Computational Approaches for Novel Therapeutic and Diagnostic Designing to Mitigate SARS-CoV2 Infection
Revolutionary Strategies to Combat Pandemics
- 1st Edition - July 13, 2022
- Editors: Arpana Parihar, Raju Khan, Ashok Kumar, Ajeet Kumar Kaushik, Hardik Gohel
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 1 1 7 2 - 6
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 9 8 0 0 - 0
Computational Approaches for Novel Therapeutic and Diagnostic Designing to Mitigate SARS-CoV2 Infection: Revolutionary Strategies to Combat Pandemics compiles information about var… Read more
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Request a sales quoteComputational Approaches for Novel Therapeutic and Diagnostic Designing to Mitigate SARS-CoV2 Infection: Revolutionary Strategies to Combat Pandemics compiles information about various computational bioinformatic approaches that can help combat viral infection. The book includes working knowledge of various molecular docking and molecular dynamic simulation approaches that have been exploited for drug repurposing and drug designing purpose. In addition, it sheds light on reverse vaccinomics and immunoinformatic approaches for vaccine designing against SARS-CoV2 infection.
This book is an essential resource for researchers, bioinformaticians, computational biologists, computational chemists and pharmaceutical companies who are working on the development of effective and specific therapeutic interventions and point-of-care diagnostic devices using various computational approaches.
- Covers computational based approaches for designing and repurposing drugs
- Discusses immunoinformatic and reverse vaccinomic approaches for effective vaccine design
- Categorizes information about artificial intelligence-based drug screening and diagnostic tools
- Cover image
- Title page
- Table of Contents
- Copyright
- List of contributors
- Preface
- Acknowledgments
- Chapter 1. Overview of coronavirus pandemic
- Abstract
- 1.1 Emergence and transmission of severe acute respiratory syndrome-Coronavirus-2
- 1.2 Case-fatality rate and mortality
- 1.3 Global response to manage
- 1.4 Future perspectives
- References
- Chapter 2. Epidemiology, transmission and pathogenesis of SARS-CoV-2
- Abstract
- 2.1 Introduction
- 2.2 The emergence of Coronavirus disease-2019 as a pandemic
- 2.3 Origin and transmission of severe acute respiratory syndrome-Coronavirus-2
- 2.4 Infectiousness and transmissibility severe acute respiratory syndrome-Coronavirus-2
- 2.5 Pathogenesis of Coronavirus disease-2019
- 2.6 Effect of host factors on Coronavirus disease-2019 pathogenesis
- 2.7 Conclusion
- Acknowledgment
- References
- Chapter 3. The global impact of pandemics on world economy and public health response
- Abstract
- 3.1 History of pandemics
- 3.2 Impact of pandemics on global economy
- 3.3 Public health response to pandemics and other public health emergencies of international concerns
- 3.4 Future perspectives
- References
- Chapter 4. Genomic, proteomic and metabolomic profiling of severe acute respiratory syndrome-Coronavirus-2
- Abstract
- 4.1 Introduction
- 4.2 Genomics of severe acute respiratory syndrome Coronavirus 2
- 4.3 Proteome of severe acute respiratory syndrome Coronavirus 2
- 4.4 Alteration of host metabolome during severe acute respiratory syndrome-Coronavirus-2 infection
- 4.5 Conclusion
- References
- Chapter 5. Currently available drugs for the treatment of Coronavirus-2
- Abstract
- 5.1 Introduction
- 5.2 Anticoagulants
- 5.3 Role of anticoagulants in Coronavirus disease 2019
- 5.4 Antivirals
- 5.5 Lopinavir/ritonavir
- 5.6 Immunomodulators
- 5.7 Tocilizumab
- 5.8 Baricitinib
- 5.9 Monoclonal antibodies
- 5.10 Sotrovimab
- 5.11 Bamlanivimab plus etesevimab
- 5.12 Investigational therapies
- 5.13 Convalescent plasma
- 5.14 Hydroxychloroquine and chloroquine
- 5.15 2-Deoxy D-glucose (2-DG)
- 5.16 Future perspectives
- 5.17 Conclusion
- References
- Chapter 6. Holistic strategies to mitigate the economic, societal, and health burden of the Coronavirus disease-2019 pandemic
- Abstract
