In Silico Modeling of Drugs Against Coronaviruses

Computational Tools and Protocols
1. Auflage 2021
ISBN: 978-1-0716-1365-8
Verlag: Springer

Buch, Englisch, 788 Seiten, Book w. online files / update, Format (B × H): 183 mm x 260 mm, Gewicht: 1702 g

Reihe: Methods in Pharmacology and Toxicology

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.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Roy, Kunal

Fachgebiete

• Naturwissenschaften Biowissenschaften Virologie
• Naturwissenschaften Chemie Chemie Allgemein
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Pharmakologie, Toxikologie
• Naturwissenschaften Chemie Physikalische Chemie Quantenchemie, Theoretische Chemie
• Mathematik | Informatik EDV | Informatik Professionelle Anwendung Computersimulation & Modelle, 3-D Graphik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Medizinische Mikrobiologie & Virologie
• Technische Wissenschaften Technik Allgemein Modellierung & Simulation
• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Biotechnologie

Inhaltsverzeichnis

Section I: Introduction

1. History and Recent Advances in Coronavirus Discovery

            Sora Abdul-Fattah, Aman Pal, Nagham Kaka, and Pramath Kakodkar

2. The Origin, Transmission, and Clinical Therapies in the Management of Coronavirus Diseases

            Nagham Kaka, Aman Pal, Sora Abdul-Fattah, and Pramath Kakodkar

3. Transmission, Medical Consequences, and Prevention/Treatment of COVID-19 Infection

            Suliman Khan, Rabeea Siddique, and Aigerim Bizhanova

4. Molecular-Level Targets for Development of Therapies Against Coronavirus Diseases

            Qiongqiong Angela Zhou, Roger Granet, and Linda V. Garner

5. Candidate Drugs for the Potential Treatment of Coronavirus Diseases

            Thanigaimalai Pillaiyar, Manoj Manickam, Sangeetha Meenakshisundaram, and Ajith Jerome Benjamine

 

Section II: Tools and Methodologies

6. Ligand-Based Approaches for Development of Drugs Against SARS-CoV-2

            Ekampreet Singh, Rameez Jabeer Khan, Rajat Kumar Jha, Gizachew Muluneh Amera, Monika Jain, Rashmi Prabha Singh, Jayaraman Muthukumaran, and Amit Kumar Singh

7. Computational Drug Repurposing for Development of Drugs Against Coronaviruses

            Ekampreet Singh, Rameez Jabeer Khan, Rajat Kumar Jha, Gizachew Muluneh Amera, Monika Jain, Rashmi Prabha Singh, Jayaraman Muthukumaran, and Amit Kumar Singh

8. Computational Methods and Tools for Repurposing of Drugs Against Coronaviruses

            Sohini Chakraborti, Sneha Bheemireddy, and Narayanaswamy Srinivasan

9. Molecular Multi-Target Approach on COVID-19 for Designing Novel Chemicals

            Pawan Kumar and Indira Ghosh

 

10. Structural Bioinformatics to Unveil Weaknesses of Coronavirus Spike Glycoprotein Stability

            Pietro Bongini, Alfonso Trezza, Monica Bianchini, Ottavia Spiga, and Neri Niccolai

11. Protein-Protein Interaction Network for Identification of New Targets Against Novel Coronavirus

            Suresh Kumar

12. Nonequilibrium Alchemical Simulations for the Development of Drugs Against COVID-19

            Marina Macchiagodena, Maurice Karrenbrock, Marco Pagliai, Guido Guarnieri, Francesco Iannone, and Piero Procacci

13. Therapeutic and Vaccine Strategies for Stopping the COVID-19 Pandemic Based on Structural and Molecular Modelling Studies of Virus-Ganglioside Interactions

            Jacques Fantini

14. Discovery of Covalent Drugs Targeting the Key Enzymes of SARS-CoV-2 Using SCARdock

            Qi Song, Zhiying Wang, and Sen Liu

15. Machine Learning Techniques for Development of Drugs Against Coronavirus-2019 (COVID-19): A Case Study Protocol

            Saurabh Sharma, Ajay Prakash, Phulen Sarma, and Bikash Medhi

Section III: Case Studies and Literature Reports

16. Dissecting the Drug Development Strategies Against SARS-CoV-2 Through Diverse Computational Modeling Techniques

            Nilanjan Adhikari, Sk. Abdul Amin, and Tarun Jha

17. Recent Perspectives on COVID-19 and Computer-Aided Virtual Screening of Natural Compounds for the Development of Therapeutic Agents towards SARS-CoV-2

            Dharshini Gopal and Sinosh Skariyachan

18. Computational Modeling of Protease Inhibitors for the Development of Drugs Against Coronaviruses

            Joseph T. Ortega, Beata Jastrzebska, and Hector R. Rangel

19. Computational Modeling of ACE2-Mediated Cell Entry Inhibitors for the Development of Drugs Against Coronaviruses

            Priyanka De and Kunal Roy

 

