|Author||: Om Silakari,Pankaj Kumar Singh|
|Publisher||: Academic Press|
|Release Date||: 2020-11-05|
|ISBN 10||: 0128205474|
|Pages||: 396 pages|
Concepts and Experimental Protocols of Modelling and Informatics in Drug Design discusses each experimental protocol utilized in the field of bioinformatics, focusing especially on computer modeling for drug development. It helps the user in understanding the field of computer-aided molecular modeling (CAMM) by presenting solved exercises and examples. The book discusses topics such as fundamentals of molecular modeling, QSAR model generation, protein databases and how to use them to select and analyze protein structure, and pharmacophore modeling for drug targets. Additionally, it discusses data retrieval system, molecular surfaces, and freeware and online servers. The book is a valuable source for graduate students and researchers on bioinformatics, molecular modeling, biotechnology and several members of biomedical field who need to understand more about computer-aided molecular modeling. Presents exercises with solutions to aid readers in validating their own protocol Brings a thorough interpretation of results of each exercise to help readers compare them to their own study Explains each parameter utilized in the algorithms to help readers understand and manipulate various features of molecules and target protein to design their study
|Author||: Michael Lutz,Terry Kenakin|
|Publisher||: John Wiley & Sons|
|Release Date||: 2000-01-10|
|ISBN 10||: 9780471988618|
|Pages||: 428 pages|
Quantitative Molecular Pharmacology and Informatics in Drug Discovery Michael Lutz, Section Head, Cheminformatics Group and Terry Kenakin, Principal Research Scientist, Glaxo Wellcome Research and Development, Research Triangle Park, NC, USA Quantitative Molecular Pharmacology and Informatics in Drug Discovery combines pharmacology, genetics and statistics to provide a complete guide to the modern drug discovery process. The book discusses the pharmacology of drug testing and provides a detailed description of the statistical methods used to analyze the resulting data. Application of genetic and genomic tools for identification of biological targets is reviewed in the context of drug discovery projects. Covering both the theoretical principles upon which the techniques are based and the practicalities of drug discovery, this informative guide. * outlines in step-by-step detail the advantages and disadvantages of each technology and approach and links these to the type of chemical target being sought after in the drug discovery process; and, * provides excellent demonstrations of how to use powerful pharmacological and statistical tools to optimize high-throughput screening assays. Written by two internationally known and well-regarded experts, this book is an essential reference for research and development scientists working in the pharmaceutical and biotechnology industries. It will also be useful for postgraduates studying pharmacology and applied statistics.
Discover how biomarkers can boost the success rate of drugdevelopment efforts As pharmaceutical companies struggle to improve the success rateand cost-effectiveness of the drug development process, biomarkershave emerged as a valuable tool. This book synthesizes and reviewsthe latest efforts to identify, develop, and integrate biomarkersas a key strategy in translational medicine and the drugdevelopment process. Filled with case studies, the bookdemonstrates how biomarkers can improve drug development timelines,lower costs, facilitate better compound selection, reducelate-stage attrition, and open the door to personalizedmedicine. Biomarkers in Drug Development is divided into eightparts: Part One offers an overview of biomarkers and their role in drugdevelopment. Part Two highlights important technologies to help researchersidentify new biomarkers. Part Three examines the characterization and validation processfor both drugs and diagnostics, and provides practical advice onappropriate statistical methods to ensure that biomarkers fulfilltheir intended purpose. Parts Four through Six examine the application of biomarkers indiscovery, preclinical safety assessment, clinical trials, andtranslational medicine. Part Seven focuses on lessons learned and the practical aspectsof implementing biomarkers in drug development programs. Part Eight explores future trends and issues, including dataintegration, personalized medicine, and ethical concerns. Each of the thirty-eight chapters was contributed by one or moreleading experts, including scientists from biotechnology andpharmaceutical firms, academia, and the U.S. Food and DrugAdministration. Their contributions offer pharmaceutical andclinical researchers the most up-to-date understanding of thestrategies used for and applications of biomarkers in drugdevelopment.
