Drug Metabolism Prediction E-Book

• Herausgeber: Wiley-VCH
• Kategorie: Wissenschaft und neue Technologien
• Serie: Methods and Principles in Medicinal Chemistry
• Sprache: Englisch

Seitenzahl: 1034

Veröffentlichungsjahr: 2014

Beschreibung

The first professional reference on this highly relevant topic, for drug developers, pharmacologists and toxicologists.

The authors provide more than a systematic overview of computational tools and knowledge bases for drug metabolism research and their underlying principles. They aim to convey their expert knowledge distilled from many years of experience in the field. In addition to the fundamentals, computational approaches and their applications, this volume provides expert accounts of the latest experimental methods for investigating drug metabolism in four dedicated chapters. The authors discuss the most important caveats and common errors to consider when working with experimental data.

Collating the knowledge gained over the past decade, this practice-oriented guide presents methods not only used in drug development, but also in the development and toxicological assessment of cosmetics, functional foods, agrochemicals, and additives for consumer goods, making it an invaluable reference in a variety of disciplines.

Leseprobe

CONTENTS

Cover

Related Titles

Title Page

Copyright

List of Contributors

Preface

A Personal Foreword

Part One: Introduction

Chapter 1: Metabolism in Drug Development

1.1 What? An Introduction

1.2 Why? Metabolism in Drug Development

1.3 How? From Experimental Results to Databases to Expert Software Packages

1.4 Who? Human Intelligence as a Conclusion

References

Part Two: Software, Web Servers and Data Resources to Study Metabolism

Chapter 2: Software for Metabolism Prediction

2.1 Introduction

2.2 Ligand-Based and Structure-Based Methods for Predicting Metabolism

2.3 Software for Predicting Sites of Metabolism

2.4 Software for Predicting Metabolites

2.5 Software for Predicting Interactions of Small Molecules with Metabolizing Enzymes

2.6 Conclusions

References

Chapter 3: Online Databases and Web Servers for Drug Metabolism Research

3.1 Introduction

3.2 Online Drug Metabolism Databases

3.3 Online Drug Metabolism Prediction Servers

References

Part Three: Computational Approaches to Study Cytochrome P450 Enzymes

Chapter 4: Structure and Dynamics of Human Drug-Metabolizing Cytochrome P450 Enzymes

4.1 Introduction

4.2 Three-Dimensional Structures of Human CYPs

4.3 Structural Features of CYPs

4.4 Dynamics of CYPs

4.5 Conclusions

References

Chapter 5: Cytochrome P450 Substrate Recognition and Binding

5.1 Introduction

5.2 Substrate Recognition in the Catalytic Cycle of CYPs

5.3 Substrate Identity in Various Species

5.4 Structural Insight into Substrate Recognition by CYPs

5.5 The Challenges of Using Docking for Predicting Kinetic Parameters

5.6 Substrate Properties for Various Human Isoforms

5.7 Conclusions

References

Chapter 6: QM/MM Studies of Structure and Reactivity of Cytochrome P450 Enzymes: Methodology and Selected Applications

6.1 Introduction

6.2 QM/MM Methods

6.3 Selected QM/MM Applications to Cytochrome P450 Enzymes

6.4 An Overview of Cytochrome P450 Function Requires Reliable MD Calculations

6.5 Conclusions

References

Chapter 7: Computational Free Energy Methods for Ascertaining Ligand Interaction with Metabolizing Enzymes

7.1 Introduction

7.2 Linking Experiment and Simulation: Statistical Mechanics

7.3 Taxonomy of Free Energy Methods

7.4 Ligand Parameterization

7.5 Specific Examples

7.6 Conclusions

References

Chapter 8: Experimental Approaches to Analysis of Reactions of Cytochrome P450 Enzymes

8.1 Introduction

8.2 Structural Data and Substrate Binding

8.3 Systems for Production of Reaction Products and Analysis of Systems

8.4 Methods for Analysis of Products of Drugs

8.5 Untargeted Searches for CYP Reactions

8.6 Complex CYP Products

8.7 Structure–Activity Relationships Based on Products

8.8 SAR of Reaction Rates

8.9 Other Issues in Predictions

8.10 Conclusions

References

Part Four: Computational Approaches to Study Sites and Products of Metabolism

Chapter 9: Molecular Interaction Fields for Predicting the Sites and Products of Metabolism

