Molecular Evolutionary Models in Drug Discovery explores the application of evolutionary molecular models in drug discovery in which secondary metabolites play a fundamental role. Secondary metabolites are not produced in isolation, they are the result of the interaction of genes, metabolism and the environment. The book examines the role of secondary metabolites as leads in drug discovery and on the development of a rational bioprospecting model for new medicines based on the evolution of secondary metabolism. These evolutionary models are part of biological systems and are the most reliable expression of the functioning of living beings. - Examines the integration and application of evolutionary models in the pharmaceutical industry to create new drug development platforms - Investigates the biotechnological prospecting of secondary metabolites and their potential use in the discovery of new drugs - Evaluates the ecosystem of living beings and how its molecular adaptation might improve the success of therapies

Systematically examining current methods and strategies, this ready reference covers a wide range of molecular structures, from organic-chemical drugs to peptides, Proteins and nucleic acids, in line with emerging new drug classes derived from biomacromolecules. A leader in the field and one of the pioneers of this young discipline has assembled here the most prominent experts from across the world to provide first-hand knowledge. While most of their methods and examples come from the area of pharmaceutical discovery and development, the approaches are equally applicable for chemical probes and diagnostics, pesticides, and any other molecule designed to interact with a biological system. Numerous images and screenshots illustrate the many examples and method descriptions. With its broad and balanced coverage, this will be the firststop resource not only for medicinal chemists, biochemists and biotechnologists, but equally for bioinformaticians and molecular designers for many years to come. From the content: * Reaction-driven de novo design * Adaptive methods in molecular design * Design of ligands against multitarget profiles * Free energy methods in ligand design * Fragment-based de novo design * Automated design of focused and target family-oriented compound libraries * Molecular de novo design by nature-inspired computing * 3D QSAR approaches to de novo drug design * Bioisosteres in de novo design * De novo design of peptides, proteins and nucleic acid structures, including RNA aptamers and many more.

Evolutionary Diversity as a Source for Anticancer Molecules discusses evolutionary diversity as source for anticancer agents derived from bacteria, algae, bryophytes, pteridophytes, and gymnosperms. The book goes over the isolation of anticancer agents and the technologyenabled screening process used to develop anticancer drugs. The book also includes discussion of the nutraceuticals and natural productsderived from invertebrates that can be used as part of cancer treatment. Evolutionary Diversity as a Source for Anticancer Molecules also deals with some of the current challenges in the prevention of cancer as well as the side effects of conventional drugs used for cancer patients.This book is a valuable resource for cancer researchers, oncologists, biotechnologists, pharmacologists, and any member of the biomedicalfield interested in understanding more about natural products with anticancer potential. - Discusses the application of natural products in place of conventional drugs to minimize the side effects in cancer treatment - Explains the relation between evolutionary mechanisms and climate change for production of secondary metabolites

Written by one of the top most statisticians with experience in diverse fields of applications of statistics, the book deals with the philosophical and methodological aspects of information technology, collection and analysis of data to provide insight into a problem, whether it is scientific research, policy making by government or decision making in our daily lives.The author dispels the doubts that chance is an expression of our ignorance which makes accurate prediction impossible and illustrates how our thinking has changed with quantification of uncertainty by showing that chance is no longer the obstructor but a way of expressing our knowledge. Indeed, chance can create and help in the investigation of truth. It is eloquently demonstrated with numerous examples of applications that statistics is the science, technology and art of extracting information from data and is based on a study of the laws of chance. It is highlighted how statistical ideas played a vital role in scientific and other investigations even before statistics was recognized as a separate discipline and how statistics is now evolving as a versatile, powerful and inevitable tool in diverse fields of human endeavor such as literature, legal matters, industry, archaeology and medicine.Use of statistics to the layman in improving the quality of life through wise decision making is emphasized.

Following significant advances in deep learning and related areas interest in artificial intelligence (AI) has rapidly grown. In particular, the application of AI in drug discovery provides an opportunity to tackle challenges that previously have been difficult to solve, such as predicting properties, designing molecules and optimising synthetic routes. Artificial Intelligence in Drug Discovery aims to introduce the reader to AI and machine learning tools and techniques, and to outline specific challenges including designing new molecular structures, synthesis planning and simulation. Providing a wealth of information from leading experts in the field this book is ideal for students, postgraduates and established researchers in both industry and academia.

