larger biological networks [11].

These intellectual foundations challenge long-held asumptions behind single-target selection. In response to these new biological insights into the complexity, robustness, and redundancy in disease phenotype, a new approach to drug discovery, namely, polypharmacology, is emerging [3,5,6,29,30,35,38–45]. Therefore, understanding the polypharmaoclogy of a drug and its effect on biological networks and phenotype is essential if we wish to improve efficiacy but also understand toxicity [3].

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Part A

Polypharmacology: A Safety Concern in Drug Discovery

Chapter 1

The Relevance of Off-Target Polypharmacology

Bruce D. Car

The concern of the public, regulators, and litigators for rare but occasionally fatal or disabling effects of drugs was crystallized in the 1990s by two cases for which a precise, biochemical understanding of the basis of the effects ultimately became well understood, those of fen-phen (fenfluramine, dexfenfluramine) and terfenadine (Seldane). While generally receiving more attention in the press, idiosyncratic hepatoxicity is thought to result from uncertain and perhaps highly complex or multifactorial immunologic mechanisms coupled to biotransformation-related events. There are potentially multiple molecular targets involved, rendering predictive strategies difficult. In contrast, the cardiac valvular effects of serotonergic agents due to 5HT2B agonism, and the fatal ventricular arrhythmias of the commonly used antihistamine, terfenadine, resulting from hERG K+ channel inhibition, are biochemically discrete. Facile counterscreens to these unwanted off-target pharmacologies permit the creation of drugs specifically devoid of these liabilities. The relevance of the discrete polypharmacology of these two cases has been extended for 5HT2B agonism to other appetite suppressants in the demonstration of a class effect. Selective agents, such as lorcaserin (Figure 1.1), lack 5HT2B agonism and do not cause valvulopathies. Following the identification of hERG as a relatively common off target, many compounds have been discontinued or have received “blackbox” labeling. Safe antihistamines no longer carry this liability. These two examples represent retrospective discoveries of major off-target safety issues. Recognizing the importance of off-target effects prior to selecting a lead for clinical advancement, a selectivity strategy was devised for the dipeptidyl peptidase IV (DPP4) class of drugs for type 2 diabetes. Proactive identification of inhibitors highly selective over DPP2, DPP8, and DPP9 at projected clinically relevant concentrations led to the development of sitagliptin (Figure 1.1), which has proved safe in a broad patient population. The relevance and precise understanding of off-target polypharmacology in these two cases has driven the desire, as exemplified by sitagliptin, to reduce or eliminate interactions with hERG, 5HT2B, and all other off targets and thereby make safer drugs. Specifically, countless patients who would have been susceptible to the consequences of off-target polypharmacology now lead healthy lives.

Figure 1.1 Structures of the appetite suppressants fenfluramine, dexfenfluramine, and lorcaserin; the antihistamine terfenadine and its metabolite, fexofenadine; the fungicide ketoconazole; and the antidiabetics, sitagliptin and vildagliptin.

What is understood of the role and function of safety pharmacology groups varies widely in the pharmaceutical industry. Different resourcing and scientific models exist, ranging from the checkbox description of the minimum datasets required by the ICH S7A and S7B guidelines, through to a more resource–intensive, broader evaluation of specific cardiovascular, respiratory, and neurologic endpoints in vivo, and broader determination of biochemical selectivity in both cell-based and biochemical assays [1, 2]. In this latter model, findings observed in initial biochemical profiling screens or in more formal drug safety evaluation in nonclinical species are used to optimize subsequent leads to reduce unwanted off-target activities. In general, safety pharmacology engages the drug discovery research phase as a largely predictive science, merging with drug safety evaluation, which is both predictive (to humans) and reactive in the determination of compound liabilities in agnostic whole- animal screens. The concept of polypharmacology or molecular promiscuity [3] and its consequences are generally incorporated into the workings of safety pharmacology groups. An understanding of the impact of selectivity versus promiscuity is emerging and guiding the evolving strategies for how safety pharmacology groups work to reduce compound attrition and improve drug safety.

The high prevalence of obesity in the developed world, with an understanding of how obesity predisposes to type 2 diabetes, cardiovascular disease, a variety of cancers, and other diseases, and quite simply human vanity, has driven the discovery, development, and subsequent abuse of appetite suppressant drugs. Multiple neuronal mechanisms contribute to the complex phenomenon of appetite and are reflected in the complexity of appetite suppressive pharmacologic approaches, and possibly the relatively low efficacy of engaging single mechanisms of appetite suppression [4]. Fenfluramine and its more potent stereoisomer, dexfenfluramine (Figure 1.1), were developed as moderately efficacious anorectic agents stimulating 5HT (5-hydroxytriptamine or serotonin) transmission by the CNS by increasing levels of 5HT. This was shown to occur for these drugs and their major metabolites, norfenfluramines, by acting as substrates for serotonin transporter on serotonergic neurons (SERT) and not dopamine or noradrenaline transporters [4]. These drugs were withdrawn from the market because of a high incidence of cardiac valve disease (CVD), especially in those patients either prescribed or self-administered substantially higher than recommended dosages [5].