20. Computational Modeling of RdRp Inhibitors for the Development of Drugs Against Novel Coronavirus (nCoV)

            Vinay Kumar and Kunal Roy

21. Computational Modeling of Chloroquine Analogues for Development of Drugs Against Novel Coronavirus (nCoV)

            Vinay Kumar and Kunal Roy

22. Computational Modeling of ACE2 Inhibitors for Development of Drugs Against Coronaviruses

            Rupa Joshi, Seema Bansal, Deepti Malik, Rubal Singla, Abhishek Mishra, Ajay Prakash, and Bikash Medhi

23. Deep Learning-Based Drug Screening for COVID-19 and Case Studies

            Konda Mani Saravanan, Haiping Zhang, Md. Tofazzal Hossain, Md. Selim Reza, and Yanjie Wei

24. Virtual Screening of Natural Compounds Targeting Proteases of Coronaviruses and Picornaviruses

            Sirin Theerawatanasirikul and Porntippa Lekcharoensuk

25. Molecular Simulation Driven Drug Repurposing for Identification of Inhibitors Against Non-Structural Proteins of SARS-CoV-2

            Amita Pathak, Bhumika Singh, Dheeraj Kumar Chaurasia, and B. Jayaram

Section IV: Online Tools and Databases

26. Online Tools and Antiviral Databases for the Development of Drugs Against Coronaviruses

            Rahul Balasaheb Aher and Dhiman Sarkar

27. Online Resource and Tools for the Development of Drugs Against Novel Corona Virus

            Suresh Kumar

28. Drug Databases for Development of Therapeutics Against Coronaviruses

            Supratik Kar and Jerzy Leszczynski

Über Autor(innen)

Dr. Kunal Roy is Professor & Head of the Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India (https://sites.google.com/site/kunalroyindia). He has been a recipient of the Commonwealth Academic Staff Fellowship (University of Manchester, 2007) and Marie Curie International Incoming Fellowship (University of Manchester, 2013) and was a former visiting scientist of Istituto di Ricerche Farmacologiche "Mario Negri" IRCCS, Milano. Italy. The field of his research interest is Quantitative Structure-Activity Relationship (QSAR) and Molecular Modeling with application in Drug Design, Property Modeling, and Predictive Ecotoxicology. Dr. Roy has published more than 300 research articles (ORCID: http://orcid.org/0000-0003-4486-8074) in refereed journals (current SCOPUS h index 43; total citations till date 9562). He has also coauthored two QSAR related books (with Academic Press and Springer Nature), edited six QSAR books (Springer Nature, Academic Press, and IGI Global), and published more than ten book chapters. Dr. Roy is the Co-Editor-in-Chief of Molecular Diversity (Springer Nature) and Editor-in-Chief of International Journal of Quantitative Structure-Property Relationships (IGI Global). Dr. Roy serves on the Editorial Boards of several international journals including (1) European Journal of Medicinal Chemistry (Elsevier); (2) Journal of Molecular Graphics and Modelling (Elsevier); (3) Computational and Structural Biotechnology Journal (Elsevier); (4) Chemical Biology and Drug Design (Wiley); (5) Expert Opinion on Drug Discovery (Informa); (6) Letters in Drug Design and Discovery (Bentham); and (7) Current Computer-Aided Drug Design (Bentham). Apart from this, Prof. Roy is a regular reviewer for QSAR papers in the journals like Chemosphere (Elsevier), Journal of HazardousMaterials (Elsevier), Ecotoxicology and Environmental Safety (Elsevier), Journal of Chemical Information and Modeling (ACS), ACS Omega (ACS),  RSC Advances (RSC), Molecular Informatics (Wiley), SAR and QSAR in Environmental Research (T&F), etc. Prof. Roy has been recipient of several awards including the AICTE Career Award (2003-04), DST Fast Track Scheme for Young Scientists (2005), Bioorganic and Medicinal Chemistry Most Cited Paper 2003-2006, 2004-2007, and 2006-2009 Awards from Elsevier, The Netherlands,  Bioorganic and Medicinal Chemistry Letters Most Cited Paper 2006-2009 Award from Elsevier, The Netherlands, Professor R. D. Desai 80th Birthday Commemoration Medal & Prize (2017) from Indian Chemical Society, etc. Prof. Roy has been a participant in the EU funded projects nanoBRIDGES and IONTOX apart from several national government funded projects (UGC, AICTE, CSIR, ICMR, DBT, DAE). Prof. Roy has recently been placed in the list of Top 2% science-wide author database of the world (World rank 81 in the subfield of Medicinal & Biomolecular Chemistry)  (https://doi.org/10.1371/journal.pbio.3000918).