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

Author: Kunal Roy
Publisher: Academic Press
ISBN: 0128016337
Format: PDF
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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

Quantitative Structure Activity Relationships in Drug Design Predictive Toxicology and Risk Assessment

Author: Roy, Kunal
Publisher: IGI Global
ISBN: 1466681373
Format: PDF, Mobi
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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.

Advances in QSAR modeling

Author: Kunal Roy
Publisher: Springer
ISBN: 3319568507
Format: PDF, ePub
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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.

Computational Toxicology

Author: Sean Ekins
Publisher: John Wiley & Sons
ISBN: 1119282586
Format: PDF, ePub, Docs
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A key resource for toxicologists across a broad spectrum of fields, this book offers a comprehensive analysis of molecular modelling approaches and strategies applied to risk assessment for pharmaceutical and environmental chemicals. • Provides a perspective of what is currently achievable with computational toxicology and a view to future developments • Helps readers overcome questions of data sources, curation, treatment, and how to model / interpret critical endpoints that support 21st century hazard assessment • Assembles cutting-edge concepts and leading authors into a unique and powerful single-source reference • Includes in-depth looks at QSAR models, physicochemical drug properties, structure-based drug targeting, chemical mixture assessments, and environmental modeling • Features coverage about consumer product safety assessment and chemical defense along with chapters on open source toxicology and big data

Computational Toxicology

Author: Bruce A. Fowler
Publisher: Academic Press
ISBN: 012396508X
Format: PDF, ePub, Docs
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Computational Toxicology: Methods and Applications for Risk Assessment is an essential reference on the translation of computational toxicology data into information that can be used for more informed risk assessment decision-making. This book is authored by leading international investigators who have real-world experience in relating computational toxicology methods to risk assessment. Key topics of interest include QSAR modeling, chemical mixtures, applications to metabolomic and metabonomic data sets, toxicogenomic analyses, applications to REACH informational strategies and much more. The examples provided in this book are based on cutting-edge technologies and set out to stimulate the further development of this promising field to offer rapid, better and more cost-effective answers to major public health concerns. Authored by leading international researchers engaged in cutting-edge applications of computational methods for translating complex toxicological data sets into useful risk assessment information Incorporates real-world examples of how computational toxicological methods have been applied to advance the science of risk assessment Provides the framework necessary for new technologies and fosters common vocabularies and principles upon which the effects of new chemical entities should be compared

In Silico Toxicology

Author: Mark Cronin
Publisher: Royal Society of Chemistry
ISBN: 1849732094
Format: PDF, ePub
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In Silico methods to predict toxicity have become increasingly important recently, particularly in light of European legislation such as REACH and the Cosmetics Regulation. They are also being used extensively worldwide e.g. in the USA, Canada, Japan and Australia. In assessing the risk that a chemical may pose to human health or to the environment, focus is now being directed towards exploitation of in silico methods to replace in vivo or in vitro techniques. A prediction of potential toxicity requires several stages: 1) Collation and organisation of data available for the compound, or if this is not available, information for related compounds. 2) An assessment of the quality of the data. 3) Generation of additional information about the compound using computational techniques at various levels of complexity - calculation of physico-chemical properties, 2-D, 3-D / MO descriptors and specific receptor modelling / interaction. 4) Use of an appropriate strategy to predict toxicity - ie a statistically valid method which makes best use of all available information (mechanism of action, activity for related compounds, extrapolation across species and endpoints, likely exposure scenario amounts over time etc). 5) Consideration then needs to be given to how this information is used in the real world ie use of expert systems / tools as relevant to assessors (if sufficiently different to previous) - weight of evidence approaches. 6) Finally evidence should be presented from case studies within this area. No other publication brings together information on all of these areas in one book and this publication is unique in that it provides a logical progression through every one of these key stages and defines the use of computational approaches to predict the environmental toxicity and human health effects of organic chemicals. The volume is aimed at the developers and users of in silico toxicology and provides an analysis of all aspects required for in silico prediction of toxicology, including data collation, quality assessment and computational approaches. The contributions from recognised leaders in each of these areas include evidence of the use and applicability of approaches using real world case studies concerning both environmental and human health effects. The book provides a very useful single source reference for people working in this area including academics, professionals, under- and post-graduate students as well as Governmental Regulatory Scientists involved in chemical risk assessment and REACH.

A Primer on QSAR QSPR Modeling

Author: Kunal Roy
Publisher: Springer
ISBN: 3319172816
Format: PDF, ePub, Mobi
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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.

