There are numerous excellent reviews on fragment-based drug discovery (FBDD), but there are to date no hand-holding guides or protocols with which one can embark on this orthogonal approach to complement traditional high throughput screening methodologies. This Methods in Enzymology volume offers the tools, practical approaches, and hit-to-lead examples on how to conduct FBDD screens. The chapters in this volume cover methods that have proven to be successful in generating leads from fragments, including chapters on how to apply computational techniques, nuclear magnetic resonance, surface plasma resonance, thermal shift and binding assays, protein crystallography, and medicinal chemistry in FBDD. Also elaborated by experienced researchers in FBDD are sample preparations of fragments, proteins, and GPCR as well as examples of how to generate leads from hits. Offers the tools, practical approaches, and hit-to-lead examples on how to conduct FBDD screens The chapters in this volume cover methods that have proven to be successful in generating leads from fragments, including chapters on how to apply computational techniques, nuclear magnetic resonance, surface plasma resonance, thermal shift and binding assays, protein crystallography, and medicinal chemistry in FBDD

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.

The book "Drug Selectivity - An Evolving Concept in Medicinal Chemistry" provides a current overview and comprehensive compilation for medicinal chemists that discusses the effects of aiming for multiple targets on the entire drug development process. The result is a broad survey of current and future strategies for drug selectivity in medicinal chemistry with theoretical but also practical aspects. Different strategies are presented and evaluated, such as various design approaches, merged multiple ligands, discovery technologies and a broad range of successful examples of unselective drugs taken from all major disease areas. With its wide-ranging view of an emerging new paradigm in drug development, this handbook is of prime importance for every medicinal and pharmaceutical chemist.

Introducing the most recent advances in crystallography, nuclear magnetic resonance, molecular modeling techniques, and computational combinatorial chemistry, this unique, interdisciplinary reference explains the application of three-dimensional structural information in the design of pharmaceutical drugs. Furnishing authoritative analyses by world-renowned experts, Structure-Based Drug Design discusses protein structure-based design in optimizing HIV protease inhibitors and details the biochemical, genetic, and clinical data on HIV-1 reverse transcriptase presents recent results on the high-resolution three-dimensional structure of the catalytic core domain of HIV-1 integrase as a foundation for divergent combination therapy focuses on structure-based design strategies for uncovering receptor antagonists to treat inflammatory diseases demonstrates a systematic approach to the design of inhibitory compounds in cancer treatment reviews current knowledge on the Interleukin-1 (IL-1) system and progress in the development of IL-1 modulators describes the influence of structure-based methods in designing capsid-binding inhibitors for relief of the common cold and much more!

Over the past years, the chem(o)informatics field has further evolved and new application areas have opened up, for example, in the broadly defined area of chemical biology. In Chemoinformatics and Computational Chemical Biology, leading investigators bring together a detailed series of reviews and methods including, among others, system-directed approaches using small molecules, the design of target-focused compound libraries, the study of molecular selectivity, and the systematic analysis of target-ligand interactions. Furthermore, the book delves into similarity methods, machine learning, probabilistic approaches, fragment-based methods, as well as topics that go beyond the current chemoinformatics spectrum, such as knowledge-based modeling of G protein-coupled receptor structures and computational design of siRNA libraries. As a volume in the highly successful Methods in Molecular BiologyTM series, this collection provides detailed descriptions and implementation advice that are exceedingly relevant for basic researchers and practitioners in this highly interdisciplinary research and development area. Cutting-edge and unambiguous, Chemoinformatics and Computational Chemical Biology serves as an ideal guide for experts and newcomers alike to this vital and dynamic field of study.

Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment describes the historical evolution of quantitative structure-activity relationship (QSAR) approaches and their fundamental principles. This book includes clear, introductory coverage of the statistical methods applied in QSAR and new QSAR techniques, such as HQSAR and G-QSAR. Containing real-world examples that illustrate important methodologies, this book identifies QSAR as a valuable tool for many different applications, including drug discovery, predictive toxicology and risk assessment. Written in a straightforward and engaging manner, this is the ideal resource for all those looking for general and practical knowledge of QSAR methods. - Includes numerous practical examples related to QSAR methods and applications - Follows the Organization for Economic Co-operation and Development principles for QSAR model development - Discusses related techniques such as structure-based design and the combination of structure- and ligand-based design tools