Structural Bioinformatics Applications In Preclinical Drug Discovery Process

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.

Structural Bioinformatics was the first major effort to show the application of the principles and basic knowledge of the larger field of bioinformatics to questions focusing on macromolecular structure, such as the prediction of protein structure and how proteins carry out cellular functions, and how the application of bioinformatics to these life science issues can improve healthcare by accelerating drug discovery and development. Designed primarily as a reference, the first edition nevertheless saw widespread use as a textbook in graduate and undergraduate university courses dealing with the theories and associated algorithms, resources, and tools used in the analysis, prediction, and theoretical underpinnings of DNA, RNA, and proteins. This new edition contains not only thorough updates of the advances in structural bioinformatics since publication of the first edition, but also features eleven new chapters dealing with frontier areas of high scientific impact, including: sampling and search techniques; use of mass spectrometry; genome functional annotation; and much more. Offering detailed coverage for practitioners while remaining accessible to the novice, Structural Bioinformatics, Second Edition is a valuable resource and an excellent textbook for a range of readers in the bioinformatics and advanced biology fields. Praise for the previous edition: "This book is a gold mine of fundamental and practical information in an area not previously well represented in book form." —Biochemistry and Molecular Education "... destined to become a classic reference work for workers at all levels in structural bioinformatics...recommended with great enthusiasm for educators, researchers, and graduate students." —BAMBED "...a useful and timely summary of a rapidly expanding field." —Nature Structural Biology "...a terrific job in this timely creation of a compilation of articles that appropriately addresses this issue." —Briefings in Bioinformatics

This work covers the impact of computational structural biology on protein structure prediction methods, macromolecular function and protein design, and key methods in drug discovery. It also addresses the computational challenges of experimental approaches in structural biology.

We are extremely happy to introduce our new book, Recent Advances in Computer Aided Drug Designing. While interacting with many researchers in the field of biotechnology and allied sciences, we felt that there was need for a book that could easily bridge the gap between in silico methods applied in structural bioinformatics for drug designing and wet lab workers. Today, when computational skills in biology and biomedical research are in high demand, this book presents updated content for methods and tools applicable in modern computer-aided drug designing. Researchers are pouring knowledge into databases that are publicly available and laboratories across the globe are accessing this information for analysis and further investigation. There is a battery of data scientists involved in development and maintenance of online databases. Alongside them, there is another class of programmers and scientists involved in development of software tools for analysis of this data. Modern tools based on machine learning are available to provide accuracy and efficiency with speedy analysis of biological and biomedical data. In many cases, analysis of readily available biological data helps to decide future directions for laboratory work. Indications obtained from such analytics save time and resources which could be very crucial in general. Publicly available protein three-dimensional structure and drug databank libraries have facilitated the drug discovery process. Millions of drugs can be screened in a few hours by using virtual screening tools. Molecular viewing tools can be used to visualize macromolecules and their interactions with drugs. Findings from such studies are being used to validate results directly in laboratories.Efforts have been made to cover all areas relevant for computer-aided drug designing to allow this book to serve as a standard reference book and meet the requirements of graduate students and researchers working in drug design and structural bioinformatics. Some chapters are dedicated to basic concepts in computer-aided drug discovery while other chapters present applications of the available tools in the field. Contents from exemplary method-based chapters are easy to follow and will help new researchers in applying contemporary tools for their studies. The book will also stimulate programmers and data scientists interested in developing tools for structural bioinformatics applications to develop new and improved versions of software. Chapters presenting the basic concepts of methods involved in drug design will help new learners in the field to meet the challenges of designing novel therapeutics by using computational tools. Cross-disciplinary research is in trend nowadays and such investigations involving experts of their respective fields are highly promising and fruitful. Drug discovery requires experts from health sciences and medical sciences, molecular biologists, bioinformaticians, biotechnologists, biochemists, statisticians, biophysicists and clinicians. For a complete piece of translated product such as a drug, inputs from specialist researchers are needed. Modern rational drug discovery approaches are truly inter-disciplinary fields which require a systems biology approach for successful ventures. This book covers all steps of drug design, from drug target identification to intermediate steps to successful clinical trials, making it truly essential for modern researchers in the drug discovery and structural bioinformatics fields.