Three Dimensional QSAR

Author: Jean Pierre Doucet
Publisher: CRC Press
ISBN: 1420091166
Format: PDF, ePub, Docs
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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 assessment. Providing up-to-date coverage of the field, Three Dimensional QSAR: Applications in Pharmacology and Toxicology presents the most recent QSAR methods and illustrates their scope, advantages, and limitations. Part I The first part of the book addresses CoMFA and related methods, such as CoMSIA, FLUFF, SOMFA. It also describes shape-, surface-, and volume-based approaches, including MSA, excluded volume, LIV, HASL, receptor surface model, COMPASS, and CoMSA. Part II Focusing on methods that use 3D information, the second part covers autocorrelation methods, such as GRIND; similarity-based methods, including similarity matrices and quantum similarity indices; and quantitative spectroscopic data–activity relationships. Some applications in data mining are also explored. Part III The third part deals with post-3D models. The authors discuss the adaptation of the receptor and simultaneous presence of several conformers or solvation mechanisms. Part IV The final part presents receptor-related approaches as well as docking and free energy calculations, which are treated at various levels. This part concerns the extensive sampling of phase space and approximate methods, such as linear interaction energy, Poisson–Boltzmann, and generalized Born models. A case study covering several parallel approaches is also developed. An appendix offers the basic principles of modeling and statistical tools routinely required in QSAR methodologies, including optimization methods, molecular mechanics and dynamics, multivariate analysis, nonlinear models, and evolutionary techniques. It provides newcomers with the concepts necessary to fully grasp the essentials of these methods and gives a basic grounding in their correct use. Illustrated with numerous examples and a color insert, this book supplies a clear overview of the strengths and weaknesses of 3D-QSAR approaches. It explains how these modern techniques can link the biological activity of chemicals to their structure, encompassing both their 2D structural formulae and 3D geometry.

Computational Modeling of Drugs Against Alzheimer s Disease

Author: Kunal Roy
Publisher: Humana Press
ISBN: 9781493974030
Format: PDF, ePub
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This volume describes different computational methods encompassing ligand-based approaches (QSAR, pharmcophore), structure-based approaches (homology modeling, docking, molecular dynamics simulation), and combined approaches (virtual screening) with applications in anti-Alzheimer drug design. Different background topics like molecular etiologies of Alzheimer’s disease, targets for new drug development, and different cheminformatic modeling strategies are covered for completeness. Special topics like multi-target drug development, natural products, protein misfolding, and nanomaterials are also included in connection with computational modeling of anti-Alzheimer drug development. In Neuromethods series style, chapters include the kind of detail and key advice from the specialists needed to get successful results in your laboratory. Cutting-edge and authoritative, Computational Modeling of Drugs Against Alzheimer’s Disease is a valuable resource for learning about the latest computational techniques used to study this disease.

Drug Like Properties

Author: Li Di
Publisher: Academic Press
ISBN: 0128013222
Format: PDF
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Of the thousands of novel compounds that a drug discovery project team invents and that bind to the therapeutic target, only a fraction have sufficient ADME (absorption, distribution, metabolism, elimination) properties, and acceptable toxicology properties, to become a drug product that will successfully complete human Phase I clinical trials. Drug-Like Properties: Concepts, Structure Design and Methods from ADME to Toxicity Optimization, Second Edition, provides scientists and students the background and tools to understand, discover, and develop optimal clinical candidates. This valuable resource explores physiochemical properties, including solubility and permeability, before exploring how compounds are absorbed, distributed, and metabolized safely and stably. Review chapters provide context and underscore the importance of key concepts such as pharmacokinetics, toxicity, the blood-brain barrier, diagnosing drug limitations, prodrugs, and formulation. Building on those foundations, this thoroughly updated revision covers a wide variety of current methods for the screening (high throughput), diagnosis (medium throughput) and in-depth (low throughput) analysis of drug properties for process and product improvement. From conducting key assays for interpretation and structural analysis, the reader learns to implement modification methods and improve each ADME property. Through valuable case studies, structure-property relationship descriptions, and structure modification strategies, Drug-Like Properties, Second Edition, offers tools and methods for ADME/Tox scientists through all aspects of drug research, discovery, design, development, and optimization. Provides a comprehensive and valuable working handbook for scientists and students in medicinal chemistry Includes expanded coverage of pharmacokinetics fundamentals and effects Contains updates throughout, including the authors’ recent work in the importance of solubility in drug development; new and currently used property methods, with a reduction of seldom-used methods; and exploration of computational modeling methods