- 6.1 Introduction
- 6.2 Multifaceted effects of Coronavirus disease-2019 on global economy and cushioning strategies
- 6.3 The policy supports across the globe
- 6.4 Reflection of the crisis
- 6.5 Ways to survive, strive, and thrive
- 6.6 Societal impact and diminution strategies to mitigate Coronavirus disease-2019 pandemic burdens
- 6.7 Causes of increasing domestic violence in lockdown phase
- 6.8 Strategies to mitigate Coronavirus disease-2019 related societal problems
- 6.9 The health burden of Coronavirus disease-2019 pandemic and amelioration strategies
- 6.10 Post-Coronavirus disease complications
- 6.11 Coronavirus disease-2019 and mental health
- 6.12 Mitigation strategies to ameliorate the Coronavirus disease-2019 health burden
- 6.13 Futuristic approaches and conclusion
- References
- Chapter 7. Natural products as a therapy to combat against SARS-CoV-2 virus infection
- Abstract
- 7.1 Introduction
- 7.2 Natural molecules targeting TMPRSS2
- 7.3 Natural molecules targeting RdRp
- 7.4 Concluding remarks
- References
- Chapter 8. Advanced high-throughput biosensor-based diagnostic approaches for detection of severe acute respiratory syndrome-coronavirus-2
- Abstract
- 8.1 Introduction
- 8.2 Conventional diagnostic approaches for severe acute respiratory syndrome-coronavirus-2
- 8.3 Biosensors as proof of concepts for rapid detection of severe acute respiratory syndrome-Coronavirus-2
- 8.4 Recent advances in high-throughput biosensor-based diagnostics
- 8.5 Conclusion and future perspectives
- Acknowledgment
- References
- Chapter 9. Pharmacophore mapping and modeling approaches for drug development
- Abstract
- 9.1 Pharmacophore: an introduction
- 9.2 Ligand-bound pharmacophore
- 9.3 Structure-based pharmacophore
- 9.4 Structure–activity relationship role with pharmacophore features
- 9.5 A “multiple compounds-multiple drug targets”-model approach of phytochemical screening of potential lead candidates for multiple targets using pharmacophore approach
- 9.6 Indian traditional natural compound pharmacophore screening for nonstructural proteins
- 9.7 Nonstructural protein 1 virtual screening
- 9.8 Nonstructural protein 3 and its subdomain virtual screening
- 9.9 Papain-like protease and 3CLpro/nonstructural protein 5
- 9.10 Nonstructural proteins 7–8 (copy assistants)
- 9.11 Nonstructural protein 9 virtual screening
- 9.12 Nonstructural protein 10/11 with nonstructural protein 14 and 16
- 9.13 RNA-dependent RNA polymerase (RdRp) or nonstructural protein 12
- 9.14 Nonstructural protein 13 or helicases
- 9.15 Nonstructural protein 14 or N7-methyltransferase
- 9.16 Nonstructural protein 15 or endoribonuclease
- 9.17 Nonstructural protein 16 or 2′-O-methyltransferases
- 9.18 Multiple profiling of pharmacophore and compounds
- 9.19 Conclusion
- Disclosure of interest
- References
- Chapter 10. Quantitative structure–activity relationship-based computational approaches
- Abstract
- 10.1 Introduction
- 10.2 The importance of quantitative structure–activity relationship
- 10.3 Requirements to generate a good quantitative structure–activity relationship model
- 10.4 Applications of quantitative structure–activity relationship in various fields
- 10.5 The different stages of advancement of quantitative structure–activity relationship
- 10.6 Molecular descriptors
- 10.7 Methods of quantitative structure–activity relationship
- 10.8 Data analysis methods
- 10.9 Quantitative structure–activity relationship model validation
- 10.10 Quantitative structure–activity relationship and Coronavirus disease-2019
- 10.11 Conclusion
- References
- Chapter 11. Molecular docking and molecular dynamic simulation approaches for drug development and repurposing of drugs for severe acute respiratory syndrome-Coronavirus-2
- Abstract
- 11.1 Introduction
- 11.2 Drug discovery and development pipelines
- 11.3 Computational approaches for drug discovery and development
- 11.4 Drug repurposing: an overview
- 11.5 Molecular docking and molecular dynamics simulation tools for drug development against severe acute respiratory syndrome-Coronavirus-2 infections
