Molecular Design: Concepts And Applications

Description:
This first introductory-level textbook on the design of small molecules is written with the first-time user in mind. Aimed at students and scientists alike, it uses computer-based methods to design and analyze such small molecules as drugs, enzyme inhibitors, probes and markers for biomolecules. Both authors have extensive practical experience of modeling and design and share their knowledge of what can and cannot be done with computer-assisted design. Divided into four sections, the book begins with a look at molecular objects and design objectives, including molecular geometry, properties, recognition and dynamics. Two further sections deal with virtual synthesis and screening, while the final section covers navigation in chemical space. The result is a textbook that takes the modeler one step further, to the de novo design of functional molecules. With its study questions at the end of each learning unit, this is equally suitable for teaching and self-learning.

Review:
'[The] authors are leading experts in the field with extensive practical experience. They provide insight into what can be achieved by computer-assisted design through proper modelling approaches.' (International Journal of Bioautomation, April 2009) 'This is an excellent book to gain a basic understanding of molecular design... The collection of topics is generally well chosen, and many literature references are given, it is a very good starting point for entering the field. Compared to many multi-author compilations, the book is easy to read, because of the excellent writing style combined with many high-quality figures and numerous examples. For including molecular design as a part of life science course, it is certainly an excellent choice.' (Angewandte Chemie, February 2009) 'Molecular Design is very easy to read and contains many useful illustrations. The authors have done an admirable job of simply explaining a complex and rapidly evolving field to a wide and varied audience. For that reason this timely volume will be valuable to chemistry and life science graduate students, experienced medicinal chemists, and bioinformaticians for both an introductory entry point and a useful reference work.' (Journal of Medicinal Chemistry, November 13, 2008) 'This book provides a brilliant first access to the interdisciplinary field of molecular design. ...a 'must have'.' (Journal of Chemical Information and Modeling)

Table of Contents:
Foreword. Preface. 1 Molecular Objects and Design Objectives. 1.1 What is a Molecule? 1.2 Simplistic Molecular Representations. 1.3 The Molecular Surface. 1.4 Molecular Shape. 1.5 The Topological Molecular Graph. 1.6 Molecular Properties and Graph Invariants. 1.7 The Drug-likeness Concept. 1.8 Scaffolds, Linkers, and Side-chains. 1.9 Substructure Similarity and 'Privileged Motifs'. 1.10 Molecules as Strings. 1.11 Constructing Molecules from Strings. 1.12 From Elements to Atom Types. 1.13 Entering the Third Dimension: Automatic Conformer Generation. 1.14 The 'Bioactive' Conformation. Literature. 2 Receptor-Ligand Interaction. 2.1 The Thermodynamics of Protein-Ligand Interaction. 2.2 The Entropic Contribution. 2.3 From Theory to Experiment: Ki and IC50. 2.4 QSAR: Estimating Quantitative Structure-Activity Relationships. 2.4.1 Free-Wilson Analysis. 2.4.2 The Hansch Model. 2.4.3 3D-QSAR. 2.5 Types of Receptor-Ligand Interaction. 2.6 The 'Biophore' Concept. 2.7 Potential Pharmacophoric Points. 2.8 The Correlation Vector Approach to Pharmacophore Modeling. 2.9 'Hard Sphere' and 'Fuzzy' Pharmacophore Models. 2.10 Lessons from Automated Ligand Docking and Scoring: What Works and What Does Not. 2.11 Fits Like a Glove: Alternative Ligand Binding Modes and Induced Fit Effects. Literature. 3 Creating the Design. 3.1 Why We Need Computer-assisted Molecular Design. 3.2 The Number of Drug Targets is Limited. 3.3 Ligand Binding Sites. 3.4 Ligand-based Design of Compound Libraries. 3.5 Similar Compounds Do Not Necessarily Interact with Their Target in Similar Ways. 3.6 The Same Ligand Can Adopt Multiple Binding Modes. 3.7 GPCRs Represent a Challenging Target Family. 3.8 Natural Products Are a Source of Inspiration. 3.9 Transition State Analogs Are Potent Enzyme Inhibitors. 3.10 New Targets Sometimes Require a New Ligand Design Concept. 3.11 De novo Design Concepts. 3.12 Primary and Secondary Constraints in de novo Design. Literature. 4 Virtual Screening Triage. 4.1 The Drug Discovery Pipeline. 4.2 High-throughput Screening (HTS): Why Is It Successful? 4.3 From Hit to Lead. 4.4 Rationalizing the Design Process. 4.5 From High to Low Diversity. 4.6 Quantifying Diversity is Difficult. 4.7 From Negative Design to Positive Design. 4.8 Watch Out for Frequent Hitters! 4.9 Shape-matching: A Coarse-grained Filtering Step. 4.10 The Ultimate Goal: Scaffold-hopping. 4.11 Assessing Chemotype Diversity in Focused Libraries. 4.12 It Works! Examples of Successful Scaffold-hops Found by Virtual Screening. 4.13 Case Studies. 4.13.1 Design of Kv1.5 Ion Channel Modulators. 4.13.2 Virtual Screening of a Natural-product-derived Combinatorial Library for Novel 5-Lipoxygenase Inhibitors. 4.13.3 Scaffold de novo Design for Cannabinoid-1 (CB-1) Receptor Ligands. Literature. 5 Secondary Design Constraints and Machine Learning. 5.1 Physicochemistry and Pharmacokinetics. 5.2 The 'Rule of 5'. 5.3 Pharmacokinetics. 5.4 Absorption. 5.5 Distribution. 5.6 Metabolism. 5.7 Elimination. 5.8 Toxicity. 5.9 Prodrugs and Bioisosteres. 5.10 Machine Learning Methods Support Lead Finding and Optimization. 5.11 An Important Step: Data Scaling. 5.12 Application of Machine Learning to Compound Library Design. 5.13 A 'Pharmacophore Road Map'. 5.14 Case Studies. 5.14.1 Predicting Cross-activities of Allosteric Modulators of Metabotropic Glutamate Receptors (mGluR). 5.14.2 Dopamine D3 Antagonists and ACE Inhibitors. 5.14.3 An Artificial Ant System for Combinatorial Optimization. Literature. Subject Index.

Author Biography:
Gisbert Schneider is Professor for Chemoinformatics and Bioinformatics at the University of Frankfurt (Germany). He studied Biochemistry, Medicine and Computer Science at the University of Berlin where he also obtained his PhD. He spent postdoctoral terms at the MIT in Cambridge, in Stockholm and Frankfurt before joining Hoffmann-La Roche in Basel. After five years in pharmaceutical research, he became the first Beilstein Professor for Chemoinformatics at the University of Franfurt. In 2006 he won the title 'Professor of the Year' in the annual national contest run by the journal 'Unicum'. Karl-Heinz Baringhaus is the Head of Computational Chemistry at Aventis Pharma in Frankfurt (Germany). He studied Chemistry at the University of M? where he also obtained his PhD degree. After a postdoctoral term at Stanford University he joined the Hoechst AG, where he was appointed head of Molecular Modeling and Computational Chemistry.