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Drug Repurposing in Cancer Therapy: Approaches and Applications provides comprehensive and updated information from experts in basic science research and clinical practice on how existing drugs can be repurposed for cancer treatment. The book summarizes successful stories that may assist researchers in the field to better design their studies for new repurposing projects. Sections discuss specific topics such as in silico prediction and high throughput screening of repurposed drugs, drug repurposing for overcoming chemoresistance and eradicating cancer stem cells, and clinical investigation on combination of repurposed drug and anticancer therapy. Cancer researchers, oncologists, pharmacologists and several members of biomedical field who are interested in learning more about the use of existing drugs for different purposes in cancer therapy will find this to be a valuable resource. - Presents a systematic and up-to-date collection of the research underpinning the various drug repurposing approaches for a quick, but in-depth understanding on current trends in drug repurposing research - Brings better understanding of the drug repurposing process in a holistic way, combining both basic and clinical sciences - Encompasses a collection of successful stories of drug repurposing for cancer therapy in different cancer types
Drug repurposing or drug repositioning is a new approach to presenting new indications for common commercial and clinically approved existing drugs. For example, chloroquine, an old antimalarial drug, showed promising results for treating COVID-19, interfering with MDR in several types of cancer, and chemosensitizing human leukemic cells.This book focuses on the hypothesis, risk/benefits, and economic impacts of drug repurposing on drug discovery in dermatology, infectious diseases, neurological disorders, cancer, and orphan diseases. It brings together up-to-date research to provide readers with an informative, illustrative, and easy-to-read book useful for students, clinicians, and the pharmaceutical industry.
Computational Methods in Drug Discovery and Repurposing for Cancer Therapy provides knowledge about ongoing research as well as computational approaches for drug discovery and repurposing for cancer therapy. The book also provides detailed descriptions about target molecules, pathways, and their inhibitors for easy understanding and applicability. The book discusses tools and techniques such as integrated bioinformatics approaches, systems biology tools, molecular docking, computational chemistry, artificial intelligence, machine learning, structure-based virtual screening, biomarkers, and transcriptome; those are discussed in the context of different cancer types, such as colon, pancreatic, glioblastoma, endometrial, and retinoblastoma, among others. This book is a valuable resource for researchers, students, and members of the biomedical and medical fields who want to learn more about the use of computational modeling to better tailor the treatment for cancer patients. - Discusses in silico remodeling of effective phytochemical compounds for discovering improved anticancer agents for substantial/significant cancer therapy - Covers potential tools of bioinformatics that are applied toward discovering new targets by drug repurposing and strategies to cure different types of cancers - Demonstrates the significance of computational and artificial intelligence approaches in anticancer drug discovery - Explores how these various advances can be integrated into a precision and personalized medicine approach that can eventually enhance patient care
This volume constitutes the proceedings of the 8th International Work-Conference on IWBBIO 2020, held in Granada, Spain, in May 2020. The total of 73papers presented in the proceedings, was carefully reviewed and selected from 241 submissions. The papers are organized in topical sections as follows: Biomarker Identification; Biomedical Engineering; Biomedical Signal Analysis; Bio-Nanotechnology; Computational Approaches for Drug Design and Personalized Medicine; Computational Proteomics and Protein-Protein Interactions; Data Mining from UV/VIS/NIR Imaging and Spectrophotometry; E-Health Technology, Services and Applications; Evolving Towards Digital Twins in Healthcare (EDITH); High Performance in Bioinformatics; High-Throughput Genomics: Bioinformatic Tools and Medical Applications; Machine Learning in Bioinformatics; Medical Image Processing; Simulation and Visualization of Biological Systems.
This detailed book explores techniques commonly used for research into drug repurposing, a well-known strategy to find alternative indications for drugs which have already undergone toxicology and pharma-kinetic studies but have failed later stages during the development, via computational methods. Thereby, it addresses the intense challenges of identifying the appropriate type of algorithm and relevant technical information for computational repurposing. Written for the highly successful Methods in Molecular Biology series, the authors of each chapter use their experience in the field to describe the implementation and successful use of a specific repurposing method thus providing lab-ready instruction. Authoritative and practical, Computational Methods for Drug Repurposing serves as an ideal guide to researchers interested in this vital area of drug development.
This book provides up-to-date information on bioinformatics tools for the discovery and development of new drug molecules. It discusses a range of computational applications, including three-dimensional modeling of protein structures, protein-ligand docking, and molecular dynamics simulation of protein-ligand complexes for identifying desirable drug candidates. It also explores computational approaches for identifying potential drug targets and for pharmacophore modeling. Moreover, it presents structure- and ligand-based drug design tools to optimize known drugs and guide the design of new molecules. The book also describes methods for identifying small-molecule binding pockets in proteins, and summarizes the databases used to explore the essential properties of drugs, drug-like small molecules and their targets. In addition, the book highlights various tools to predict the absorption, distribution, metabolism, excretion (ADME) and toxicity (T) of potential drug candidates. Lastly, it reviews in silico tools that can facilitate vaccine design and discusses their limitations.
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.
Drug repurposing is defined as identifying new pharmacological indications from old, existing, failed, investigational, already marketed, or FDA-approved drugs and prodrugs, and applying these new uses in the treatment of diseases other than the drug’s original intended therapeutic use. The application of computational techniques in discovery research not only helps in the development of drugs from leads or existing drug molecules but can also be useful for the repurposing of existing drug candidates. This new volume presents exciting recent advances in drug repurposing and computational approaches for the discovery and development of drugs against certain difficult-to-treat and life-threatening diseases. With contributions from a global team of experts (academicians, scientists, and researchers), it explores the sophisticated tools and techniques of drug repurposing and computational drug discovery. It delivers valuable information on computational techniques, tools, and databases being utilized for drug repurposing and for identifying the uses of existing drug candidates on different emerging or deadly diseases. Drug repurposing and computational approaches addressed in the book target the discovery and development of drugs for microbial infections (bacterial, fungal, viral, COVID-19), parasitic diseases and neglected tropical diseases (NTDs), malignant diseases (cancer), inflammatory diseases, cardiovascular disorders, diabetes, and aging and neurological (CNS) disorders. In addition, the challenges and regulatory issues encountered in drug repurposing and computational drug discovery programs are looked at, offering perspectives for future directions.
An essential outline of the main facets of polypharmacology in drug discovery research Extending drug discovery opportunities beyond the "one drug, one target" philosophy, a polypharmacological approach to the treatment of complex diseases is emerging as a hot topic in both industry and academic research. Polypharmacology in Drug Discovery presents an overview of the various facets of polypharmacology and how it can be applied as an innovative concept for developing medicines for treating bacterial infections, epilepsy, cancer, psychiatric disorders, and more. Filled with a collection of instructive case studies that reinforce the material and illuminate the subject, this practical guide: Covers the two-sided nature of polypharmacology—its contribution to adverse drug reactions and its benefit in certain therapeutic drug classes Addresses the important topic of polypharmacology in drug discovery, a subject that has not been thoroughly covered outside of scattered journal articles Overviews state-of-the-art approaches and developments to help readers understand concepts and issues related to polypharmacology Fosters interdisciplinary drug discovery research by embracing computational, synthetic, in vitro and in vivo pharmacological and clinical aspects of polypharmacology A clear road map for helping readers successfully navigate around the problems involved with promiscuous ligands and targets, Polypharmacology in Drug Discovery provides real examples, in-depth explanations and discussions, and detailed reviews and opinions to spark inspiration for new drug discovery projects.