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Quantitative structure-activity relationships (QSARs) represent predictive models derived from the application of statistical tools correlating biological activity or other properties of chemicals with descriptors representative of molecular structure and/or property. Quantitative Structure-Activity Relationships in Drug Design, Predictive Toxicology, and Risk Assessment discusses recent advancements in the field of QSARs with special reference to their application in drug development, predictive toxicology, and chemical risk analysis. Focusing on emerging research in the field, this book is an ideal reference source for industry professionals, students, and academicians in the fields of medicinal chemistry and toxicology.
The object of this series is to provide interesting and timely reviews covering all aspects of the field. It is our hope that this will encourage the transfer of new methods, techniques, and parameterizations from the field in which they were developed to other areas that can make good use of them.·Quantitative Structure Property Relationships (QSPR) have developed into a major method of chemical research in many scientific disciplines·Provides much needed cross fertilization between disciplines researching QSPR
This brief goes back to basics and describes the Quantitative structure-activity/property relationships (QSARs/QSPRs) that represent predictive models derived from the application of statistical tools correlating biological activity (including therapeutic and toxic) and properties of chemicals (drugs/toxicants/environmental pollutants) with descriptors representative of molecular structure and/or properties. It explains how the sub-discipline of Cheminformatics is used for many applications such as risk assessment, toxicity prediction, property prediction and regulatory decisions apart from drug discovery and lead optimization. The authors also present, in basic terms, how QSARs and related chemometric tools are extensively involved in medicinal chemistry, environmental chemistry and agricultural chemistry for ranking of potential compounds and prioritizing experiments. At present, there is no standard or introductory publication available that introduces this important topic to students of chemistry and pharmacy. With this in mind, the authors have carefully compiled this brief in order to provide a thorough and painless introduction to the fundamental concepts of QSAR/QSPR modelling. The brief is aimed at novice readers.
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
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.
Quantitative structure property relationships (QSPR) have become a major method of chemical research. In the course of this development the field has suffered from fragmentation. Applications of QSPR are found in all major chemical disciplines including physical organic, physical, medicinal, agricultural, biological, enviromental, and polymer chemistry. Frequently workers in one area are unaware of parameterizations and models used in other ares which they might well find useful. The is a common thread which runs through these widely diverse areas. The basic principles, parameterizations and methodology are the same or similar throughout. The object of this series is to provide interesting and timely reviews covering all aspects of the field. It encourages the transfer of new methods, techniques, and parameterizations from the area in which they were developed to other areas that can make good use of them. In view of the widespread use of QSPR we believe that this is an important objective. This series will provide the cross-fertilization which is sorely needed.
The book, which is related to QSAR in sciences, is divided into five main chapters. The first chapter is the Introductory chapter. The second chapter aims to provide an update of the recent advances in the field of rational design of PDE inhibitors. The third chapter includes designing a series of peptidic inhibitors that possessed a substrate transition-state analog and evaluating the structure-activity relationship of the designed inhibitors, based on docking and scoring, using the docking simulation software Molecular Operating Environment. The aim of the forth chapter is to develop structure-property relationships for the qualitative and quantitative prediction of the reverse-phase liquid chromatographic retention times of chlorogenic acids. The final chapter aims to determine the model of interactions between the natural compounds with anti-inflammatory molecular target by molecular docking analysis.
More than 20 years of experience in molecular structure generation, from conceptualization through to applications Innovative, interdisciplinary text demonstrating example queries with software packages such as MOLGEN-online Detailed explanations on establishing QSPRs and QSARs as well as structure elucidation using mass spectrometry and structure generation. Aims and Scope This work provides an introduction to mathematical modeling of molecules and the resulting applications (structure generation, structure elucidation, QSAR/QSPR etc.). Most chemists have experimented with some software that represents molecules in an electronic form, and such models and applications are of increasing interest in diverse and growing fields such as drug discovery, environmental science and metabolomics. Furthermore, structure generation remains the only way to systematically create molecules that are not (yet) present in a database. This book starts with the mathematical theory behind representing molecules, explaining chemical concepts in mathematical terms and providing exercises that can be completed online. The later chapters cover applications of the theory, with detailed explanations on QSPR and QSAR investigations and finally structure elucidation combining mass spectrometry and structure generation. This book is aimed in particular at the users of structure generation methods and corresponding techniques, but also for those interested in teaching and learning mathematical chemistry, and for software designers in chemoinformatics.
Mathematical Physics in Theoretical Chemistry deals with important topics in theoretical and computational chemistry. Topics covered include density functional theory, computational methods in biological chemistry, and Hartree-Fock methods. As the second volume in the Developments in Physical & Theoretical Chemistry series, this volume further highlights the major advances and developments in research, also serving as a basis for advanced study. With a multidisciplinary and encompassing structure guided by a highly experienced editor, the series is designed to enable researchers in both academia and industry stay abreast of developments in physical and theoretical chemistry. - Brings together the most important aspects and recent advances in theoretical and computational chemistry - Covers computational methods for small molecules, density-functional methods, and computational chemistry on personal and quantum computers - Presents cutting-edge developments in theoretical and computational chemistry that are applicable to graduate students and research professionals in chemistry, physics, materials science and biochemistry