Although at the time it was known that 5HT is mitogenic in certain systems, the relatively weak association (odds ratio of 2) between drug administration and CVD was not understood. Broad screening of receptors (receptorome) led, in part, to a detailed evaluation of the 5HT2 family of 5HT receptors [6]. A series of experiments spanning several years identified the high expression of the receptor for 5HT2B on cardiac valvular endothelium, and revealed that elevated plasma 5HT concentrations can drive mitogenesis through agonism of the 5HT2B receptor, that agonism of the 5HT2B receptor by fenfluramines and their metabolites likely underpins cardiac valvular pathology, and that an interactions of 5HT with 5HT2C drives appetite control [5].

Identification of the desired molecular target for appetite control (5HT2C) versus the putative cause of valvulopathy (5HT2B) spawned drug discovery programs driving selectivity between these two proteins. Through these and other research programs, the author and industry colleagues have recognized the frequency with which aminergic receptors, transporters, and degradative enzymes (monamine oxidase A and B) are off-target hits for a large variety of clinical indications, but especially those drugs that are CNS-active. While 5HT2B agonism is rare and serious, 5HT2B antagonism does not appear to be associated with clinical consequences despite the cardiac phenotype of the knockout mouse of the same receptor. Lorcaserin was recently submitted for registration with the FDA as a 5HT2C-selective appetite suppressant. While this selectivity appeared to successfully avoid the predisposition to CVD [7], an unusual constellation of preclinical rodent carcinogenicity findings more recently led to the initial rejection of the drug application. Possibly related to the difficulty in building selectivity into drugs specifically targeting 5HT receptors, identifying 5HT2C agonists without a variety of unexpected preclinical off-target effects has prove extremely difficult for all companies working in this field.

Since the discovery of the role of the myocardial K+ channel, hERG, in drug-induced QT interval prolongation, and secondarily an association with the rare ventricular arrhythmia, torsades de pointes (TdP), drug leads have been carefully evaluated and profiled in vitro and in vivo for this liability. Although an imperfect association exists between hERG inhibition, QT prolongation, and TdP, studiously avoiding these effects preclinically, and rigorous early clinical screening has markedly reduced the incidence of this liability. TdP has plagued repolarization-delaying antiarrhythmics, various antihistamines, antipsychotics, antimicrobials, and other drugs [8, 9]. Before development of the molecule-level hypotheses that led to chemists developing a structure–activity relationship (SAR) for selectivity of desirable pharmacology over hERG, several market withdrawals of commonly used agents occurred. Terfenadine (Seldane) was a commonly used and highly effective antihistamine in the late 1980s and early 1990s. In 1990, Monahan et al. [10] described the first association (exclusive of drug overdose) of symptomatic TdP occurring with the use of terfenadine in a patient who was taking the recommended prescribed dose of this drug in addition to cefaclor, ketoconazole, and medroxyprogesterone. Measured serum concentrations of terfenadine and its main metabolite showed that excessive levels of parent terfenadine and proportionately reduced concentrations of metabolite, suggesting inhibition of terfenadine metabolism by ketoconazole-mediated inhibition of drug metabolism through cytochrome 3A4 [10, 11]. This was subsequently proved. In fact, ketaconazole both increased parent terfenadine (Figure 1.1) while reducing concentrations of the active acid metabolite fexofenadine [11]. This is consistent with the generally poor cell penetrance of acids, the knowledge that hERG inhibitors act on the intracellular side of the K+ channel, and that the SAR for this interaction frequently involves drug basicity. The interactions of fexofenadine with hERG are profoundly reduced compared to terfenadine, rendering this drug and subsequently improved antihistamines much safer with respect to cardiovascular risk.

Following many years in which potentially avoidable off-target effects of drugs were first identified in clinical trials, strategies were developed to attempt to identify and eliminate such effects prior to lead selection. The eventual development of highly selective DPP4 inhibitors with optimal safety profiles in humans derived from this strategy.