This handbook provides the first-ever inside view of today's integrated approach to rational drug design. Chemoinformatics experts from large pharmaceutical companies, as well as from chemoinformatics service providers and from academia demonstrate what can be achieved today by harnessing the power of computational methods for the drug discovery process. With the user rather than the developer of chemoinformatics software in mind, this book describes the successful application of computational tools to real-life problems and presents solution strategies to commonly encountered problems. It shows how almost every step of the drug discovery pipeline can be optimized and accelerated by using chemoinformatics tools -- from the management of compound databases to targeted combinatorial synthesis, virtual screening and efficient hit-to-lead transition. An invaluable resource for drug developers and medicinal chemists in academia and industry.
|Author||: Adriano D. Andricopulo,Leonardo L. G. Ferreira|
|Publisher||: Frontiers Media SA|
|Release Date||: 2019-02-05|
|ISBN 10||: 2889457443|
|Pages||: 329 pages|
Chemoinformatics is paramount to current drug discovery. Structure- and ligand-based drug design strategies have been used to uncover hidden patterns in large amounts of data, and to disclose the molecular aspects underlying ligand-receptor interactions. This Research Topic aims to share with a broad audience the most recent trends in the use of chemoinformatics in drug design. To that end, experts in all areas of drug discovery have made their knowledge available through a series of articles that report state-of-the-art approaches. Readers are provided with outstanding contributions focusing on a wide variety of topics which will be of great value to those interested in the many different and exciting facets of drug design.
Chemoinformatics is broadly a scientific discipline encompassing the design, creation, organization, management, retrieval, analysis, dissemination, visualization and use of chemical information. It is distinct from other computational molecular modeling approaches in that it uses unique representations of chemical structures in the form of multiple chemical descriptors; has its own metrics for defining similarity and diversity of chemical compound libraries; and applies a wide array of statistical, data mining and machine learning techniques to very large collections of chemical compounds in order to establish robust relationships between chemical structure and its physical or biological properties. Chemoinformatics addresses a broad range of problems in chemistry and biology; however, the most commonly known applications of chemoinformatics approaches have been arguably in the area of drug discovery where chemoinformatics tools have played a central role in the analysis and interpretation of structure-property data collected by the means of modern high throughput screening. Early stages in modern drug discovery often involved screening small molecules for their effects on a selected protein target or a model of a biological pathway. In the past fifteen years, innovative technologies that enable rapid synthesis and high throughput screening of large libraries of compounds have been adopted in almost all major pharmaceutical and biotech companies. As a result, there has been a huge increase in the number of compounds available on a routine basis to quickly screen for novel drug candidates against new targets/pathways. In contrast, such technologies have rarely become available to the academic research community, thus limiting its ability to conduct large scale chemical genetics or chemical genomics research. However, the landscape of publicly available experimental data collection methods for chemoinformatics has changed dramatically in very recent years. The term "virtual screening" is commonly associated with methodologies that rely on the explicit knowledge of three-dimensional structure of the target protein to identify potential bioactive compounds. Traditional docking protocols and scoring functions rely on explicitly defined three dimensional coordinates and standard definitions of atom types of both receptors and ligands. Albeit reasonably accurate in many cases, conventional structure based virtual screening approaches are relatively computationally inefficient, which has precluded them from screening really large compound collections. Significant progress has been achieved over many years of research in developing many structure based virtual screening approaches. This book is the first monograph that summarizes innovative applications of efficient chemoinformatics approaches towards the goal of screening large chemical libraries. The focus on virtual screening expands chemoinformatics beyond its traditional boundaries as a synthetic and data-analytical area of research towards its recognition as a predictive and decision support scientific discipline. The approaches discussed by the contributors to the monograph rely on chemoinformatics concepts such as: -representation of molecules using multiple descriptors of chemical structures -advanced chemical similarity calculations in multidimensional descriptor spaces -the use of advanced machine learning and data mining approaches for building quantitative and predictive structure activity models -the use of chemoinformatics methodologies for the analysis of drug-likeness and property prediction -the emerging trend on combining chemoinformatics and bioinformatics concepts in structure based drug discovery The chapters of the book are organized in a logical flow that a typical chemoinformatics project would follow - from structure representation and comparison to data analysis and model building to applications of structure-property relationship models for hit identification and chemical library design. It opens with the overview of modern methods of compounds library design, followed by a chapter devoted to molecular similarity analysis. Four sections describe virtual screening based on the using of molecular fragments, 2D pharmacophores and 3D pharmacophores. Application of fuzzy pharmacophores for libraries design is the subject of the next chapter followed by a chapter dealing with QSAR studies based on local molecular parameters. Probabilistic approaches based on 2D descriptors in assessment of biological activities are also described with an overview of the modern methods and software for ADME prediction. The book ends with a chapter describing the new approach of coding the receptor binding sites and their respective ligands in multidimensional chemical descriptor space that affords an interesting and efficient alternative to traditional docking and screening techniques. Ligand-based approaches, which are in the focus of this work, are more computationally efficient compared to structure-based virtual screening and there are very few books related to modern developments in this field. The focus on extending the experiences accumulated in traditional areas of chemoinformatics research such as Quantitative Structure Activity Relationships (QSAR) or chemical similarity searching towards virtual screening make the theme of this monograph essential reading for researchers in the area of computer-aided drug discovery. However, due to its generic data-analytical focus there will be a growing application of chemoinformatics approaches in multiple areas of chemical and biological research such as synthesis planning, nanotechnology, proteomics, physical and analytical chemistry and chemical genomics.
