De novo Molecular Design E-Book
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- Herausgeber: Wiley-VCH
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Systematically examining current methods and strategies, this ready reference covers a wide range of molecular structures, from organic-chemical drugs to peptides, Proteins and nucleic acids, in line with emerging new drug classes derived from biomacromolecules.
A leader in the field and one of the pioneers of this young discipline has assembled here the most prominent experts from across the world to provide first-hand knowledge. While most of their methods and examples come from the area of pharmaceutical discovery and development, the approaches are equally applicable for chemical probes and diagnostics, pesticides, and any other molecule designed to interact with a biological system. Numerous images and screenshots illustrate the many examples and method descriptions.
With its broad and balanced coverage, this will be the firststop resource not only for medicinal chemists, biochemists and biotechnologists, but equally for bioinformaticians and molecular designers for many years to come.
From the content:
* Reaction-driven de novo design
* Adaptive methods in molecular design
* Design of ligands against multitarget profiles
* Free energy methods in ligand design
* Fragment-based de novo design
* Automated design of focused and target family-oriented compound libraries
* Molecular de novo design by nature-inspired computing
* 3D QSAR approaches to de novo drug design
* Bioisosteres in de novo design
* De novo design of peptides, proteins and nucleic acid structures, including RNA aptamers
and many more.
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Seitenzahl: 1069
Veröffentlichungsjahr: 2013
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Table of Contents
Related Titles
Title Page
Copyright
List of Contributors
Foreword
Preface
Chapter 1: De Novo Design: From Models to Molecules
1.1 Molecular Representation
1.2 The Molecular Design Cycle
1.3 Receptor–Ligand Interaction
1.4 Modeling Fitness Landscapes
1.5 Strategies for Compound Construction
1.6 Strategies for Compound Scoring
1.7 Flashback Forward: A Brief History of De Novo Drug Design
1.8 Conclusions
Acknowledgments
References
Chapter 2: Coping with Complexity in Molecular Design
2.1 Introduction
2.2 A Simple Model of Molecular Interactions
2.3 Enhancements to the Simple Complexity Model
2.4 Enumerating and Sampling the Complexity of Chemical Space
2.5 Validation of the Complexity Model
2.6 Reductionism and Drug Design
2.7 Complexity and Information Content as a Factor in De Novo Design
2.8 Complexity of Thermodynamic Entropy and Drug Design
2.9 Complex Systems, Emergent Behavior, and Molecular Design
Acknowledgments
References
Chapter 3: The Human Pocketome
3.1 Predicted Pockets
3.2 Compilation of the Validated Human Pocketome
3.3 Diversity and Redundancy of the Human Pocketome
3.4 Compound Activity Prediction by Ligand-Pocket Docking and Scoring
3.5 Pocketome-Derived 3D Chemical Fields as Activity Prediction Models
3.6 Clustering the Ligands by Function and Subpockets
3.7 Conclusions
Acknowledgments
References
Chapter 4: Structure-Based De Novo Drug Design
4.1 Introduction
4.2 Current Progress in SBDND Methodologies
4.3 Recent Applications of Structure-Based De Novo Design
4.4 Perspectives and Conclusion
Acknowledgment
References
Chapter 5: De Novo Design by Fragment Growing and Docking
5.1 Introduction
5.2 Case Study I: High-Throughput Screening with Dr Feils
5.3 Case Study II: Fragment-Based Drug Design with Dr Goode
5.4 Conclusion
Disclaimer
Acknowledgments
References
Chapter 6: Hit and Lead Identification from Fragments
6.1 Introduction to FBDD
6.2 Fragment Library Design Incorporating Computational Methods
6.3 Fragment Screening
6.4 Fragment Prioritization for Optimization
6.5 Fragment Hit Expansion and Fragment Evolution
6.6 Fragment Merging Principles
6.7 Fragment Linking Principles
6.8 Fragment-Assisted Drug Discovery (FADD)
6.9 Conclusion
Acknowledgments
References
Chapter 7: Pharmacophore-Based De Novo Design
7.1 Introduction
7.2 A Summary of the Algorithms of PhDD v1.0
7.3 An Introduction to the Modifications in the Updated Version of PhDD (v2.0)
7.4 Validation of PhDD
7.5 Concluding Remarks
Acknowledgment
References
