Qsar
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| Author | : Kunal Roy |
| Publisher | : Academic Press |
| Total Pages | : 494 |
| Release | : 2015-03-03 |
| Genre | : Medical |
| ISBN | : 0128016337 |
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
| Author | : Kunal Roy |
| Publisher | : Springer |
| Total Pages | : 129 |
| Release | : 2015-04-11 |
| Genre | : Science |
| ISBN | : 3319172816 |
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.
| Author | : Hugo Kubinyi |
| Publisher | : John Wiley & Sons |
| Total Pages | : 252 |
| Release | : 2008-07-11 |
| Genre | : Science |
| ISBN | : 3527616837 |
Finding the new remedy for a certain disease: an inspired goal. QSAR, an invaluable tool in drug design, aids scientists to attain this aim. This book is a long-awaited comprehensive text to QSAR and related approaches. It provides a practice-oriented introduction to the theory, methods and analyses for QSAR relationships, including modelling-based and 3D approaches. Hugo Kubinyi is a leading expert in QSAR. Readers will benefit from the author's 20 years of practical experience, from his careful calculations and recalculations of thousands of QSAR equations. Among the topics covered are: - physiocochemical parameters - quantitative models - statistical methods - Hansch analysis - Free Wilson analysis - 3D-QSAR approaches The book can readily be used as a textbook due to its high didactic value and numerous examples (over 200 equations and 1100 references).
| Author | : Hugo Kubinyi |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 413 |
| Release | : 1998-04-30 |
| Genre | : Medical |
| ISBN | : 0792347900 |
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.
| Author | : Tomasz Puzyn |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 428 |
| Release | : 2010-01-19 |
| Genre | : Science |
| ISBN | : 1402097832 |
This book presents an interdisciplinary overview on the most recent advances in QSAR studies. The first part consists of a comprehensive review of QSAR methodology. The second part highlights the interdisciplinary aspects and new areas of QSAR modelling.
| Author | : James Devillers |
| Publisher | : Academic Press |
| Total Pages | : 309 |
| Release | : 1996-08-09 |
| Genre | : Technology & Engineering |
| ISBN | : 0080537383 |
Comprehensive and impeccably edited, Neural Networks in QSAR and Drug Design is the first book to present an all-inclusive coverage of the topic. The book provides a practice-oriented introduction to the different neural network paradigms, allowing the reader to easily understand and reproduce the results demonstrated. Numerous examples are detailed, demonstrating a variety of applications to QSAR and drug design.The contributors include some of the most distinguished names in the field, and the book provides an exhaustive bibliography, guiding readers to all the literature related to a particular type of application or neural network paradigm. The extensive index acts as a guide to the book, and makes retrieving information from chapters an easy task. A further research aid is a list of software with indications of availablility and price, as well as the editors scale rating the ease of use and interest/price ratio of each software package. The presentation of new, powerful tools for modeling molecular properties and the inclusion of many important neural network paradigms, coupled with extensive reference aids, makes Neural Networks in QSAR and Drug Design an essential reference source for those on the frontiers of this field. - Presents the first coverage of neural networks in QSAR and Drug Design - Allows easy understanding and reproduction of the results described within - Includes an exhaustive bibliography with more than 200 references - Provides a list of applicable software packages with availability and price
| Author | : Kunal Roy |
| Publisher | : Springer |
| Total Pages | : 555 |
| Release | : 2017-05-22 |
| Genre | : Science |
| ISBN | : 3319568507 |
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.
| Author | : Matthias Dehmer |
| Publisher | : John Wiley & Sons |
| Total Pages | : 437 |
| Release | : 2012-09-13 |
| Genre | : Medical |
| ISBN | : 3527645012 |
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.
| Author | : H. Timmerman |
| Publisher | : Elsevier |
| Total Pages | : 509 |
| Release | : 1995-11-20 |
| Genre | : Computers |
| ISBN | : 0080545009 |
Based on topics presented at the Annual Japanese (Quantitative) Structure-Activity Relationship Symposium and the Biennial China-Japan Drug Design and Development conference, the topics in this volume cover almost every procedure and subdiscipline in the SAR discipline.They are categorized in three sections. Section one includes topics illustrating newer methodologies relating to ligand-receptor, molecular graphics and receptor modelling as well as the three-dimensional (Q)SAR examples with the active analogue approach and the comparative molecular field analysis. In section 2 the hydrophobicity parameters, log P (1-octanol/water) for compound series of medicinal-chemical interest are analysed physico-organic chemically. Section 3 contains the examples based on the traditional Hansch QSAR approach.A variety of methodologies and procedures are presented in this single volume, along with their methodological philosophies.
| Author | : Roy, Kunal |
| Publisher | : IGI Global |
| Total Pages | : 727 |
| Release | : 2015-02-28 |
| Genre | : Technology & Engineering |
| ISBN | : 1466681373 |
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.