|Author||: C. Gopi Mohan|
|Release Date||: 2019-01-10|
|ISBN 10||: 3030052826|
|Pages||: 406 pages|
This book reviews the advances and challenges of structure-based drug design in the preclinical drug discovery process, addressing various diseases, including malaria, tuberculosis and cancer. Written by internationally recognized researchers, this edited book discusses how the application of the various in-silico techniques, such as molecular docking, virtual screening, pharmacophore modeling, molecular dynamics simulations, and residue interaction networks offers insights into pharmacologically active novel molecular entities. It presents a clear concept of the molecular mechanism of different drug targets and explores methods to help understand drug resistance. In addition, it includes chapters dedicated to natural-product- derived medicines, combinatorial drug discovery, the CryoEM technique for structure-based drug design and big data in drug discovery. The book offers an invaluable resource for graduate and postgraduate students, as well as for researchers in academic and industrial laboratories working in the areas of chemoinformatics, medicinal and pharmaceutical chemistry and pharmacoinformatics.
Since the first attempts at structure-based drug design about four decades ago, molecular modelling techniques for drug design have developed enormously, along with the increasing computational power and structural and biological information of active compounds and potential target molecules. Nowadays, molecular modeling can be considered to be an integral component of the modern drug discovery and development toolbox. Nevertheless, there are still many methodological challenges to be overcome in the application of molecular modeling approaches to drug discovery. The eight original research and five review articles collected in this book provide a snapshot of the state-of-the-art of molecular modeling in drug design, illustrating recent advances and critically discussing important challenges. The topics covered include virtual screening and pharmacophore modelling, chemoinformatic applications of artificial intelligence and machine learning, molecular dynamics simulation and enhanced sampling to investigate contributions of molecular flexibility to drug–receptor interactions, the modeling of drug–receptor solvation, hydrogen bonding and polarization, and drug design against protein–protein interfaces and membrane protein receptors.
Unique work on structure-based drug design, covering multiple aspects of drug discovery and development. Fully colored, many images, computer animations of 3D structures (these only in electronic form). Makes the spatial aspects of interacting molecules clear to the reader, covers multiple applications and methods in drug design. Structures by mode of action, no therapeutic areas. Of high relevance for academia and industrial research. Focus on gene technology in drug design, omics-technologies computational methods experimental techniques of structure determination multiple examples on mode of action of current drugs, ADME-tox properties in drug development, QSAR methods, combinatorial chemistry, biologicals, ribosome, targeting protein-protein interfaces.
This book is not going to be an exhaustive survey covering all aspects of rational drug design. Instead, it is going to provide critical know-how through real-world examples. Relevant case studies will be presented and analyzed to illustrate the following: how to optimize a lead compound whether one has high or low levels of structural information; how to derive hits from competitors’ active compounds or from natural ligands of the targets; how to springboard from competitors’ SAR knowledge in lead optimization; how to design a ligand to interfere with protein-protein interactions by correctly examining the PPI interface; how to circumvent IP blockage using data mining; how to construct and fully utilize a knowledge-based molecular descriptor system; how to build a reliable QSAR model by focusing on data quality and proper selection of molecular descriptors and statistical approaches. A Practical Guide to Rational Drug Design focuses on computational drug design, with only basic coverage of biology and chemistry issues, such as assay design, target validation and synthetic routes. Discusses various tactics applicable to daily drug design Readers can download the materials used in the book, including structures, scripts, raw data, protocols, and codes, making this book suitable resource for short courses or workshops Offers a unique viewpoint on drug discovery research due to the author’s cross-discipline education background Explores the author’s rich experiences in both pharmaceutical and academic settings
|Author||: Joanna Kołodziej,Horacio González-Vélez|
|Release Date||: 2019-03-25|
|ISBN 10||: 3030162729|
|Pages||: 352 pages|
This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications.