9.1 Introduction

9.2 CYP from a GRID Perspective

9.3 From Lead Optimization to Preclinical Phases: the Challenge of SoM Prediction

9.4 Conclusions

References

Chapter 10: Structure-Based Methods for Predicting the Sites and Products of Metabolism

10.1 Introduction

10.2 6 Å Rule

10.3 Methodological Approaches

10.4 Prediction of Binding Poses

10.5 Protein Flexibility

10.6 Role of Water Molecules

10.7 Effect of Mutations

10.8 Conclusions

References

Chapter 11: Reactivity-Based Approaches and Machine Learning Methods for Predicting the Sites of Cytochrome P450-Mediated Metabolism

11.1 Introduction

11.2 Reactivity Models for CYP Reactions

11.3 Reactivity-Based Methods Applied to CYP-Mediated Site of Metabolism Prediction

11.4 Machine Learning Methods Applied to CYP-Mediated Site of Metabolism Prediction

11.5 Applications to SoM Prediction

11.6 Combinations of Structure-Based Models and Reactivity

11.7 Conclusions

References

Chapter 12: Knowledge-Based Approaches for Predicting the Sites and Products of Metabolism

12.1 Introduction

12.2 Building and Maintaining a Knowledge Base

12.3 Encoding Rules in a Knowledge Base

12.4 Ways of Working with Rules

12.5 Using the Logic of Argumentation

12.6 Combining Absolute and Relative Reasoning

12.7 Combining Predictions from Multiple Sources

12.8 Validation and Assessment of Performance

12.9 Conclusions

References

Part Five: Computational Approaches to Study Enzyme Inhibition and Induction

Chapter 13: Quantitative Structure–Activity Relationship (QSAR) Methods for the Prediction of Substrates, Inhibitors, and Inducers of Metabolic Enzymes

13.1 Introduction

13.2 In Silico QSAR Methods

13.3 QSAR Models for Cytochrome P450

13.4 Conjugative Metabolizing Enzymes

13.5 In Vitro Clearance QSAR

13.6 Conclusions

References

Chapter 14: Pharmacophore-Based Methods for Predicting the Inhibition and Induction of Metabolic Enzymes

14.1 Introduction

14.2 Substrate and Inhibitor Pharmacophore Models

14.3 Inducer Models

14.4 Conclusions

References

Chapter 15: Prediction of Phosphoglycoprotein (P-gp)-Mediated Disposition in Early Drug Discovery

15.1 Introduction

15.2 QSAR Modeling of Compounds Interacting with Transporters

15.3 Influence of Compound Structure on P-gp Substrate Identity

15.4 QSAR Models for P-gp Substrates

15.5 Application to Drug Discovery

15.6 Conclusions

References

Chapter 16: Predicting Toxic Effects of Metabolites

16.1 Introduction

16.2 Methods for Predicting Toxic Effects

16.3 Conclusions

References

Part Six: Experimental Approaches to Study Metabolism

Chapter 17: In Vitro Models for Metabolism: Applicability for Research on Food Bioactives