Chapter 8: 3D-QSAR Approaches to De Novo Drug Design
8.1 Introduction
8.2 Current Methods
8.3 Leapfrog
8.4 Recent Advances
8.5 Conclusions
Acknowledgments
References
Chapter 9: Ligand-Based Molecular Design Using Pseudoreceptors
9.1 Introduction
9.2 Pseudoreceptor Algorithms
9.3 Successful Applications Overview
9.4 Conclusions
Acknowledgments
References
Chapter 10: Reaction-Driven De Novo Design: a Keystone for Automated Design of Target Family-Oriented Libraries
10.1 Introduction
10.2 Reaction-Driven Design: Tackling the Problem of Synthetic Feasibility
10.3 Successful Applications of Reaction-Driven De Novo Design
10.4 Reaction-Driven Design of Chemical Libraries Addressing Target Families
10.5 Conclusions
References
Chapter 11: Multiobjective De Novo Design of Synthetically Accessible Compounds
11.1 Introduction
11.2 Design of Synthetically Accessible Compounds
11.3 Synthetic Accessibility Using Reaction Vectors
11.4 De Novo Design Using Evolutionary Algorithms
11.5 Conclusions
Acknowledgments
References
Chapter 12: De Novo Design of Ligands against Multitarget Profiles
12.1 Introduction
12.2 Automating the Creativity of Ligand Design
12.3 Evolutionary Algorithm
12.4 Experimental Validation
12.5 Reducing Antitarget Activity
12.6 Optimizing D4 Receptor Potency
12.7 Designing Novel Ligands to a Defined Profile
12.8 Conclusion
Acknowledgments
References
Chapter 13: Construction of Drug-Like Compounds by Markov Chains
13.1 Introduction
13.2 FOG Algorithm and Library Generation
13.3 Applications
13.4 Conclusion
Acknowledgments
References
Chapter 14: Coping with Combinatorial Space in Molecular Design
14.1 Introduction
14.2 Chemical Space
14.3 Combinatorial Space
14.4 Visualization
14.5 Conclusion
References
Chapter 15: Fragment-Based Design of Focused Compound Libraries
15.1 Introduction
15.2 General Workflow
15.3 Fragment Space
15.4 Query
15.5 FTrees Fragment Space Search
15.6 Scaffold Selection
15.7 Design of Focused Libraries
15.8 Application Example
15.9 Summary and Conclusions
Acknowledgments
References
Chapter 16: Free Energy Methods in Ligand Design
16.1 Free Energy (FE) Methods in Lead Optimization (LO)
16.2 The Variety of In Silico Binding Affinity Methods
16.3 The Choice of a Method for Calculating Binding FE
16.4 Experimental Data
16.5 Current Issues
16.6 Practical Examples
16.7 Miscellaneous Issues
16.8 Best Practices
16.9 Conclusions and Outlook
Acknowledgments
Abbreviations
References
Chapter 17: Bioisosteres in De Novo Design
17.1 Introduction
17.2 History of Isosterism and Bioisosterism
17.3 Methods for Bioisosteric Replacement
17.4 Exemplar Applications
17.5 Conclusions
Acknowledgments
References
Chapter 18: Peptide Design by Nature-Inspired Algorithms
18.1 Template-Based Design
18.2 Nature-Inspired Optimization
18.3 Worked Example: De Novo Design of MHC-I Binding Peptides by Ant Colony Optimization
18.4 Chemical Modification
18.5 Conclusions and Outlook
Acknowledgments
References
Chapter 19: De Novo Computational Protein Design
19.1 Introduction
19.2 Elements of Computational Protein Design
19.3 Efforts in Theoretically Guided Protein Design
19.4 Conclusion
Acknowledgments
References
Chapter 20: De Novo Design of Nucleic Acid Structures
20.1 Introduction
20.2 DNA-Branched Structures
20.3 Scaffolded DNA Origami Design
20.4 Alternative DNA Designs: between Junctions and Origami
20.5 Conclusions
Acknowledgments
References
Chapter 21: RNA Aptamer Design
21.1 Aptamers and Design
21.2 Riboswitches and Aptamers
21.3 SELEX
21.4 Speeding Up SELEX by Computational Methods
21.5 Structures and Probing Methods
21.6 Functional Analyses (In Vitro and In Vivo)
21.7 Problems
21.8 Future Perspectives
References
Index
Related Titles
Brown, N. (ed.)
Scaffold Hopping in Medicinal Chemistry
2014
ISBN: 978-3-527-33364-6
(also available in digital formats)
Hoffmann, R., Gohier, A., Pospisil, P. (eds.)
Data Mining in Drug Discovery
2014
ISBN: 978-3-527-32984-7
(also available in digital formats)
Brown, N. (ed.)
Bioisosteres in Medicinal Chemistry
2012
ISBN: 978-3-527-33015-7
(also available in digital formats)
Sotriffer, C. (ed.)
Virtual Screening
Principles, Challenges, and Practical Guidelines
2011
ISBN: 978-3-527-32636-5
(also available in digital formats)
Comba, P. (ed.)
Modeling of Molecular Properties
2011
ISBN: 978-3-527-33021-8
(also available in digital formats)
Matta, Chérif F. (ed.)