This book serves as an introduction to advanced research topics related to molecular modeling, chemoinformatics, bioinformatics, and pharmacoinformatics. It functions as a text for post-graduate level students as well as a reference for researchers. Both fundamentals and recent research applications are included in the book. Topics related to molecular modeling (QSAR, molecular docking, pharmacophore mapping, etc.), chemoinformatics, bioinformatics, and pharmacoinformatics are treated as new technologies; meaning there is an introduction and description of the advantages and disadvantages of these methodologies.
This important new book provides innovative material, including peer-reviewed chapters and survey articles on new applied research and development, in the scientifically important field of QSAR in medicinal chemistry. QSAR is a growing field because available computing power is continuously increasing, QSAR’s potential is enormous, limited only by the quantity and quality of the available experimental input, which are also continuously improving. The number of possible structures for the design of new organic compounds is difficult to imagine, and QSAR helps to predict their activities even before synthesis. The book provides a wealth of valuable information and: • Presents an overview of recent developments in QSAR methodologies along with a brief history of QSAR • Covers the available web resource tools and in silico techniques used in virtual screening and drug discovery processes, compiling an extensive review of web resources in the following categories: databases related to chemical compounds, drug targets, and ADME/toxicity prediction; molecular modeling and drug designing; virtual screening; pharmacophore generation; molecular descriptor calculation software; software for quantum mechanics; ligand binding affinities (docking); and software related to ADME/toxicity prediction • Reviews the rm2 as a more stringent measure for the assessment of model predictivity compared to traditional validation metrics, being specifically important since validation is a crucial step in any QSAR study • Presents linear model improvement techniques that take into account the conformation flexibility of the modeled molecules • Summarizes the building processes of four different pharmacophore models: common-feature, 3D-QSAR, protein-, and protein-ligand complexes • Shows the role of different conceptual density functional theory based chemical reactivity descriptors, such as hardness, electrophilicity, net electrophilicity, and philicity in the design of different QSAR/QSPR/QSTR models • Reviews the use of chemometrics in PPAR research highlighting its substantial contribution in identifying essential structural characteristics and understanding the mechanism of action • Presents the structures and QSARs of antimicrobial and immunosuppressive cyclopeptides, discussing the balance of antimicrobial and haemolytic activities for designing new antimicrobial cyclic peptides • Shows the relationship between DFT global descriptors and experimental toxicity of a selected group of polychlorinated biphenyls, exploring the efficacy of three DFT descriptors • Reviews the applications of Quantitative Structure-Relative Sweetness Relationships (QSRSR), showing that the last decade was marked by an increase in the number of studies regarding QSAR applications for both understanding the sweetness mechanism and synthesizing novel sweetener compounds for the food additive industry The wide coverage makes this book an excellent reference for those in chemistry, pharmacology, and medicine as well as for research centers, governmental organizations, pharmaceutical companies, and health and environmental control organizations.
|Author||: Andrew Bush,Diana Bilton,Margaret Hodson|
|Publisher||: CRC Press|
|Release Date||: 2015-07-02|
|ISBN 10||: 0340764252|
|Pages||: 699 pages|
Hodson and Geddes' Cystic Fibrosis provides everything the respiratory clinician, pulmonologist or health professional treating patients needs in a single manageable volume. This international and authoritative work brings together current knowledge and has become established in previous editions as a leading reference in the field. This fourth edition includes a wealth of new information, figures, useful videos, and a companion eBook. The basic science that underlies the disease and its progression is outlined in detail and put into a clinical context. Diagnostic and clinical aspects are covered in depth, as well as promising advances such as gene therapies and other novel molecular based treatments. Patient monitoring and the importance of multidisciplinary care are also emphasized. This edition: Features accessible sections reflecting the multidisciplinary nature of the cystic fibrosis care team Contains a chapter written by patients and families about their experiences with the disease Includes expanded coverage of clinical areas, including chapters covering sleep, lung mechanics and the work of breathing, upper airway disease, insulin deficiency and diabetes, bone disease, and sexual and reproductive issues Discusses management both in the hospital and at home Includes a new section on monitoring and discusses the use of databases to improve patient care Covers monitoring in different age groups, exercise testing and the outcomes of clinical trials in these areas Includes chapters devoted to nursing, physiotherapy, psychology, and palliative and spiritual care Throughout, the emphasis is on providing an up-to-date and balanced review of both the clinical and basic science aspects of the subject and reflecting the multidisciplinary nature of the cystic fibrosis care team.