17.1 Introduction

17.2 Classification of In Vitro Models for Metabolism

17.3 Modifications via Gut (Colon) Microflora

17.4 Intestinal (Gut Wall) Metabolism

17.5 Hepatic Metabolism

17.6 Pharmacokinetic Data Obtainable from In Vitro Metabolism Models

17.7 Assay Validation

17.8 Conclusions

References

Chapter 18: In Vitro Approaches to Study Drug–Drug Interactions

18.1 Introduction

18.2 Inhibition of Drug Metabolism

18.3 Transcriptional Regulation of Metabolism

18.4 Next-Generation Models and Concluding Remarks

References

Chapter 19: Metabolite Detection and Profiling

19.1 Introduction

19.2 Chromatography

19.3 Mass Spectrometry

19.4 Sample Preparation for LC–MS-Based Metabolite Profiling

19.5 Metabolic Profiling by LC–MS

19.6 Conclusions

References

Index

End User License Agreement

List of Tables

Table 1.1

Table 1.2

Table 1.3

Table 1.4

Table 1.5

Table 2.1

Table 3.1

Table 3.2

Table 4.1

Table 5.1

Table 5.2

Table 5.3

Table 6.1

Table 8.1

Table 8.2

Table 8.3

Table 10.1

Table 14.1

Table 14.2

Table 14.3

Table 15.1

Table 15.2

Table 17.1

Table 18.1

Table 18.2

List of Illustrations

Figure 1.1

Figure 1.2

Figure 1.3

Figure 1.4

Figure 1.5

Figure 1.6

Figure 3.1

Figure 3.2

Figure 4.1

Figure 4.2

Figure 4.3

Figure 4.4

Figure 4.5

Figure 5.1

Figure 5.2

Figure 5.3

Figure 5.4

Figure 5.5

Figure 5.6

Figure 5.7

Figure 5.8

Figure 5.9

Figure 5.10

Figure 5.11

Scheme 6.1

Scheme 6.2

Scheme 6.3

Figure 6.1

Scheme 6.4

Figure 6.2

Figure 6.3

Figure 6.4

Figure 6.5

Figure 6.6

Scheme 6.5

Figure 6.7

Figure 6.8

Figure 6.9

Scheme 6.6

Figure 6.10

Scheme 6.7

Scheme 6.8

Figure 6.11

Figure 6.12

Figure 7.1

Figure 7.2

Figure 7.3

Figure 8.1

Figure 8.2

Figure 8.3

Figure 8.4

Figure 8.5

Figure 8.6

Figure 8.7

Figure 8.8

Figure 8.9

Figure 9.1

Figure 9.2

Figure 9.3

Figure 9.4

Figure 9.5

Figure 9.6

Figure 9.7

Figure 10.1

Figure 10.2

Figure 10.3

Figure 10.4

Figure 10.5

Figure 11.1

Figure 11.2

Figure 11.3

Figure 11.4

Figure 11.5

Figure 11.6

Figure 11.7

Figure 11.8

Figure 11.9

Figure 11.10

Figure 11.11

Figure 12.1

Figure 12.2

Figure 12.3

Figure 12.4

Figure 12.5

Figure 12.6

Figure 12.7

Figure 12.8

Figure 12.9

Figure 13.1

Figure 13.2

Figure 13.3

Figure 13.4

Figure 14.1

Figure 14.2

Figure 15.1

Figure 16.1

Figure 16.2

Figure 16.3

Figure 17.1

Figure 17.2

Figure 18.1

Figure 18.2

Figure 18.3

Figure 18.4

Figure 18.5

Figure 18.6

Figure 18.7

Figure 18.8

Figure 18.9

Figure 19.1

Figure 19.2

Figure 19.3

Figure 19.4

Guide

Cover

Table of Contents

Begin Reading

Part 1

Chapter 1

Pages

ii

iii

iv

xvii

xviii

xix

xx

xxi

xxii

xxiii

xxiv

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

61

62

63

64

65

66

67

68

69

70

71

72

73

74

75

76

77

78

79

80

81

82

83

84

85

86

87

88

89

90

91

92

93

94

95

96

97

98

99

100

101

102

103

105

106

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

123

124

125

126

127

128

129

130

131

132

133

135

136

137

138

139

140

141

142

143

144

145

146

147

148

149

150

151

152

153

154

155

156

157

158

159

160

161

162

163

164

165

166

167

168

169

170

171

172

173

174

175

176

177

178

179

180

181

182

183

184

185

186

187

188

189

190

191

192

193

194

195

196

197

198

199

200

201

202

203

204

205

206

207

208

209

210

211

212

213

214

215

216

217

218

219

220

221

222

223

224

225

226

227

228

229

230

231

232

233

234

235

236

237

238

239

240

241

242

243

244

245

246

247

248

249

250

251

252

253

254

255

256

257

258

259

260

261

262

263

264

265

266

267

268

269

270

271

272

273

274

275

276

277

278

279

280

281

282

283

284

285

286

287

288

289

290

291

292

293

294

295

296

297

298

299

300

301

302

303

304

305

306

307

308

309

310

311

312

313

314

315

316

317

318

319

320

321

322

323

324

325

326

327

328

329

330

331

332

333

334

335

336

337

338

339

340

341

342

343

344

345

346

347

348

349

350

351

352

353

354

355

356

357

358

359

360

361

362

363

364

365

366

367

368

369

370

371

372

373

374

375

376

377

378

