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The approaches in drug design are mainly comprised of these three multidisciplinary sciences. First, Bioinformatics has successfully gather biological data in form of biomolecular sequences, in order to construct knowledge on drug and vaccine design. It is of considerable importance for drug designers to comprehend the utilization of bioinformatics tools for resolving their research questions. Second, Nanotechnology has made possible the design and delivery of the nano-based drug. Third, Pharmaceutical Chemistry made it possible to investigate the adsorption, distribution, metabolism, and toxicology of the drug candidates in a fine-grained resolution.
The molecular modeling perspective in drug design. (N. Calude Cohen). Molecular graphics and modeling: tools of the trade. (Roderick E. Hubbard). Molecular modeling of small molecules. (Tamara Gund). Computer assisted new lead design. (Akiko Itai, Miho Yamada Mizutani, Yoshihiko Nishibata, and Nubuo Tomioka). Experimental techniques and data banks. (John P. Priestle and C. Gregory Paris). Computer-assisted drug discovery. (Peter Gund, Gerald Maggiora, and James P. Snyder). Modeling drug-receptor interactions. (Konrad F. Koehler, Shashidhar N. Rao, and James P. Snyder). Glossary of terminology. (J. P. Tollenaere).
Improving and Accelerating Therapeutic Development for Nervous System Disorders is the summary of a workshop convened by the IOM Forum on Neuroscience and Nervous System Disorders to examine opportunities to accelerate early phases of drug development for nervous system drug discovery. Workshop participants discussed challenges in neuroscience research for enabling faster entry of potential treatments into first-in-human trials, explored how new and emerging tools and technologies may improve the efficiency of research, and considered mechanisms to facilitate a more effective and efficient development pipeline. There are several challenges to the current drug development pipeline for nervous system disorders. The fundamental etiology and pathophysiology of many nervous system disorders are unknown and the brain is inaccessible to study, making it difficult to develop accurate models. Patient heterogeneity is high, disease pathology can occur years to decades before becoming clinically apparent, and diagnostic and treatment biomarkers are lacking. In addition, the lack of validated targets, limitations related to the predictive validity of animal models - the extent to which the model predicts clinical efficacy - and regulatory barriers can also impede translation and drug development for nervous system disorders. Improving and Accelerating Therapeutic Development for Nervous System Disorders identifies avenues for moving directly from cellular models to human trials, minimizing the need for animal models to test efficacy, and discusses the potential benefits and risks of such an approach. This report is a timely discussion of opportunities to improve early drug development with a focus toward preclinical trials.
Basic Principles of Drug Discovery and Development presents the multifaceted process of identifying a new drug in the modern era, which requires a multidisciplinary team approach with input from medicinal chemists, biologists, pharmacologists, drug metabolism experts, toxicologists, clinicians, and a host of experts from numerous additional fields. Enabling technologies such as high throughput screening, structure-based drug design, molecular modeling, pharmaceutical profiling, and translational medicine are critical to the successful development of marketable therapeutics. Given the wide range of disciplines and techniques that are required for cutting edge drug discovery and development, a scientist must master their own fields as well as have a fundamental understanding of their collaborator's fields. This book bridges the knowledge gaps that invariably lead to communication issues in a new scientist's early career, providing a fundamental understanding of the various techniques and disciplines required for the multifaceted endeavor of drug research and development. It provides students, new industrial scientists, and academics with a basic understanding of the drug discovery and development process. The fully updated text provides an excellent overview of the process and includes chapters on important drug targets by class, in vitro screening methods, medicinal chemistry strategies in drug design, principles of in vivo pharmacokinetics and pharmacodynamics, animal models of disease states, clinical trial basics, and selected business aspects of the drug discovery process. - Provides a clear explanation of how the pharmaceutical industry works, as well as the complete drug discovery and development process, from obtaining a lead, to testing the bioactivity, to producing the drug, and protecting the intellectual property - Includes a new chapter on the discovery and development of biologics (antibodies proteins, antibody/receptor complexes, antibody drug conjugates), a growing and important area of the pharmaceutical industry landscape - Features a new section on formulations, including a discussion of IV formulations suitable for human clinical trials, as well as the application of nanotechnology and the use of transdermal patch technology for drug delivery - Updated chapter with new case studies includes additional modern examples of drug discovery through high through-put screening, fragment-based drug design, and computational chemistry
Right before the COVID-19 pandemic declared by the World Health Organization (WHO), life sciences have incited novel areas of studies that revolutionize the health sector. They are the studies of structural bioinformatics, pharmacogenomics, and metabolomics. The structural bioinformatics field is the very foundation of drug design research, as it provides insight into the molecular simulations and interactions between the biomolecules and the drug candidates. Secondly, pharmacogenomics is the starting point of any efforts in developing personalized medicine. Lastly, metabolomics provides instrumentation to elicit biomarkers for various diseases and health conditions. These studies have enabled current accelerated effort in COVID-19 research, as well as other communicable and non-communicable diseases.
Design of Hybrid Molecules for Drug Development reviews the principles, advantages, and limitations involved with designing these groundbreaking compounds. Beginning with an introduction to hybrid molecule design and background as to their need, the book goes on to explore a range of important hybrids, with hybrids containing natural products, molecules containing NO- and H2S-donors, dual-acting compounds acting as receptor ligands and enzyme inhibitors, and the design of photoresponsive drugs all discussed. Drawing on practical case studies, the hybridization of molecules for development as treatments for a number of key diseases is then outlined, including the design of hybrids for Alzheimer's, cancer, and malaria. With its cutting-edge reviews of breaking developments in this exciting field, the book offers a novel approach for all those working in the design, development, and administration of drugs for a range of debilitating disorders. - Highlights an approach unimpaired by the limitations of the classical search for lead structures - one of the core problems in modern drug development processes, making the content of high relevance for both academic and non-academic drug development processes - Pulls together research and design techniques in a novel way to give researchers the best possible platform from which to review the approaches and techniques applied - Compares the advantages and disadvantages of these compounds - Includes the very latest developments, such as photoactivatable and photo-responsive drugs
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.
Building on the success of the previous editions, Textbook of Drug Design and Discovery has been thoroughly revised and updated to provide a complete source of information on all facets of drug design and discovery for students of chemistry, pharmacy, pharmacology, biochemistry, and medicine. The book follows drug design from the initial lead identification through optimization and structure-activity relationship with reference to the final processes of clinical evaluation and registration. Chapters investigate the design of enzyme inhibitors and drugs for particular cellular targets such as ion channels and receptors, and also explore specific classes of drug such as peptidomimetics, antivirals and anticancer agents. The use of gene technology in pharmaceutical research, computer modeling techniques, and combinatorial approaches are also included.
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
Natural Products have been important sources of useful drugs from prehistoric times to the present. This book gives an overview about this field and provides important recent contributions to the discovery of new drugs generated by research on natural products. Total synthesis of natural products with interesting biological activities is paving the way for the preparation of new and improved analogs. The methods of combinatorial chemistry permit the selection of the best drug from a large number of candidates. Beyond synthesis and evaluation of organic molecules a number of new bioorganic methods are coming to the fore and will be discucced in this isue of the ERnst schering Research Foundation workshop proceedings.