The desired pharmacology of DPP4 inhibitors in type 2 diabetes is the inhibition of cleavage of the incretinlike hormones, GLP1 (glucagonlike peptide-1) and GIP (gastrointestinal polypeptide) in plasma. Normally, GLP1 is rapidly hydrolyzed (half-life t <1 min) by DPP4. GLP1 acts to reduce plasma glucose by stimulating pancreatic islet β-cell insulin secretion. Through inhibition of its cleavage, the action of GLP1 may be prolonged, thereby lowering blood glucose and improving glucose homeostasis [12]. Using selective tool molecules for homologous proteinases (an inhibitor of DPP8/9), and of quiescent cell proline dipeptidases (QPP), effects relating to their inhibition, including alopecia, thrombocytopenia, reticulocytopenia, enlarged spleen, multiorgan histopathologic changes, and gastrointestinal toxicity, were shown in vivo. In addition, study of the DPP8/9 inhibitor in vitro suggested attenuation of human T-cell responses. In parallel studies, selective inhibitors of DPP4 did not demonstrate toxicity in either rats or dogs [13]. In addition to these homologous proteinases, efforts to maintain selectivity of DPP4 over DPP2 have also been sought [14]. Clinical results with sitagliptin suggest that an optimal safety profile for this new class of antihyperglycemic may have resulted from the proactive medicinal chemistry strategy to obtain high selectivity of DPP4 over homologous proteinases. However, some less selective DPP4 inhibitors are also used safely in patients, suggesting that these drugs are either selective within the exposure range employed in patients, or that the selectivity itself is not important [14]. The delayed full registration in the United States of the less selective DPP4 inhibitor, vildagliptin (Figure 1.1), may relate in part to preclinical safety issues, possibly secondary to DPP nonselectivity.

Two examples of clearly avoidable but retrospectively discovered off targets, in part, drove the pharmaceutical industry to seek drugs with greater selectivity. Complementing this approach is an example in which proactively building biochemical selectivity into a drug may have contributed to an overall safer medicine. The definition of selectivity has been broadened from specific off targets to broader classes of relatively higher-frequency off-target hits. When drugs are then classified by high nonselectivity (molecular promiscuity) versus highly selectivity, a compelling correlation between clinical safety and biochemical selectivity emerges [3]. The science of these concepts is aptly described by the term polypharmacology.

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Chapter 2

Screening for Safety-Relevant Off-Target Activities

Laszlo Urban, Steven Whitebread, Jacques Hamon, Dmitri Mikhailov, and Kamal Azzaoui

2.1 Introduction

The term off-target is generally used with a pejorative connotation. However, concerning drug discovery and medicine, the correct meaning of off-target is interpreted somewhat differently. Let us start with all “druggable” targets and consider those that have a positive therapeutic potential. It is remarkable that most of them qualify for this category; depending on their activation, inhibition or modulation, and tissue/organ distribution, they are associated with beneficial effects as therapies or life quality enhancers. Also, molecules of the body undergo structural, configurational changes in a large number of pathological conditions and become specific targets for drug molecules. Drug interaction with the above described targets for a therapy is always defined as the on-target effect, and if the same drug has an effect on another molecule, we call it an off-target effect. While this sounds trivial, the consequences of off-target effects could be very different. Off-target effects might synergize with the on-target effect and enhance therapeutic potential. They might have other beneficial effects, which could broaden the indication of the drug. For example, most successful psychiatric indications require effects at multiple targets, but often with a restrictive side effect profile. Off-target effects can also highlight alternative applications of the drug or its optimized derivatives. However, the greatest interest is in those off-target effects that are associated with unwanted side effects, or more precisely, adverse drug reactions. In this aspect, we have arrived at the original connotation “wrong, bad, injurious, unfit, and so on.” While this seems to make sense, caution should be taken, because one can assume on-target and off-target effects could be associated with the same target, depending on the therapeutic indication.

In this chapter we take aim at the safety-related off-target effects. We will focus on safety-oriented applications, which are used for early safety testing during the lead selection and optimization phase of drug discovery. The strategy and approach we will review have been discussed by various authors and called several names, such as in vitro safety pharmacology profiling [1] or exploratory safety profiling [2]. Although testing for adverse drug reactions (ADRs) in in vitro safety pharmacology panels is not new, the modern concept of integrated risk assessment based on these studies has emerged only during the past 5 years. Annotation of individual molecular targets was made possible by the development of automated multiple parallel and high-content profiling screens and by the systemic accumulation of clinical information on adverse drug reactions. Linking the data from these two approaches together provided such a knowledge base, which one can use today for the prediction of clinical ADRs of drug candidates on the basis of their preclinical pharmacokinetic (PK) performance and in vitro safety pharmacology data. Furthermore, early mitigation of off-target effects became a possibility by developing a structure–activity relationship (SAR) analysis based on chemical structural features associated with binding to specific off-target proteins.

2.2 General Aspects

2.2.1 Rationale for Profiling Molecules for Potential Adverse Effects