379

380

381

382

383

384

385

386

387

388

389

390

391

392

393

394

395

396

397

398

399

400

401

402

403

404

405

406

407

408

409

410

411

412

413

414

415

416

417

418

419

420

421

422

423

424

425

426

427

428

429

430

431

432

433

434

435

436

437

438

439

440

441

442

443

444

445

446

447

448

449

450

451

452

453

454

455

456

457

458

459

460

461

462

463

464

465

466

467

468

469

470

471

472

473

474

475

476

477

478

479

480

481

482

483

484

485

486

487

488

489

490

491

492

493

494

495

496

497

498

499

500

501

502

503

504

505

506

507

508

509

510

511

Related Titles

Methods and Principles in Medicinal Chemistry

Edited by R. Mannhold, H. Kubinyi, G. Folkers

Editorial Board

H. Buschmann, H. Timmerman, H. van de Waterbeemd, T. Wieland

Previous Volumes of this Series:

Vela, José Miguel / Maldonado, Rafael / Hamon, Michel (Eds.)

In vivo Models for Drug Discovery

2014

ISBN: 978-3-527-33328-8

Vol. 62

Liras, Spiros / Bell, Andrew S. (Eds.)

Phosphodiesterases and Their Inhibitors

2014

ISBN: 978-3-527-33219-9

Vol. 61

Hanessian, Stephen (Ed.)

Natural Products in Medicinal Chemistry

2014

ISBN: 978-3-527-33218-2

Vol. 60

Lackey, Karen / Roth, Bruce (Eds.)

Medicinal Chemistry Approaches to Personalized Medicine

2013

ISBN: 978-3-527-33394-3

Vol. 59

Brown, Nathan (Ed.)

Scaffold Hopping in Medicinal Chemistry

2013

ISBN: 978-3-527-33364-6

Vol. 58

Hoffmann, Rémy / Gohier, Arnaud / Pospisil, Pavel (Eds.)

Data Mining in Drug Discovery

2013

ISBN: 978-3-527-32984-7

Vol. 57

Dömling, Alexander (Ed.)

Protein-Protein Interactions in Drug Discovery

2013

ISBN: 978-3-527-33107-9

Vol. 56

Kalgutkar, Amit S. / Dalvie, Deepak / Obach, R. Scott / Smith, Dennis A.

Reactive Drug Metabolites

2012

ISBN: 978-3-527-33085-0

Vol. 55

Brown, Nathan (Ed.)

Bioisosteres in Medicinal Chemistry

2012

ISBN: 978-3-527-33015-7

Vol. 54

Gohlke, Holger (Ed.)

Protein-Ligand Interactions

2012

ISBN: 978-3-527-32966-3

Vol. 53

Drug Metabolism Prediction

Johannes Kirchmair

All books published by Wiley-VCH are carefully produced. Nevertheless, authors, editors, and publisher do not warrant the information contained in these books, including this book, to be free of errors. Readers are advised to keep in mind that statements, data, illustrations, procedural details or other items may inadvertently be inaccurate.

Library of Congress Card No.: applied for

British Library Cataloguing-in-Publication Data

A catalogue record for this book is available from the British Library.

Bibliographic information published by the Deutsche Nationalbibliothek

The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data are available on the Internet at http://dnb.d-nb.de.

© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Boschstr. 12, 69469 Weinheim, Germany

All rights reserved (including those of translation into other languages). No part of this book may be reproduced in any form – by photoprinting, microfilm, or any other means – nor transmitted or translated into a machine language without written permission from the publishers. Registered names, trademarks, etc. used in this book, even when not specifically marked as such, are not to be considered unprotected by law.

Print ISBN: 978-3-527-33566-4

ePDF ISBN: 978-3-527-67299-8

ePub ISBN: 978-3-527-67301-8

Mobi ISBN: 978-3-527-67300-1

oBook ISBN: 978-3-527-67326-1

List of Contributors

Andreas Bender

Unilever Centre for Molecular Science Informatics

Department of Chemistry

Lensfield Road

Cambridge CB2 1EW

UK

Jessica A. Bonzo

Life Technologies Corporation

Cell Biology and Stem Cell Systems

7335 Executive Way

Frederick, MD 21704

USA

Fabio Broccatelli

The Institute of Cancer Research

Division of Cancer Therapeutics

Cancer Research UK Cancer

Therapeutics Unit

15 Cotswold Road

Sutton SM2 5NG

UK

Nathan Brown

The Institute of Cancer Research

Division of Cancer Therapeutics

Cancer Research UK Cancer

Therapeutics Unit

15 Cotswold Road

Sutton SM2 5NG

UK

Hui Chen

Chinese Academy of Sciences

Institute of Chemistry

CAS Key Laboratory of Photochemistry

Beijing National Laboratory for Molecular Sciences (BNLMS)