Helps you choose the right computational tools and techniques to meet your drug design goals Computational Drug Design covers all of the major computational drug design techniques in use today, focusing on the process that pharmaceutical chemists employ to design a new drug molecule. The discussions of which computational tools to use and when and how to use them are all based on typical pharmaceutical industry drug design processes. Following an introduction, the book is divided into three parts: Part One, The Drug Design Process, sets forth a variety of design processes suitable for a number of different drug development scenarios and drug targets. The author demonstrates how computational techniques are typically used during the design process, helping readers choose the best computational tools to meet their goals. Part Two, Computational Tools and Techniques, offers a series of chapters, each one dedicated to a single computational technique. Readers discover the strengths and weaknesses of each technique. Moreover, the book tabulates comparative accuracy studies, giving readers an unbiased comparison of all the available techniques. Part Three, Related Topics, addresses new, emerging, and complementary technologies, including bioinformatics, simulations at the cellular and organ level, synthesis route prediction, proteomics, and prodrug approaches. The book's accompanying CD-ROM, a special feature, offers graphics of the molecular structures and dynamic reactions discussed in the book as well as demos from computational drug design software companies. Computational Drug Design is ideal for both students and professionals in drug design, helping them choose and take full advantage of the best computational tools available. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.
30 tutorials and more than 100 exercises in chemoinformatics, supported by online software and data sets Chemoinformatics is widely used in both academic and industrial chemical and biochemical research worldwide. Yet, until this unique guide, there were no books offering practical exercises in chemoinformatics methods. Tutorials in Chemoinformatics contains more than 100 exercises in 30 tutorials exploring key topics and methods in the field. It takes an applied approach to the subject with a strong emphasis on problem-solving and computational methodologies. Each tutorial is self-contained and contains exercises for students to work through using a variety of software packages. The majority of the tutorials are divided into three sections devoted to theoretical background, algorithm description and software applications, respectively, with the latter section providing step-by-step software instructions. Throughout, three types of software tools are used: in-house programs developed by the authors, open-source programs and commercial programs which are available for free or at a modest cost to academics. The in-house software and data sets are available on a dedicated companion website. Key topics and methods covered in Tutorials in Chemoinformatics include: Data curation and standardization Development and use of chemical databases Structure encoding by molecular descriptors, text strings and binary fingerprints The design of diverse and focused libraries Chemical data analysis and visualization Structure-property/activity modeling (QSAR/QSPR) Ensemble modeling approaches, including bagging, boosting, stacking and random subspaces 3D pharmacophores modeling and pharmacological profiling using shape analysis Protein-ligand docking Implementation of algorithms in a high-level programming language Tutorials in Chemoinformatics is an ideal supplementary text for advanced undergraduate and graduate courses in chemoinformatics, bioinformatics, computational chemistry, computational biology, medicinal chemistry and biochemistry. It is also a valuable working resource for medicinal chemists, academic researchers and industrial chemists looking to enhance their chemoinformatics skills.
