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This practice-oriented handbook surveys current knowledge on the prediction and prevention of adverse drug reactions related to off-target activity of small molecule drugs. It is unique in collating the current approaches into a single source, and includes several highly instructive case studies that may be used as guidelines on how to improve drug development projects. With its large section on ADME-related effects, this is key knowledge for every drug developer.
With its focus on emerging concerns of kinase and GPCR-mediated antitarget effects, this vital reference for drug developers addresses one of the hot topics in drug safety now and in future. Divided into three major parts, the first section deals with novel technologies and includes the utility of adverse event reports to drug discovery, the translational aspects of preclinical safety findings, broader computational prediction of drug side-effects, and a description of the serotonergic system. The main part of the book looks at some of the most common antitarget-mediated side effects, focusing on hepatotoxicity in drug safety, cardiovascular toxicity and signaling effects via kinase and GPCR anti-targets. In the final section, several case studies of recently developed drugs illustrate how to prevent anti-target effects and how big pharma deals with them if they occur. The more recent field of systems pharmacology has gained prominence and this is reflected in chapters dedicated to the utility in deciphering and modeling anti-targets. The final chapter is concerned with those compounds that inadvertently elicit CNS mediated adverse events, including a pragmatic description of ways to mitigate these types of safety risks. Written as a companion to the successful book on antitargets by Vaz and Klabunde, this new volume focuses on recent progress and new classes, methods and case studies that were not previously covered.
The proposed volume provides both fundamental and detailed information about the computational and computational-experimental studies which improve our knowledge of how leaving matter functions, the different properties of drugs (including the calculation and the design of new ones), and the creation of completely new ways of treating numerical diseases. Whenever it is possible, the interplay between theory and experiment is provided. The book features computational techniques such as quantum-chemical and molecular dynamic approaches and quantitative structure–activity relationships. The initial chapters describe the state-of-the art research on the computational investigations in molecular biology, molecular pharmacy, and molecular medicine performed with the use of pure quantum-chemical techniques. The central part of the book illustrates the status of computational techniques that utilize hybrid, so called QM/MM approximations as well as the results of the QSAR studies which now are the most popular in predicting drugs’ efficiency. The last chapters describe combined computational and experimental investigations.
Discussing recent advances in the field of matrix metalloproteinase (MMP) research from a multidisciplinary perspective, Matrix Metalloproteinase Biologyis a collection of chapters written by leaders in the field of MMPs. The book focuses on the challenges of understanding the mechanisms substrate degradation by MMPs, as well as how these enzymes are able to degrade large, highly ordered substrates such as collagen. All topics addressed are considered in relation to disease progression including roles in cancer metastasis, rheumatoid arthritis and other inflammatory diseases. The text first provides an overview of MMPs, focusing on the history, the development and failures of small molecule inhibitors in clinical trials, and work with TIMPS, the endogenous inhibitors of MMPs. These introductory chapters establish the foundation for later discussion of the recent progress on the design of different types of inhibitors, including novel antibody based therapeutics. The following section emphasizes research using novel methods to further the study of the MMPs. The third and final section focuses on in vivo research, particularly with respect to cancer models, degradation of the extracellular matrix, and MMP involvement in other disease states. Written and edited by leaders in the field, Matrix Metalloproteinase Biology addresses the rapidly growth in MMP research, and will be an invaluable resource to advanced students and researchers studying cell and molecular biology.
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.
The inhibition of angiogenesis is an effective mechanism of slowing down tumor growth and malignancies. The process of induction or pro-angiogenesis is highly desirable for the treatment of cardiovascular diseases, wound healing disorders, and more. Efforts to understand the molecular basis, both for inhibition and induction, have yielded fascinating results. Originally published by Bentham and now distributed by Elsevier, Anti-Angiogenesis Drug Discovery and Development, Volume 2 is an compilation of well-written reviews on various aspects of the anti-angiogenesis process. These reviews have been contributed by leading practitioners in drug discovery science and highlight the major developments in this exciting field in the last two decades. These reader-friendly chapters cover topics of great scientific importance, many of which are considered significant medical breakthroughs, making this book excellent reading both for the novice as well as for expert medicinal chemists and clinicians. - Edited and written by leading experts in angiogenesis drug development - Reviews recent advances in the field, such as coverage of anti-angiogenetic drugs in ovarian cancer - Reports current strategies and future outlook for anti-angiogenic therapy and cardiovascular diseases
Chemoinformatics strategies to improve drug discovery results With contributions from leading researchers in academia and the pharmaceutical industry as well as experts from the software industry, this book explains how chemoinformatics enhances drug discovery and pharmaceutical research efforts, describing what works and what doesn't. Strong emphasis is put on tested and proven practical applications, with plenty of case studies detailing the development and implementation of chemoinformatics methods to support successful drug discovery efforts. Many of these case studies depict groundbreaking collaborations between academia and the pharmaceutical industry. Chemoinformatics for Drug Discovery is logically organized, offering readers a solid base in methods and models and advancing to drug discovery applications and the design of chemoinformatics infrastructures. The book features 15 chapters, including: What are our models really telling us? A practical tutorial on avoiding common mistakes when building predictive models Exploration of structure-activity relationships and transfer of key elements in lead optimization Collaborations between academia and pharma Applications of chemoinformatics in pharmaceutical research experiences at large international pharmaceutical companies Lessons learned from 30 years of developing successful integrated chemoinformatic systems Throughout the book, the authors present chemoinformatics strategies and methods that have been proven to work in pharmaceutical research, offering insights culled from their own investigations. Each chapter is extensively referenced with citations to original research reports and reviews. Integrating chemistry, computer science, and drug discovery, Chemoinformatics for Drug Discovery encapsulates the field as it stands today and opens the door to further advances.
With its focus on emerging concerns of kinase and GPCR-mediated antitarget effects, this vital reference for drug developers addresses one of the hot topics in drug safety now and in future. Divided into three major parts, the first section deals with novel technologies and includes the utility of adverse event reports to drug discovery, the translational aspects of preclinical safety findings, broader computational prediction of drug side-effects, and a description of the serotonergic system. The main part of the book looks at some of the most common antitarget-mediated side effects, focusing on hepatotoxicity in drug safety, cardiovascular toxicity and signaling effects via kinase and GPCR anti-targets. In the final section, several case studies of recently developed drugs illustrate how to prevent anti-target effects and how big pharma deals with them if they occur. The more recent field of systems pharmacology has gained prominence and this is reflected in chapters dedicated to the utility in deciphering and modeling anti-targets. The final chapter is concerned with those compounds that inadvertently elicit CNS mediated adverse events, including a pragmatic description of ways to mitigate these types of safety risks. Written as a companion to the successful book on antitargets by Vaz and Klabunde, this new volume focuses on recent progress and new classes, methods and case studies that were not previously covered.
With over 105,000 medical terms and over one million words, this is the most extensive dictionary of its kind available.