This essential volume explores a variety of tools and protocols of structure-based (homology modeling, molecular docking, molecular dynamics, protein-protein interaction network) and ligand-based (pharmacophore mapping, quantitative structure-activity relationships or QSARs) drug design for ranking and prioritization of candidate molecules in search of effective treatment strategy against coronaviruses. Beginning with an introductory section that discusses coronavirus interactions with humanity and COVID-19 in particular, the book then continues with sections on tools and methodologies, literature reports and case studies, as well as online tools and databases that can be used for computational anti-coronavirus drug research. Written for the Methods in Pharmacology and Toxicology series, chapters include the kind of practical detail and implementation advice that ensures high quality results in the lab. Comprehensive and timely, In Silico Modeling of Drugs Against Coronaviruses: Computational Tools and Protocols is an ideal reference for researchers working on the development of novel anti-coronavirus drugs for SARS-CoV-2 and for coronaviruses that will likely appear in the future.

Coronavirus Drug Discovery, Volume Three: Druggable Targets and In Silico Update presents comprehensive information on drug discovery against COVID-19. Chapters in Part One of this volume describe the various druggable targets and associated signaling pathways for effective targeting of SARS-CoV-2. In Part Two, chapters discuss the various computational approaches and in silico studies against SARS-CoV-2. Written by global team of experts, this book is an excellent resource that will be extremely useful to drug developers, medicinal chemists, pharmaceutical companies in R&D, research institutes in both academia and industry, and the National Library of Medicines and Health. In addition, agencies such as the National Institutes of Health, Centers for Disease Control and Prevention, World Health Organization, European Medicines Agency, the US Food and Drug Administration, and all others involved in drug discovery against COVID-19 will find this book useful. Discusses the pathogenic mechanisms of SARS-CoV-2 and druggable targets Reviews the various signaling pathways associated with SAR-CoV-2 as possible druggable targets Presents computational approaches and in silico studies against SARS-CoV-2

Infectious diseases caused by viruses, parasites, bacteria, and fungi are the number one cause of death worldwide. Although new technologies have improved diagnosis of infectious diseases, the efficacy of all known current anti-infective agents is threatened by the spread of drug-resistant forms of the pathogens. Hence, there remains an urgent need to develop anti-infective agents that target drug-resistant pathogens. In Silico Models for Drug Discovery presents a comprehensive look at the role in silico models play in understanding infectious diseases and in developing novel therapeutics to treat them. Written by leading experts in the field, chapters cover topics such as techniques to derive novel antimicrobial targets, methods of interpreting polypharmacology-based drug target networks, and molecular dynamics techniques used to compute binding energies of drugs to their target proteins, to name a few. Written in the successful Methods in Molecular BiologyTM series or in review article format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible protocols, and notes on troubleshooting and avoiding known pitfalls. Authoritative and easily accessible, In Silico Models for Drug Discovery seeks to serve both professionals and novices involved in the study and treatment of infectious diseases.

This book provides a comprehensive overview of recent novel coronavirus (SARS-CoV-2) infection, their biology and associated challenges for their treatment and prevention of novel Coronavirus Disease 2019 (COVID-19). Discussing various aspects of COVID-19 infection, including global epidemiology, genome organization, immunopathogenesis, transmission cycle, diagnosis, treatment, prevention, and control strategies, it highlights host-pathogen interactions, host immune response, and pathogen immune invasion strategies toward developing an immune intervention or preventive vaccine for COVID-19. An understanding of the topics covered in the book is imperative in the context of designing strategies to protect the human race from further losses and harm due to SARS-CoV-2 infection causing COVID-19.

This book proposes applications of tensor decomposition to unsupervised feature extraction and feature selection. The author posits that although supervised methods including deep learning have become popular, unsupervised methods have their own advantages. He argues that this is the case because unsupervised methods are easy to learn since tensor decomposition is a conventional linear methodology. This book starts from very basic linear algebra and reaches the cutting edge methodologies applied to difficult situations when there are many features (variables) while only small number of samples are available. The author includes advanced descriptions about tensor decomposition including Tucker decomposition using high order singular value decomposition as well as higher order orthogonal iteration, and train tenor decomposition. The author concludes by showing unsupervised methods and their application to a wide range of topics. Allows readers to analyze data sets with small samples and many features; Provides a fast algorithm, based upon linear algebra, to analyze big data; Includes several applications to multi-view data analyses, with a focus on bioinformatics.

This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact.

Human coronaviruses caused the SARS epidemic that infected more than 8000 people, killing about ten percent of them in 32 countries. This book provides essential information on these viruses and the development of vaccines to control coronavirus infections.