No. 2, 1st North Street, Zhongguancun

Beijing 100190

China

Richard J. Dimelow

Wright Dose Ltd

2 Woodlands Road

Altrincham WA14 1HF

UK

Guus Duchateau

Unilever

R&D Vlaardingen

Olivier van Noortlaan 120

3133 AT Vlaardingen

The Netherlands

Stephen S. Ferguson

National Institute of Environmental Health Sciences

Biomolecular Screening Branch

Division of the National Toxicology Program

111 T.W. Alexander Drive

Research Triangle Park, NC 27709

USA

Mathew Paul Gleeson

Kasetsart University

Faculty of Science

Department of Chemistry

50 Phaholyothin Road

Chatuchak, Bangkok 10900

Thailand

Natalie D. Glube

BASF SE

Human Nutrition Europe

Chemiestraße 22

68623 Lampertheim

Germany

Frederick Peter Guengerich

Vanderbilt University School of Medicine

Department of Biochemistry and Center in Molecular Toxicology

638 Robinson Research Building

2200 Pierce Avenue

Nashville, TN 37232-0146

USA

Supa Hannongbua

Kasetsart University

Faculty of Science

Department of Chemistry

50 Phaholyothin Road

Chatuchak, Bangkok 10900

Thailand

Philip Neville Judson

Lhasa Limited

Granary Wharf House

2 Canal Wharf

Leeds LS11 5PY

UK

Teresa Kaserer

University of Innsbruck

Institute of Pharmacy/Pharmaceutical Chemistry and Center for Molecular Biosciences Innsbruck (CMBI)

Innrain 80–82

6020 Innsbruck

Austria

Nathan J. Kidley

Syngenta

Jealott's Hill International Research Centre

Bracknell, Berkshire RG42 6EY

UK

Johannes Kirchmair

University of Cambridge

Unilever Centre for Molecular Science Informatics

Department of Chemistry

Lensfield Road

Cambridge CB2 1EW

UK

and

ETH Zurich

Institute of Pharmaceutical Sciences

Department of Chemistry and Applied Biosciences

Vladimir-Prelog-Weg 1-5/10

8093 Zurich

Switzerland

Andrew G. Leach

Liverpool John Moores University

School of Pharmacy and Biomolecular Sciences

James Parsons Building

Byrom Street

Liverpool L3 3AF

UK

Ghulam Mustafa

Heidelberg Institute for Theoretical Studies

Molecular and Cellular Modeling Group

Schloss-Wolfsbrunnenweg 35

69118 Heidelberg

Germany

and

University of Karachi

Dr. Panjwani Center for Molecular Medicine & Drug Research

International Center for Chemical & Biological Sciences

KU Circular Rd

75270 Karachi

Pakistan

Chris Oostenbrink

University of Natural Resources and Life Sciences

Institute of Molecular Modeling and Simulation

Muthgasse 18

1190 Vienna

Austria

Oraphan Phuangsawai

Kasetsart University

Faculty of Science

Department of Chemistry

50 Phaholyothin Road

Chatuchak, Bangkok 10900

Thailand

Patrik Rydberg (Deceased)

University of Copenhagen

Faculty of Health and Medical Sciences

Department of Drug Design and Pharmacology

Universitetsparken 2

2100 Copenhagen

Denmark

and

Optibrium Ltd

7221 Cambridge Research Park

Beach Drive

Cambridge CB25 9TL

UK

Daniela Schuster

University of Innsbruck

Institute of Pharmacy/Pharmaceutical Chemistry and Center for Molecular Biosciences Innsbruck (CMBI)

Innrain 80–82

6020 Innsbruck

Austria

Sason Shaik

The Hebrew University of Jerusalem

Institute of Chemistry and the Lise Meitner-Minerva Center for Computational Quantum Chemistry

Campus Admond Safra at Givat Ram

91904 Jerusalem

Israel

Lu Tan

University of Cambridge

Cambridge Institute for Medical Research

Department of Medicine

Hills Road

Cambridge CB2 0XY

UK

Veronika Temml

University of Innsbruck

Institute of Pharmacy/Pharmaceutical Chemistry and Center for Molecular Biosciences Innsbruck (CMBI)