This book describes the processes that are involved in the development of new drugs. The authors discuss the history, role of natural products and concept of receptor interactions with regard to the initial stages of drug discovery. In a single, highly readable volume, it outlines the basics of pharmacological screening, drug target identification, and genetics involved in early drug discovery. The final chapters introduce readers to stem therapeutics, pharmacokinetics, pharmacovigilance, and toxicological testing. Given its scope, the book will enable research scholars, professionals and young scientists to understand the key fundamentals of drug discovery, including stereochemistry, pharmacokinetics, clinical trials, statistics and toxicology.

Designing and developing new drugs is an expensive and time-consuming process, and there is a need to discover new tools or approaches that can optimize this process. Applied Computer-Aided Drug Design: Models and Methods compiles information about the main advances in computational tools for discovering new drugs in a simple and accessible language for academic students to early career researchers. The book aims to help readers understand how to discover molecules with therapeutic potential by bringing essential information about the subject into one volume. Key Features · Presents the concepts and evolution of classical techniques, up to the use of modern methods based on computational chemistry in accessible format. · Gives a primer on structure- and ligand-based drug design and their predictive capacity to discover new drugs. · Explains theoretical fundamentals and applications of computer-aided drug design. · Focuses on a range of applications of the computations tools, such as molecular docking; molecular dynamics simulations; homology modeling, pharmacophore modeling, quantitative structure-activity relationships (QSAR), density functional theory (DFT), fragment-based drug design (FBDD), and free energy perturbation (FEP). · Includes scientific reference for advanced readers Readership Students, teachers and early career researchers.

BIOINFORMATICS TOOLS FOR Pharmaceutical DRUG PRODUCT DLEVELOPMENT A timely book that details bioinformatics tools, artificial intelligence, machine learning, computational methods, protein interactions, peptide-based drug design, and omics technologies, for drug development in the pharmaceutical and medical sciences industries. The book contains 17 chapters categorized into 3 sections. The first section presents the latest information on bioinformatics tools, artificial intelligence, machine learning, computational methods, protein interactions, peptide-based drug design, and omics technologies. The following 2 sections include bioinformatics tools for the pharmaceutical sector and the healthcare sector. Bioinformatics brings a new era in research to accelerate drug target and vaccine design development, improving validation approaches as well as facilitating and identifying side effects and predicting drug resistance. As such, this will aid in more successful drug candidates from discovery to clinical trials to the market, and most importantly make it a more cost-effective process overall. Readers will find in this book: Applications of bioinformatics tools for pharmaceutical drug product development like process development, pre-clinical development, clinical development, commercialization of the product, etc.; The ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach; The broad and deep background, as well as updates, on recent advances in both medicine and AI/ML that enable the application of these cutting-edge bioinformatics tools. Audience The book will be used by researchers and scientists in academia and industry including drug developers, computational biochemists, bioinformaticians, immunologists, pharmaceutical and medical sciences, as well as those in artificial intelligence and machine learning.

The process of drug discovery and development is a complex multistage logistics project spanned over 10-15 years with an average budget exceeding 1 billion USD. Starting with target identification and synthesizing anywhere between 10k to 15k synthetic compounds to potentially obtain the final drug that reaches the market involves a complicated maze with multiple inter- and intra-operative fields. Topics described in this book emphasize the progresses in computational applications, pharmacokinetics advances, and molecular modeling developments. In addition the book also contains special topics describing target deorphaning in Mycobacterium tuberculosis, therapy treatment of some rare diseases, and developments in the pediatric drug discovery process.