- 11.6 Current trends and future perspectives
- 11.7 Conclusion
- References
- Chapter 12. Computational approaches for drug repositioning and repurposing to combat SARS-CoV-2 infection
- Abstract
- 12.1 Introduction: COVID-19: challenges and issues
- 12.2 Conventional drug discovery versus drug repurposing
- 12.3 Strategies and approaches of drug repurposing
- 12.4 Computational tools used for drug repurposing
- 12.5 Drug-repurposing strategies for COVID-19
- 12.6 Drugs proposed by computational methods that are under clinical trials
- 12.7 Future prospects and conclusion
- Acknowledgments
- Disclosure of interest
- References
- Chapter 13. System and network biology-based computational approaches for drug repositioning
- Abstract
- 13.1 Introduction
- 13.2 Approaches of system biology towards drug repositioning
- 13.3 Computational approaches used in systems biology
- 13.4 Drug repositioning strategies
- 13.5 Validation of computational drug repositioning
- 13.6 Recent systems biology and network-based approaches for drug repositioning for Coronavirus disease-2019
- 13.7 Future aspects
- 13.8 Concluding remark
- References
- Chapter 14. Databases, DrugBank, and virtual screening platforms for therapeutic development
- Abstract
- 14.1 Introduction
- 14.2 LitCovid
- 14.3 Gess
- 14.4 CORDITE
- 14.5 SARSCOVIDB
- 14.6 Severe acute respiratory syndrome-Coronavirus-2 three-dimensional
- 14.7 Coronavirus disease-2019 CG
- 14.8 Coronavirus-AbDab
- 14.9 Coronavirus-GLUE
- 14.10 CoV2ID
- 14.11 ZINC
- 14.12 VIStEDD
- 14.13 SMART
- 14.14 Immune epitope database
- 14.15 SWISS-MODEL
- 14.16 Iterative threading assembly refinement
- 14.17 Drugs against severe acute respiratory syndrome-Coronavirus-2
- 14.18 Advantages and disadvantages
- 14.19 Virtual screening platforms
- 14.20 Webservers
- 14.21 Conclusion
- 14.22 Future prospective
- References
- Chapter 15. Absorption, distribution, metabolism, excretion, and toxicity assessment of drugs using computational tools
- Abstract
- 15.1 Introduction
- 15.2 Molecular modeling
- 15.3 Ligand-based methods
- 15.4 Structure-based methods
- 15.5 Databases
- 15.6 Machine learning-based approach
- 15.7 Aborption, distribution, metabolism, excretion, and toxicity predictors and tools
- 15.8 Conclusion
- References
- Chapter 16. Immunoinformatics and reverse vaccinomic approaches for effective design
- Abstract
- 16.1 Introduction
- 16.2 Conclusion
- References
- Chapter 17. Artificial intelligence-based drug screening and drug repositioning tools and their application in the present scenario
- Abstract
- 17.1 Introduction
- 17.2 Current state-of-the-art of artificial intelligence in drug discovery
- 17.3 Advantages and drawbacks
- 17.4 Challenges of artificial intelligence in drug discovery
- 17.5 Opportunities and future prospects
- Acknowledgments
- References
- Chapter 18. Machine Learning and Deep Learning based AI Tools for Development of Diagnostic Tools
- Abstract
- 18.1 Introduction
- 18.2 Artificial intelligence for medical diagnosis
- 18.3 Machine learning and deep learning-based artificial intelligence tools
- 18.4 Machine learning for diagnostic applications
- 18.5 Deep learning in diagnostic applications
- 18.6 Objectives and challenges of severe acute respiratory syndrome-Coronavirus-2 diagnostic tools
- 18.7 Diagnostic tools for severe acute respiratory syndrome-Coronavirus-2—case study
- 18.8 Summary
- References
- Chapter 19. Present therapeutic and diagnostic approaches for SARS-CoV-2 infection
- Abstract
- 19.1 Introduction
- 19.2 Therapeutic approaches for the treatment of Coronavirus disease-2019
- 19.3 Diagnosis of severe acute respiratory syndrome-Coronavirus-2 pathogenesis
- 19.4 Concluding remarks and future prospects
- Acknowledgment
- References
- Chapter 20. Clinically available/under trial drugs and vaccines for treatment of SARS-COV-2
- Abstract
- 20.1 Introduction
- 20.2 Structure, symptoms, and remedies
- 20.3 Important drug target of SARS-COV-2
- 20.4 Various therapeutic approaches
- 20.5 Drugs being used
- 20.6 Approaches for vaccine against SARS-COV-2
