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In Silico Modeling of Drugs Against Coronaviruses

Computational Tools and Protocols

  • Book
  • © 2021

Overview

Editors:
  1. Kunal Roy

    1. Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India

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  • Documents protocols and case studies of computational drug design and computational drug repurposing
  • Features structure-based and ligand-based approaches in drug design
  • Covers machine learning/deep learning techniques in the development of coronavirus therapies
  • Includes online tools and databases useful for computational anti-coronavirus drug development

Part of the book series: Methods in Pharmacology and Toxicology (MIPT)

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Table of contents (28 protocols)

  1. Front Matter

    Pages i-xxvi
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  2. Introduction

    1. Front Matter

      Pages 1-1
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    2. History and Recent Advances in Coronavirus Discovery

      • Sora Abdul-Fattah, Aman Pal, Nagham Kaka, Pramath Kakodkar
      Pages 3-24

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

      • Nagham Kaka, Aman Pal, Sora Abdul-Fattah, Pramath Kakodkar
      Pages 25-44

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

      • Suliman Khan, Rabeea Siddique, Aigerim Bizhanova
      Pages 45-67

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

      • Qiongqiong Angela Zhou, Roger Granet, Linda V. Garner
      Pages 69-84

    6. Candidate Drugs for the Potential Treatment of Coronavirus Diseases

      • Thanigaimalai Pillaiyar, Manoj Manickam, Sangeetha Meenakshisundaram, Ajith Jerom Benjamine
      Pages 85-114

  3. Tools and Methodologies

    1. Front Matter

      Pages 115-115
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    2. Ligand-Based Approaches for the Development of Drugs Against SARS-CoV-2

      • Ekampreet Singh, Rameez Jabeer Khan, Rajat Kumar Jha, Gizachew Muluneh Amera, Monika Jain, Rashmi Prabha Singh et al.
      Pages 117-134

    3. Computational Drug Repurposing for the Development of Drugs Against Coronaviruses

      • Ekampreet Singh, Rameez Jabeer Khan, Rajat Kumar Jha, Gizachew Muluneh Amera, Monika Jain, Rashmi Prabha Singh et al.
      Pages 135-162

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

      • Sohini Chakraborti, Sneha Bheemireddy, Narayanaswamy Srinivasan
      Pages 163-177

    5. Molecular Multi-target Approach on COVID-19 for Designing Novel Chemicals

      • Pawan Kumar, Indira Ghosh
      Pages 179-202

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

      • Pietro Bongini, Alfonso Trezza, Monica Bianchini, Ottavia Spiga, Neri Niccolai
      Pages 203-211

    7. Protein–Protein Interaction Network for the Identification of New Targets Against Novel Coronavirus

      • Suresh Kumar
      Pages 213-230

    8. Nonequilibrium Alchemical Simulations for the Development of Drugs Against Covid-19

      • Marina Macchiagodena, Maurice Karrenbrock, Marco Pagliai, Guido Guarnieri, Francesco Iannone, Piero Procacci
      Pages 231-271

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

      • Jacques Fantini
      Pages 273-290

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

      • Qi Song, Zhiying Wang, Sen Liu
      Pages 291-306

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

      • Saurabh Sharma, Ajay Prakash, Phulen Sarma, Bikash Medhi
      Pages 307-325

  4. Case Studies and Literature Reports

    1. Front Matter

      Pages 327-327
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    2. Dissecting the Drug Development Strategies Against SARS-CoV-2 Through Diverse Computational Modeling Techniques

      • Nilanjan Adhikari, Sk. Abdul Amin, Tarun Jha
      Pages 329-431
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Keywords

About this book

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.

Editors and Affiliations

  • Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India

    Kunal Roy

About the editor

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 Hazardous Materials (Elsevier), Ecotoxicologyand 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).

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