3D QSAR in Drug Design


Book Description

Progress in medicinal chemistry and in drug design depends on our ability to understand the interactions of drugs with their biological targets. Classical QSAR studies describe biological activity in terms of physicochemical properties of substituents in certain positions of the drug molecules. The purpose of this book is twofold: On the one hand, both the novice and the experienced user will be introduced to the theory and application of 3D QSAR analyses, and on the other, a comprehensive overview of the scope and limitations of these methods is given. The detailed discussion of the present state of the art should enable scientists to further develop and improve these powerful new tools. The greater part of the book is dedicated to the theoretical background of 3D QSAR and to a discussion of CoMFA applications. In addition, various other 3D QSAR approaches and some CoMFA-related methods are described in detail. Thus, the book should be valuable for medicinal, agricultural and theoretical chemists, biochemists and biologists, as well as for other scientists interested in drug design. Its content, starting at a very elementary level and proceeding to the latest methodological results, the strengths and limitations of 3D QSAR approaches, makes the book also appropriate as a text for teaching and for graduate student courses.




3D QSAR in Drug Design


Book Description

Significant progress has been made in the study of three-dimensional quantitative structure-activity relationships (3D QSAR) since the first publication by Richard Cramer in 1988 and the first volume in the series, 3D QSAR in Drug Design. Theory, Methods and Applications, published in 1993. The aim of that early book was to contribute to the understanding and the further application of CoMFA and related approaches and to facilitate the appropriate use of these methods. Since then, hundreds of papers have appeared using the quickly developing techniques of both 3D QSAR and computational sciences to study a broad variety of biological problems. Again the editor(s) felt that the time had come to solicit reviews on published and new viewpoints to document the state of the art of 3D QSAR in its broadest definition and to provide visions of where new techniques will emerge or new appli- tions may be found. The intention is not only to highlight new ideas but also to show the shortcomings, inaccuracies, and abuses of the methods. We hope this book will enable others to separate trivial from visionary approaches and me-too methodology from in- vative techniques. These concerns guided our choice of contributors. To our delight, our call for papers elicited a great many manuscripts.




Three Dimensional QSAR


Book Description

As a result of new statistical and mathematical approaches, improved visualization tools, and recognition by international regulatory groups, quantitative structure-activity relationships (QSARs) now play important roles in pharmacology for the design of new drugs as well as in toxicology and ecotoxicology for hazard identification and risk assessm




3D QSAR in Drug Design


Book Description

Volumes 2 and 3 of the 3D QSAR in Drug Design series aim to review the progress being made in CoMFA and other 3D QSAR approaches since the publication of the highly successful first volume about four years ago. Volume 2 (Ligand-Protein Interactions and Molecular Similarity) divides into three sections dealing with Ligand-Protein Interactions, Quantum Chemical Models and Molecular Dynamics Simulations, and Pharmacophore Modelling and Molecular Similarity, respectively. Volume 3 (Recent Advances) is also divided into three sections, namely 3D QSAR Methodology: CoMFA and Related Approaches, Receptor Models and Other 3D QSAR Approaches, and 3D QSAR Applications. More than seventy distinguished scientists have contributed nearly forty reviews of their work and related research to these two volumes which are of outstanding quality and timeliness. These works present an up-to-date coverage of the latest developments in all fields of 3D QSAR.




Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment


Book Description

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




Statistical Modelling of Molecular Descriptors in QSAR/QSPR


Book Description

This handbook and ready reference presents a combination of statistical, information-theoretic, and data analysis methods to meet the challenge of designing empirical models involving molecular descriptors within bioinformatics. The topics range from investigating information processing in chemical and biological networks to studying statistical and information-theoretic techniques for analyzing chemical structures to employing data analysis and machine learning techniques for QSAR/QSPR. The high-profile international author and editor team ensures excellent coverage of the topic, making this a must-have for everyone working in chemoinformatics and structure-oriented drug design.




3D QSAR in Drug Design


Book Description

Significant progress has been made in the study of three-dimensional quantitative structure-activity relationships (3D QSAR) since the first publication by Richard Cramer in 1988 and the first volume in the series. 3D QSAR in Drug Design. Theory, Methods and Applications, published in 1993. The aim of that early book was to contribute to the understanding and the further application of CoMFA and related approaches and to facilitate the appropriate use of these methods. Since then, hundreds of papers have appeared using the quickly developing techniques of both 3D QSAR and computational sciences to study a broad variety of biological problems. Again the editor(s) felt that the time had come to solicit reviews on published and new viewpoints to document the state of the art of 3D QSAR in its broadest definition and to provide visions of where new techniques will emerge or new appli- tions may be found. The intention is not only to highlight new ideas but also to show the shortcomings, inaccuracies, and abuses of the methods. We hope this book will enable others to separate trivial from visionary approaches and me-too methodology from in- vative techniques. These concerns guided our choice of contributors. To our delight, our call for papers elicited a great many manuscripts.







Advances in QSAR Modeling


Book Description

The book covers theoretical background and methodology as well as all current applications of Quantitative Structure-Activity Relationships (QSAR). Written by an international group of recognized researchers, this edited volume discusses applications of QSAR in multiple disciplines such as chemistry, pharmacy, environmental and agricultural sciences addressing data gaps and modern regulatory requirements. Additionally, the applications of QSAR in food science and nanoscience have been included – two areas which have only recently been able to exploit this versatile tool. This timely addition to the series is aimed at graduate students, academics and industrial scientists interested in the latest advances and applications of QSAR.