Computer Aided Drug Design Cadd From Ligand Based Methods To Structure Based Approaches

Computer-Aided Drug Design (CADD): From Ligand-Based Methods to Structure-Based Approaches outlines the basic theoretical principles, methodologies and applications of different fundamental and advanced CADD approaches and techniques. Including information on current protocols as well as recent developments in the computational methods, tools and techniques used for rational drug design, the book explains the fundamental aspects of CADD, combining this with a practical understanding of the various in silico approaches used in modern drug discovery processes to assess the field in a comprehensive and systematic manner. Providing up-to-date, information and guidance for scientists, researchers, students and teachers, the book helps readers address specific academic and research related problems using illustrative explanations, examples and case studies, which are systematically reviewed. Highlights in silico approaches to drug design and discovery using computational tools and techniques Details ligand-based and structure-based drug design in a comprehensive and systematic approach Summarizes recent developments in computational drug design strategy as novel approaches of rational drug designing

Structure-based (SBDD) and ligand-based (LBDD) drug design are extremely important and active areas of research in both the academic and commercial realms. This book provides a complete snapshot of the field of computer-aided drug design and associated experimental approaches. Topics covered include X-ray crystallography, NMR, fragment-based drug design, free energy methods, docking and scoring, linear-scaling quantum calculations, QSAR, pharmacophore methods, computational ADME-Tox, and drug discovery case studies. A variety of authors from academic and commercial institutions all over the world have contributed to this book, which is illustrated with more than 200 images. This is the only book to cover the subject of structure and ligand-based drug design, and it provides the most up-to-date information on a wide range of topics for the practising computational chemist, medicinal chemist, or structural biologist. Professor Kenneth Merz has been selected as the recipient of the 2010 ACS Award for Computers in Chemical & Pharmaceutical Research that recognizes the advances he has made in the use of quantum mechanics to solve biological and drug discovery problems.

Molecular Docking for Computer-Aided Drug Design: Fundamentals, Techniques, Resources and Applications offers in-depth coverage on the use of molecular docking for drug design. The book is divided into three main sections that cover basic techniques, tools, web servers and applications. It is an essential reference for students and researchers involved in drug design and discovery. Covers the latest information and state-of-the-art trends in structure-based drug design methodologies Includes case studies that complement learning Consolidates fundamental concepts and current practice of molecular docking into one convenient resource

Designing and developing new drugs is an expensive and time-consuming process, and there is a need to discover new tools or approaches that can optimize this process. Applied Computer-Aided Drug Design: Models and Methods compiles information about the main advances in computational tools for discovering new drugs in a simple and accessible language for academic students to early career researchers. The book aims to help readers understand how to discover molecules with therapeutic potential by bringing essential information about the subject into one volume. Key Features · Presents the concepts and evolution of classical techniques, up to the use of modern methods based on computational chemistry in accessible format. · Gives a primer on structure- and ligand-based drug design and their predictive capacity to discover new drugs. · Explains theoretical fundamentals and applications of computer-aided drug design. · Focuses on a range of applications of the computations tools, such as molecular docking; molecular dynamics simulations; homology modeling, pharmacophore modeling, quantitative structure-activity relationships (QSAR), density functional theory (DFT), fragment-based drug design (FBDD), and free energy perturbation (FEP). · Includes scientific reference for advanced readers Readership Students, teachers and early career researchers.

This book provides up-to-date information on bioinformatics tools for the discovery and development of new drug molecules. It discusses a range of computational applications, including three-dimensional modeling of protein structures, protein-ligand docking, and molecular dynamics simulation of protein-ligand complexes for identifying desirable drug candidates. It also explores computational approaches for identifying potential drug targets and for pharmacophore modeling. Moreover, it presents structure- and ligand-based drug design tools to optimize known drugs and guide the design of new molecules. The book also describes methods for identifying small-molecule binding pockets in proteins, and summarizes the databases used to explore the essential properties of drugs, drug-like small molecules and their targets. In addition, the book highlights various tools to predict the absorption, distribution, metabolism, excretion (ADME) and toxicity (T) of potential drug candidates. Lastly, it reviews in silico tools that can facilitate vaccine design and discusses their limitations.

Modern drug discovery and design programs use computer aided drug discovery (CADD) for identifying and optimizing bioactive compounds used for developing new drugs. It is also known by alternative terms such as in-silico pharmacology and computational therapeutics. CADD approaches are vital in identifying viable drug candidates at a low cost. These approaches are usually divided into two types, namely, structure-based and ligand-based drug design approaches. Both these approaches are used to identify suitable lead molecules. These computational methods are useful for reducing the use of animal models in pharmacological research, assisting in the rational design of novel and safe drug candidates, repositioning marketed drugs, and assisting medicinal chemists and pharmacologists throughout the drug discovery process. This book is a compilation of chapters that discuss the most vital concepts and emerging trends in the usage of computers for drug discovery and design. It will provide comprehensive knowledge to the readers.

The Ernst Schering Research Foundation sponsored its 15th workshop in Berlin on October 19-21, 1994. Leading scientists from Europe and North America were invited to discuss computer-aided drug design in industrial research. Computer-aided drug design is a very exciting field and an intellec tual challenge, like playing chess. But these reasons are no longer suf ficient to justify using this method in industry, if they ever were. Fig. 1. The participants of the workshop VI Preface Therefore, when we, together with Prof. Hoyer, started to think about this workshop, our intentions quickly became clear. We were not so much interested in the very latest developments of methods or in computer-aided drug design itself - enough conferences have dealt with these topics. However, we were very interested in the usefulness and limitations of computer-aided drug design in the indu strial research process. A lot has changed in the pharmaceutical industry recently. These changes are gaining momentum, so it is the right time to think about the role of computer-aided drug design in this changing environment.

This book presents various computer-aided drug discovery methods for the design and development of ligand and structure-based drug molecules. A wide variety of computational approaches are now being used in various stages of drug discovery and development, as well as in clinical studies. Yet, despite the rapid advances in computer software and hardware, combined with the exponential growth in the available biological information, there are many challenges that still need to be addressed, as this book shows. In turn, it shares valuable insights into receptor-ligand interactions in connection with various biological functions and human diseases. The book discusses a wide range of phylogenetic methods and highlights the applications of Molecular Dynamics Simulation in the drug discovery process. It also explores the application of quantum mechanics in order to provide better accuracy when calculating protein-ligand binding interactions and predicting binding affinities. In closing, the book provides illustrative descriptions of major challenges associated with computer-aided drug discovery for the development of therapeutic drugs. Given its scope, it offers a valuable asset for life sciences researchers, medicinal chemists and bioinformaticians looking for the latest information on computer-aided methodologies for drug development, together with their applications in drug discovery.