Innrain 80–82

6020 Innsbruck

Austria

Bernard Testa

Lausanne University Hospital (CHUV)

Department of Pharmacy

Rue du Bugnon

1011 Lausanne

Switzerland

Walter Thiel

Max-Planck-Institut für Kohlenforschung

Kaiser-Wilhelm-Platz 1

45470 Mülheim an der Ruhr

Germany

Simon Thomas

Cyprotex Discovery Ltd

Scientific Computing Group

15 Beech Lane

Macclesfield SK10 2DR

UK

Dandamudi Usharani

The Hebrew University of Jerusalem

Institute of Chemistry and the Lise Meitner-Minerva Center for Computational Quantum Chemistry

Campus Admond Safra at Givat Ram

91904 Jerusalem

Israel

Rebecca C. Wade

Heidelberg Institute for Theoretical Studies

Molecular and Cellular Modeling Group

Schloss-Wolfsbrunnenweg 35

69118 Heidelberg

Germany

and

Heidelberg University

Center for Molecular Biology (ZMBH)

Im Neuenheimer Feld 282

69120 Heidelberg

Germany

Mark J. Williamson

University of Cambridge

Unilever Centre for Molecular Science Informatics

Department of Chemistry

Lensfield Road

Cambridge CB2 1EW

UK

Ian D. Wilson

Imperial College

Department of Surgery and Cancer

Exhibition Road

South Kensington, London SW7 2AZ

UK

David S. Wishart

University of Alberta

Department of Computing Science

2-21 Athabasca Hall

Edmonton, AB T6G 2E8

Canada

and

University of Alberta

Department of Biological Sciences

CW 405, Biological Sciences Bldg.

Edmonton, AB T6G 2E8

Canada

and

National Institute for Nanotechnology

Division of NanoLife Sciences

11421 Saskatchewan Drive

Edmonton, AB T6G 2M9

Canada

Xiaofeng Yu

Heidelberg Institute for Theoretical Studies

Molecular and Cellular Modeling Group

Schloss-Wolfsbrunnenweg 35

69118 Heidelberg

Germany

Preface

In addition to mediating cell metabolism, the metabolic system developed in animals and humans for the chemical conversion of xenobiotics. Over millions of years, a plethora of oxidizing, hydrolyzing, conjugating, and other enzymes were optimized by evolution. Modification, degradation, and/or conjugation, in many cases to polar products, enable a safe elimination from the organism. Whereas many plant products are toxic, there are only rare examples that the metabolic system converts harmless natural substances into toxic entities. The situation changed about two centuries ago, after the advent of synthetic organic compounds: many of them contain structural features that the metabolic system cannot handle in the same manner as natural products. In only a few generations, evolution did not have enough time to optimize the enzymes for this new challenge. Of course, also potential drug candidates offer such a challenge to the metabolic system. The development of many compounds must be discontinued because of severe side effects of some toxic metabolites, most often chemically reactive compounds [1]. Some metabolites, even formed in only minor amounts, may cause idiosyncratic toxicity, rarely observed but with fatal consequences for the individual.

Chemical features that are easily metabolized are responsible for short biological half-life of some potential drug candidates; on the other hand, lack of such moieties might cause a half-life that is too long for safe use of the drug. In addition, such compounds as well as highly lipophilic analogs have a higher risk to form toxic metabolites. Thus, it is most important to understand metabolic pathways and to have tools to predict which compounds might be generated. This necessity applies especially for the common oxidation of xenobiotics by various cytochrome P450s (CYPs). Three approaches are suited to achieve this task: theoretical treatment, by calculating the accessibility and chemical reactivity of the chemical features of the compound; molecular modeling, especially pharmacophore searches and docking, using 3D structures of the cytochrome binding pockets; and empirical approaches, using the large databases of known metabolic pathways. All these methods have their pros and cons, and none of them seems to be perfect. Especially species selectivity, to conclude from animal results to humans, and the relative amount of certain metabolites are difficult or even impossible to predict.