- 20.7 Currently available/under clinical trial vaccines
- 20.8 Future prospects
- 20.9 Conclusion
- References
- Chapter 21. Present and future challenges in therapeutic designing using computational approaches
- Abstract
- 21.1 Introduction
- 21.2 Therapeutic designing using computational approaches
- 21.3 Design of nucleic acid-based therapeutics and related issues
- 21.4 Computational therapeutic design and Coronavirus disease-2019
- 21.5 Present and future challenges in the design of therapeutic strategies
- 21.6 Conclusion
- References
- Chapter 22. Digital healthcare data management using blockchain technology in genomics and COVID-19
- Abstract
- 22.1 Introduction
- 22.2 Literature review
- 22.3 Summary and conclusion
- References
- Chapter 23. Prediction of drug–target interaction —a helping hand in drug repurposing
- Abstract
- 23.1 Introduction
- 23.2 Drug–target interaction and SARS-CoV-2
- 23.3 Conclusion
- References
- Chapter 24. Artificial intelligence methods to repurpose and discover new drugs to fight the Coronavirus disease-2019 pandemic
- Abstract
- 24.1 Introduction
- 24.2 Artificial intelligence in drug discovery
- 24.3 Selected drug repurposing strategies
- 24.4 Future perspectives and challenges
- 24.5 Conclusions
- References
- Chapter 25. Severe acute respiratory syndrome coronavirus-2: An era of struggle and discovery leading to the emergency use authorization of treatment and prevention measures based on computational analysis
- Abstract
- 25.1 Introduction
- 25.2 Severe acute respiratory syndrome-Coronavirus-2
- 25.3 Coronavirus disease-2019 treatment options
- 25.4 Coronavirus disease-2019 vaccinations
- 25.5 Severe acute respiratory syndrome-Coronavirus-2 variants
- 25.6 Current challenges and future perspective
- 25.7 Summary
- References
- Index
- No. of pages: 618
- Language: English
- Edition: 1
- Published: July 13, 2022
- Imprint: Academic Press
- Paperback ISBN: 9780323911726
- eBook ISBN: 9780323998000
AP
Arpana Parihar
RK
Raju Khan
Raju Khan is a Senior Principal Scientist and Professor, at CSIR-Advanced Materials and Processes Research Institute, Bhopal. He did his PhD in Chemistry in 2005 from Jamia Millia Islamia, Central University, New Delhi, and Postdoctoral researcher at the “Sensor Research Laboratory” University of the Western Cape, Cape Town. His current research involved synthesizing novel materials to fabricate electrochemical and fluorescence-based biosensors integrated with microfluidics to detect target disease risk biomarkers for health care monitoring. He has published over 150 papers in SCI journal, which attracted over 5500 citations as per Google Scholar, published 45 book chapters in the reputed book Elsevier and Taylor Francis, editing of 28 books from Elsevier and Taylor Francis, and his research has been highlighted in Nature India. He has supervised 5 PhD and 30 undergraduate/postgraduate theses and has supervised 4 numbers of postdoctoral fellows under the scheme of N-PDF, CSIR-Nehru Fellowship, and DST-Women Scientist Projects.
AK
Ashok Kumar
AK
Ajeet Kumar Kaushik
Dr. Ajeet Kaushik is Associate Professor at the NanoBioTech Laboratory, Department of Environmental Engineering, Florida Polytechnic University, USA. He is the recipient of various reputed awards for his service in the area of nano-biotechnology for health care. He has edited seven books, written more than 100 international research peer reviewed publications, and has three patents in the area of nanomedicine and smart biosensors for personalized health care. In the course of his research, Dr. Kaushik has been engaged in the design and development of various electro-active nanostructures for electrochemical biosensor and nanomedicine for health care. His research interests include nanobiotechnology, analytical systems, design and develop nanostructures, nano-carries for drug delivery, nano-therapeutics for CNS diseases, on-demand site-specific release of therapeutic agents, exploring personalized nanomedicines, biosensors, point-of-care sensing devices, and related areas of health care monitoring.
HG