Quantum Biochemistry
2010
ISBN: 978-3-527-32322-7
(also available in digital formats)
Schneider, G., Baringhaus, K.-H
Molecular Design
Concepts and Applications
2008
ISBN: 978-3-527-31432-4
Editor
Prof. Gisbert Schneider
ETH Zürich
Institute of Pharmaceutical Sciences
Wolfgang-Pauli-Strasse 10
8093 Zürich
Switzerland
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: 978-3-527-33461-2
ePDF ISBN: 978-3-527-67700-9
ePub ISBN: 978-3-527-67703-0
Mobi ISBN: 978-3-527-67702-3
oBook ISBN: 978-3-527-67701-6
List of Contributors
Foreword
The history of de novo drug design, which is concerned primarily with the use of computers to design new active drug compounds, may as well be called the history of computer-aided drug design (CADD). Quantitative structure–activity relationship (QSAR) studies were a prominent feature of the drug design process until the second half of the 1980s. QSAR studies provide an effective technique for analyzing the correlations between molecular structure and biological activity, and can still be used as a powerful approach during the lead optimization phase of a drug discovery program. For the purposes of lead generation, however, QSAR studies cannot be used, for example, to design a molecule with a different molecular skeleton.
To overcome these issues, de novo drug design was introduced in the 1990s. Although a variety of different de novo drug design software suites have been developed, they are invariably difficult to at the practical level for real drug design. It is noteworthy that successful examples of drug design using these tools could not be found during those early days, and the use and general perception of de novo drug design consequently went into decline following its peak usage in the mid-1990s. This decline in the use of de novo drug design was attributed to scientists focusing on the magnitude of the computational binding strength with the target receptor, while ignoring the drug-like properties and the synthetic tractability of the designed compounds.
Following of from the pivot role of CADD in in silico virtual screening, de novo drug design has reappeared in the form of lead hopping or scaffold hopping during the first half of the 2000s. This reappearance owes a lot to the compound libraries generated using combinatorial chemistry and chemoinformatics technologies. The recent progress of de novo drug design was reviewed by Prof Schneider [1], where 36 kinds of software were classified according to their methodology. Furthermore, in a review by Prof Kunchukian [2], the 20 latest types of software were comprehensively added. According to Kunchukian's count, the number of the reports published every year from 2005 through 2008 increased by five to six reports until it eventually doubled in 2009. The numbers then continued to increase at the same pace afterward. The big difference in the recent popularity of de novo drug design relative to its initial release in the 1990s relates to the number of research reports in which the compounds designed on the computer were actually synthesized and evaluated. This shows that the use of de novo drug design software for drug development spot has reached a practical level. Interestingly, there are now more de novo drug design software suites available than there are in silico virtual screening programs. That is, the technology of de novo drug design is not fixed and the software has many advantages and disadvantages. In other words, de novo drug design has a hidden potential for further developments.
The number of possible combination of atoms in organic compounds (chemical space) is vast, and the number is said to be the sixtieth power of 10. De novo drug design is a combination of optimization problem that enables the user to find the most promising compound out of this vast chemical space. A variety of different optimization algorithms have been devised, including the evolutionary algorithm, Monte Carlo simulation, taboo search, depth-first search, breadth-first search, and the A* algorithm. As de novo drug design software adopts various algorithms, the software is flooded with many candidates.
Taken against this background, the publication of this special edition of “De novo Molecular Design” appears to be particularly timely. This book itself is dedicated to the concepts and ideas for de novo drug design. The potentials and limitations of the relevant techniques are critically discussed and comprehensively exemplified in 21 chapters by distinguished authors from both academia and the pharmaceutical industry. A series of well-defined chapters follow the first exciting and challenging chapter, “De novo design: from models to molecules”, with examples including structure-, fragment-, pharmacophore-, QSAR-, reaction-, polypharmacology-, combinatorial-, and biosteric-based de novo designs. As a scientist keen to recommend the use of de novo drug design in the drug discovery process, I am convinced that readers will be able to successfully apply these de novo design methods to their own drug design projects and produce many innovative compounds for the pharmaceutical drug market. It is my central hope that this book will be helpful and be used in the same way as an encyclopedia when hints and ideas are needed during the drug design process.
Tokyo, April 2013
Prof Kimito Funatsu
Department of Chemical System Engineering
The University of Tokyo, Tokyo, Japan
References
1. Schneider, G. and Fechner, U. (2005) Computer-based de novo design of drug-like molecules. Nat. Rev. Drug Discov., 4, 649–663.
2. Kutchukian, P.S. and Shakhnovich, E.I. (2010) De novo design: balancing novelty and confined chemical space. Expert Opin. Drug Discov., 5, 789–812.