The introduction of this book provides an overview of the role of metabolism in drug development, followed by a part on software and databases for the study of metabolism. The next part discusses computational approaches for the study of the most important metabolic enzymes, the cytochrome P450 enzymes. 3D structures, substrate recognition and binding, and theoretical and experimental methods for the study of ligand–protein interactions are discussed in this part. The chapters of the next part go into more detail with respect to the sites and products of metabolism, using either molecular interaction fields or structure-, reactivity-, and knowledge-based approaches. The important aspect of enzyme inhibition and induction is discussed in the next chapters, using quantitative structure–activity relationships and pharmacophore-based methods; separate chapters discuss the role of P-gp-mediated disposition and the prediction of toxic effects of metabolites. Last but not least, three chapters describe experimental approaches, that is, in vitro models for the study of metabolism and drug–drug interactions and experimental metabolite detection and profiling.

We are very grateful to Johannes Kirchmair for having accepted our invitation to edit this book, which will be of great importance and practical value for all scientists involved in drug research. Our thanks also go to all chapter authors for their valuable contributions, as well as to Frank Weinreich and Heike Nöthe at Wiley-VCH for their engagement in this project and in our entire book series “Methods and Principles in Medicinal Chemistry.”

Düsseldorf

Weisenheim am Sand

Zürich

June 2014

Raimund Mannhold

Hugo Kubinyi

Gerd Folkers

Reference

1.

Kalgutkar, A.S., Dalvie, D., Obach, R.S., and Smith, D.A. (eds) (2012)

Reactive Drug Metabolites, Methods and Principles in Medicinal Chemistry

, vol. 55 (series eds R. Mannhold, H. Kubinyi, and G. Folkers), Wiley-VCH Verlag GmbH, Weinheim.

A Personal Foreword

Metabolism is a decisive factor for the safety and performance of drugs, cosmetics, food bioactives, and agrochemicals. Methods for analyzing and predicting the metabolic fate of small molecules have become a thriving field of research during the past few years. The allure of predictive metabolism arises from its multidisciplinary nature, bringing together scientists from diverse backgrounds. The research of predictive metabolism also brought me to Cambridge, where I had the privilege to work with Robert Glen and our metabolism team, an inspiring group of a dozen scientists including bioinformaticians, chemists, computer scientists, mathematicians, pharmacists, and physicists, on new methods for predictive metabolism. Unilever and other companies supported us with the necessary funding, a platform for scientific interactions, and, most importantly, experimental data to play with. This has been a truly enlightening, collaborative environment for research and led me to further pursue this work, now together with Bayer Pharma AG at ETH Zurich.

Today a broad range of computational tools and knowledge bases for drug metabolism research are available. The vast majority of these resources are accessible to nonexpert users. With this book, we intend to provide more than a comprehensive overview of these methods and their underlying principles. Our aim is to convey expert knowledge distilled from years – decades – of experience in drug metabolism and our fascination for this field of research.

Metabolizing enzymes show a distinguished level of promiscuity for the binding of small molecules and complex and diverse reaction mechanisms. This makes assay design, readout, and interpretation extremely challenging. The importance of understanding assay and analytical technologies cannot be overemphasized. Thus, in addition to the systematic overview of prediction-based methods, in this volume four dedicated chapters will provide expert accounts of state-of-the-art experimental approaches for investigating drug metabolism, pointing out the most important caveats and common errors to consider when working with experimental data.

It was a great pleasure for me to contribute to this book with such a distinguished team of experts. I would like to take the opportunity to thank the series editors, Raimund Mannhold, Hugo Kubinyi, and Gerd Folkers, and Frank Weinreich and Heike Nöthe at Wiley-VCH for their continuous support during the preparation of this book. I am very grateful to all contributors for their excellent work and communication.

Drug metabolism is a captivating and challenging playground for experimentalists and theoreticians alike, and there are so much more questions and challenges ahead to resolve! Thus, I hope that this book will inspire and encourage young scientists and established experts in metabolism research to further contribute to this exciting field.

On behalf of all contributors, I wish you an enjoyable and informative read.

Zurich

June 2014

Johannes Kirchmair

Part OneIntroduction

1Metabolism in Drug Development

Bernard Testa

1.1 What? An Introduction

Drug metabolism, and more generally xenobiotic metabolism, has become a major pharmacological and pharmaceutical science with particular relevance to biology, therapeutics, and toxicology, as abundantly explained and illustrated in a number of recent books [1–8] and reviews [9–18]. As such, drug metabolism is also of great importance in medicinal chemistry and clinical pharmacology because it influences the deactivation, activation, detoxification, and toxification of most drugs [19–22]. This broader pharmacological context will be considered in Section 1.2. There, I shall address the “Why?” question, namely “Why does drug metabolism deserve so much attention?”