With the most comprehensive and up-to-date overview of structure-based drug discovery covering both experimental and computational approaches, Structural Biology in Drug Discovery: Methods, Techniques, and Practices describes principles, methods, applications, and emerging paradigms of structural biology as a tool for more efficient drug development. Coverage includes successful examples, academic and industry insights, novel concepts, and advances in a rapidly evolving field. The combined chapters, by authors writing from the frontlines of structural biology and drug discovery, give readers a valuable reference and resource that: Presents the benefits, limitations, and potentiality of major techniques in the field such as X-ray crystallography, NMR, neutron crystallography, cryo-EM, mass spectrometry and other biophysical techniques, and computational structural biology Includes detailed chapters on druggability, allostery, complementary use of thermodynamic and kinetic information, and powerful approaches such as structural chemogenomics and fragment-based drug design Emphasizes the need for the in-depth biophysical characterization of protein targets as well as of therapeutic proteins, and for a thorough quality assessment of experimental structures Illustrates advances in the field of established therapeutic targets like kinases, serine proteinases, GPCRs, and epigenetic proteins, and of more challenging ones like protein-protein interactions and intrinsically disordered proteins

Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.

The study of evolution at the molecular level has given the subject of evolutionary biology a new significance. Phylogenetic 'trees' of gene sequences are a powerful tool for recovering evolutionary relationships among species, and can be used to answer a broad range of evolutionary and ecological questions. They are also beginning to permeate the medical sciences. In this book, the authors approach the study of molecular evolution with the phylogenetic tree as a central metaphor. This will equip students and professionals with the ability to see both the evolutionary relevance of molecular data, and the significance evolutionary theory has for molecular studies. The book is accessible yet sufficiently detailed and explicit so that the student can learn the mechanics of the procedures discussed. The book is intended for senior undergraduate and graduate students taking courses in molecular evolution/phylogenetic reconstruction. It will also be a useful supplement for students taking wider courses in evolution, as well as a valuable resource for professionals. First student textbook of phylogenetic reconstruction which uses the tree as a central metaphor of evolution. Chapter summaries and annotated suggestions for further reading. Worked examples facilitate understanding of some of the more complex issues. Emphasis on clarity and accessibility.

The newer research areas in pharmaceutical sciences, particularly molecular modeling and simulations, prompted a more efficient drug discovery process. Informatics integrated with pharmaceutical sciences (cheminformatics and bioinformatics) became an essential component of drug research. Drug informatics such as genomics and proteomics assists in the Rational Drug Design (RDD). This emerging discipline is known as “Computer-Aided Drug Design (CADD)”, which has profound application in rational drug design (RDD). The advanced and adequate practice in drug design informatics is essential for pharmacy graduates. Hence, a companion for acquiring knowledge on these concepts is vital. The students of B. Pharmacy, M. Pharmacy (Pharmaceutical Chemistry, Pharmacology, and Pharmaceutics), biotechnology, biomedical engineering and other interdisciplinary fields may find this book as a reference guide. The salient features of this book are: • Systematic and simple approach • Emphasis on traditional and modern drug design strategies • Comprehensive coverage for the current advances in the drug design • Experimental section to ensure hands-on-experience Note: T& F does not sell or distribute the Hardback in India, Pakistan, Nepal, Bhutan, Bangladesh and Sri Lanka.

Nervous system diseases and disorders are highly prevalent and substantially contribute to the overall disease burden. Despite significant information provided by the use of animal models in the understanding of the biology of nervous system disorders and the development of therapeutics; limitations have also been identified. Treatment options that are high in efficacy and low in side effects are still lacking for many diseases and, in some cases are nonexistent. A particular problem in drug development is the high rate of attrition in Phase II and III clinical trials. Why do many therapeutics show promise in preclinical animal models but then fail to elicit predicted effects when tested in humans? On March 28 and 29, 2012, the Institute of Medicine Forum on Neuroscience and Nervous System Disorders convened the workshop "Improving Translation of Animal Models for Nervous System Disorders" to discuss potential opportunities for maximizing the translation of new therapies from animal models to clinical practice. The primary focus of the workshop was to examine mechanisms for increasing the efficiency of translational neuroscience research through discussions about how and when to use animal models most effectively and then best approaches for the interpretation of the data collected. Specifically, the workshop objectives were to: discuss key issues that contribute to poor translation of animal models in nervous system disorders, examine case studies that highlight successes and failures in the development and application of animal models, consider strategies to increase the scientific rigor of preclinical efficacy testing, explore the benefits and challenges to developing standardized animal and behavioral models. Improving the Utility and Translation of Animal Models for Nervous System Disorders: Workshop Summary also identifies methods to facilitate development of corresponding animal and clinical endpoints, indentifies methods that would maximize bidirectional translation between basic and clinical research and determines the next steps that will be critical for improvement of the development and testing of animal models of disorders of the nervous system.