Preface
This book builds on the legacy of many bright minds. It does not claim completeness or truth. Its intention merely is to inspire readers to critically and creatively explore the possibilities of de novo molecular design for drug discovery and chemical biology. I am most grateful to all authors for contributing truly exciting 21 chapters. Their willingness and thoroughness allowed us to compile a formidable collection of ideas and reports on the various aspects of computer-assisted molecular design. Special thanks go to Prof Kimito Funatsu, who shares his thoughts on de novo design in the Foreword. I am equally grateful to my colleagues who agreed to act as impartial reviewers, and through their personal advice helped me not to go over the top. My beloved wife was very lenient toward me during the preparation of this volume (and not just then). Dr Heike Nöthe and Dr Frank Weinreich from Wiley-VCH did a great job supporting me in the editing process and ensured swift and professional book production. Persistent challenge by my research team at ETH helped me focus on some tough scientific questions and come up with hopefully useful answers.
This book starts off with a general overview of the scientific pillars of molecular design. In the subsequent chapters, renowned experts from industry and academia alike provide their views on the drug discovery process and the role of de novo design, receptor- and ligand-based approaches, the nature of macromolecular structure and ligand–receptor interaction, chemical space navigation, combinatorial- and fragment-based design principles, rigorous physical approaches to solve the scoring problem in drug design, and the automated generation of bioactive peptides, proteins, and nucleic acids as potential drugs of the future. I have structured the contributions so that they are attuned to one another and demonstrate the various ideas and technological concepts in a well-defined collation. This book is meant to be read from cover to cover. Nevertheless, all chapters stand on their own, and the interested reader may cherry-pick favorites. Consequently, slight redundancy of contents was unavoidable and has intentionally been kept to ensure that each chapter represents the authors' individual views on a topic, and at the same time allows the reader to learn about different thoughts and opinions.
As I have had the great privilege to witness the rise of computer-assisted de novo design from its humble beginnings to become mainstream science, I am pleased to see these fascinating techniques now being broadly applied in drug discovery and chemical biology. There is still much more to come and to expect from the amalgamation of technologies and complementary scientific thinking. I am convinced that only by constantly keeping an open mind for surprising fresh ideas and unexpected revelations will we be able to make continuous progress in molecular design. This also means that some of our “old beliefs” might need a critical overhaul, and some should better be discarded to make way for new and improved concepts that will enable researchers to conceive of innovative algorithms for molecule construction, scoring, and chemical space navigation.
Zürich, April 2013
Gisbert Schneider
Chapter 1
De Novo Design: From Models to Molecules
Gisbert Schneider and Karl-Heinz Baringhaus
Form ever follows function, and this is the law.
Where function does not change, form does not change.
Louis Sullivan, American architect (1896) [1]
Innovative bioactive agents fuel sustained drug discovery and the development of new medicines. Future success in chemical biology and pharmaceutical research alike will fundamentally rely on the combination of advanced synthetic and analytical technologies that are embedded in a theoretical framework that provides a rationale for the interplay between chemical structure and biological effect. A driving role in this setting falls on leading edge concepts in computer-assisted molecular design, by providing access to a virtually infinite source of novel druglike compounds and guiding experimental screening campaigns. In this chapter, we present concepts and ideas for the representation of molecular structure, suggest predictive models of structure–activity relationships, and discuss approaches that have proved their usefulness and will contribute to future drug discovery by generating innovative bioactive agents. We also highlight some of the current prohibitive aspects of fully automated de novo design that will require attention for future methodological breakthroughs. This chapter provides an introduction to important pillars of de novo drug design, whereas the subsequent contributions presented in this book offer in-depth treatments of current trends, methods, and approaches together with numerous practical examples. We are confident that the reading will inspire.
1.1 Molecular Representation
Ever since the first atomic models of molecules have been conceived, scientists have used such models, and their associated concepts and language, to come up with innovative chemical agents that possess sought properties [2]. So far, we tend to think of a molecule in terms of sticks and balls when it comes to visualize chemical structure. No doubt, simplistic representations have their justification for describing certain aspects of molecular constitution, configuration, and conformation and provide an intuitive access to “molecular architecture” (Figure 1.1). However, they fall far short of relating functional aspects to the objects we recognize as molecules. In the end, it is the desired function we wish to get from a molecular structure. “Form follows function” – this credo of modern architecture and industrial design is equally valid for molecular design, in particular in medicinal chemistry and chemical biology striving for new chemical entities (NCEs) as biologically active lead compounds and eventually future drugs.
Figure 1.1 Atomic models of molecular structure as depicted in John Dalton's seminal book entitled (1808). Panel (a) presents the “arbitrary signs chosen to represent the several chemical elements or ultimate particles.” Panel (b) might be considered as an early molecular design study, as it depicts Dalton's view of various arrangements of water molecules. Note the similarity between these archaic philosophies and contemporary molecular models.
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