Full Description
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 ofDrugs 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.
Contents
- Part I Introduction. - History and Recent Advances in Coronavirus Discovery. - The Origin, Transmission, and Clinical Therapies in the Management of Coronavirus Diseases. - Transmission, Medical Consequences, and Prevention/Treatment of COVID-19 Infection. - Molecular-Level Targets for the Development of Therapies Against Coronavirus Diseases. - Candidate Drugs for the Potential Treatment of Coronavirus Diseases. - Part II Tools and Methodologies. - Ligand-Based Approaches for theDevelopment of Drugs Against SARS-CoV-2. - Computational Drug Repurposing for the Development of Drugs Against Coronaviruses. - Computational Methods and Tools for Repurposing of Drugs Against Coronaviruses. - Molecular Multi-target Approach on COVID-19 for Designing Novel Chemicals. - Structural Bioinformatics to Unveil Weaknesses of Coronavirus Spike Glycoprotein Stability. - Protein-Protein Interaction Network for the Identification of New Targets Against Novel Coronavirus. - Nonequilibrium Alchemical Simulations for the Development of DrugsAgainst Covid-19. - Therapeutic and Vaccine Strategies for Stopping the COVID-19 Pandemic Based on Structural and Molecular Modeling Studies of Virus-Ganglioside Interactions. - Discovery of Covalent Drugs Targeting the Key Enzymes of SARS-CoV-2 Using SCARdock. - Machine Learning Techniques for Development of Drugs Against Coronavirus Disease 2019 (COVID-19): A Case Study Protocol. - Part III Case Studies and Literature Reports. - Dissecting the Drug Development Strategies Against SARS-CoV-2 Through Diverse Computational Modeling Techniques. - Recent Perspectives on COVID-19 and Computer-Aided Virtual Screening ofNatural Compounds for the Development of Therapeutic Agents Towards SARS-CoV-2. - Computational Modeling of Protease Inhibitors for the Development of Drugs Against Coronaviruses. - Computational Modeling of ACE2-Mediated Cell Entry Inhibitors for the Development of Drugs Against Coronaviruses. - Computational Modeling of RdRp Inhibitors for the Development of Drugs against Novel Coronavirus (nCoV). - Computational Modeling of Chloroquine Analogues for Development of Drugs Against Novel Coronavirus (nCoV). - Computational Modeling of ACE2 Inhibitors for Development of Drugs Against Coronaviruses. - Deep Learning-Based Drug Screening for COVID-19 and Case Studies. - Virtual Screening of Natural Compounds Targeting Proteases of Coronaviruses and Picornaviruses. - Molecular Simulation-Driven Drug Repurposing for the Identification of Inhibitors Against Non-Structural Proteins of SARS-CoV-2. - Part IV Online Tools and Databases. - Online Tools and Antiviral Databases for the Development of Drugs Against Coronaviruses. - Online Resource and Tools for the Development of Drugs Against Novel Coronavirus. - Drug Databases for Development of Therapeutics Against Coronaviruses.