The Practice of Medicinal Chemistry, Fourth Edition provides a practical and comprehensive overview of the daily issues facing pharmaceutical researchers and chemists. In addition to its thorough treatment of basic medicinal chemistry principles, this updated edition has been revised to provide new and expanded coverage of the latest technologies and approaches in drug discovery. With topics like high content screening, scoring, docking, binding free energy calculations, polypharmacology, QSAR, chemical collections and databases, and much more, this book is the go-to reference for all academic and pharmaceutical researchers who need a complete understanding of medicinal chemistry and its application to drug discovery and development. Includes updated and expanded material on systems biology, chemogenomics, computer-aided drug design, and other important recent advances in the field Incorporates extensive color figures, case studies, and practical examples to help users gain a further understanding of key concepts Provides high-quality content in a comprehensive manner, including contributions from international chapter authors to illustrate the global nature of medicinal chemistry and drug development research An image bank is available for instructors at www.textbooks.elsevier.com
Modelling Methodology for Physiology and Medicine, Second Edition, offers a unique approach and an unprecedented range of coverage of the state-of-the-art, advanced modeling methodology that is widely applicable to physiology and medicine. The second edition, which is completely updated and expanded, opens with a clear and integrated treatment of advanced methodology for developing mathematical models of physiology and medical systems. Readers are then shown how to apply this methodology beneficially to real-world problems in physiology and medicine, such as circulation and respiration. The focus of Modelling Methodology for Physiology and Medicine, Second Edition, is the methodology that underpins good modeling practice. It builds upon the idea of an integrated methodology for the development and testing of mathematical models. It covers many specific areas of methodology in which important advances have taken place over recent years and illustrates the application of good methodological practice in key areas of physiology and medicine. It builds on work that the editors have carried out over the past 30 years, working in cooperation with leading practitioners in the field. Builds upon and enhances the reader's existing knowledge of modeling methodology and practice Editors are internationally renowned leaders in their respective fields Provides an understanding of modeling methodologies that can address real problems in physiology and medicine and achieve results that are beneficial either in advancing research or in providing solutions to clinical problems
Chemoinformatics strategies to improve drug discoveryresults With contributions from leading researchers in academia and thepharmaceutical industry as well as experts from the softwareindustry, this book explains how chemoinformatics enhances drugdiscovery and pharmaceutical research efforts, describing whatworks and what doesn't. Strong emphasis is put on tested and provenpractical applications, with plenty of case studies detailing thedevelopment and implementation of chemoinformatics methods tosupport successful drug discovery efforts. Many of these casestudies depict groundbreaking collaborations between academia andthe pharmaceutical industry. Chemoinformatics for Drug Discovery is logicallyorganized, offering readers a solid base in methods and models andadvancing to drug discovery applications and the design ofchemoinformatics infrastructures. The book features 15 chapters,including: What are our models really telling us? A practical tutorial onavoiding common mistakes when building predictive models Exploration of structure-activity relationships and transfer ofkey elements in lead optimization Collaborations between academia and pharma Applications of chemoinformatics in pharmaceuticalresearch—experiences at large international pharmaceuticalcompanies Lessons learned from 30 years of developing successfulintegrated chemoinformatic systems Throughout the book, the authors present chemoinformaticsstrategies and methods that have been proven to work inpharmaceutical research, offering insights culled from their owninvestigations. Each chapter is extensively referenced withcitations to original research reports and reviews. Integrating chemistry, computer science, and drug discovery,Chemoinformatics for Drug Discovery encapsulates the fieldas it stands today and opens the door to further advances.
Pharmacology in Drug Discovery and Development: Understanding Drug Response, Second Edition, is an introductory resource illustrating how pharmacology can be used to furnish the tools necessary to analyze different drug behavior and trace this behavior to its root cause or molecular mechanism of action. The concepts discussed in this book allow for the application of more predictive pharmacological procedures aimed at increasing therapeutic efficacy that will lead to more successful drug development. Chapters logically build upon one another to show how to characterize the pharmacology of any given molecule and allow for more informed predictions of drug effects in all biological systems. New chapters are dedicated to the interdisciplinary drug discovery environment in both industry and academia, and special techniques involved in new drug screening and lead optimization. This edition has been fully revised to address the latest advances and research related to real time kinetic assays, pluridimensional efficacy, signaling bias, irreversible and chemical antagonism, allosterically-induced bias, pharmacokinetics and safety, target and pathway validation, and much more. With numerous valuable chapter summaries, detailed references, practical examples and case studies throughout, Dr. Kenakin successfully navigates a highly complex subject, making it accessible for students, professors, and new researchers working in pharmacology and drug discovery. Includes example-based cases that illustrate how the pharmacological concepts discussed in this book lead to practical outcomes for further research Provides vignettes on those researchers and scientists who have contributed significantly to the fields of pharmacology and drug discovery throughout history Offers sample questions throughout the book and an appendix containing answers for self-testing and retention