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M Ethods in P Harmacology and T Oxicology M ETHODS IN P HARMACOLOGY AND T OXICOLOGY Series Editor Y. James Kang Department of Pharmacology and Toxicology, University of Louisville Louisville, KY, USA For further volumes: http://www.springer.com/series/7653 Methods in Pharmacology and Toxicology publishes cutting-edge techniques, including meth- ods, protocols, and other hands-on guidance and context, in all areas of pharmacological and toxicological research. Each book in the series offers time-tested laboratory protocols and expert navigation necessary to aid toxicologists and pharmaceutical scientists in labora- tory testing and beyond. With an emphasis on details and practicality, Methods in Pharma- cology and Toxicology focuses on topics with wide-ranging implications on human health in order to provide investigators with highly useful compendiums of key strategies and approaches to successful research in their respective areas of study and practice. In Silico Modeling of Drugs Against Coronaviruses Computational Tools and Protocols Edited by Kunal Roy Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India Editor Kunal Roy Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology Jadavpur University Kolkata, India ISSN 1557-2153 ISSN 1940-6053 (electronic) Methods in Pharmacology and Toxicology ISBN 978-1-0716-1365-8 ISBN 978-1-0716-1366-5 (eBook) https://doi.org/10.1007/978-1-0716-1366-5 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2021 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Humana imprint is published by the registered company Springer Science+Business Media, LLC part of Springer Nature. The registered company address is: 1 New York Plaza, New York, NY 10004, U.S.A. Dedication For Aatreyi, Arpit, and Chaitali Preface Coronaviruses (CoVs) (belonging to the family Coronaviridae, subfamily Coronavirinae) are enveloped viruses with single-stranded, positive-sense RNA having ~26–32 kb genome [1]. Coronaviruses primarily infect birds and mammals, but they can also infect humans and cause diseases of varying severity. Coronaviruses infecting humans historically included several mild common cold viruses, such as hCoV-OC43, HKU, and 229E [2]. However, in the last two decades, they have also been found to cause severe diseases such as severe acute respiratory syndrome (SARS) in 2002–2003 and Middle East respiratory syndrome (MERS) in 2012 [3]. At the end of 2019, a cluster of pneumonia cases occurred in Wuhan, China. It then quickly spread to other parts of the world causing a pandemic situation popularly termed as Coronavirus Disease-2019 (COVID-2019). This is a respiratory disease caused by a novel beta-coronavirus strain, SARS-CoV-2, which has led to over 52,487,476 confirmed cases and 1,290,653 fatalities in over 200 countries (as of 13 November 2020) since its emergence. The two-thirds of the CoV genome correspond to genes for nonstruc- tural proteins. Among the structural proteins, spike (S), envelope (E), and membrane (M) proteins are contained within the viral membrane among which the last two proteins are involved in viral assembly, while the nucleocapsid (N) protein is required for RNA genome assembly. The surface-located trimeric glycoprotein of CoVs (S protein) plays a functional role in viral entry into host cells, viral infection, and pathogenesis. It has thus been considered as a major therapeutic target for development of therapies and vaccines against SARS-CoV and MERS-CoV [4]. This S protein mediates host cell invasion via binding to a receptor protein called angiotensin-converting enzyme 2 (ACE2) found in the lower respiratory tract of humans [5] and regulates both the cross-species and human-to-human transmission. This invasion process is facilitated by the host cell-produced serine protease TMPRSS211. There are several nonstructural proteins including RNA-dependent RNA polymerase (RdRp), coronavirus main protease (3CLpro), and papain-like protease (PLpro) encoded by the viral genome. After entering to the host cells, the viral genome is released as a single-stranded positive RNA, which is then translated into viral polyproteins using host cell protein translation machinery. RdRp synthesizes a full-length negative-strand RNA template to be used to make more viral genomic RNA [6]. The viral polyproteins are cleaved into effector proteins by viral proteinases 3CLpro and PLpro, the latter also behaving as a deubiquitinase that may deubiquinate certain host cell proteins, including interferon factor 3 and NF-κB, resulting in immune suppression. Currently there are no antiviral drugs or vaccines1 with proven efficacy approved against COVID-19, although several vaccines have been claimed to be in the advanced stages of clinical trials. The devastating impact of the current COVID-19 outbreak and the possibility of future CoV epidemics strongly warrant the rapid development of new treatments and fast intervention protocols [7]. Unfortunately, the scientific community has limited knowledge of the molecular details of SARS-CoV-2 infection. Despite the fact that CoVs have under- gone substantial genetic evolution, they still have considerable similarities, which should be a basis for the identification of promising targets for antiviral therapies and vaccines against 1 In 2021, several vaccines against COVID-19 have become available. For details, please see https://www.who. int/news-room/q-a-detail/coronavirus-disease-(covid-19)-vaccines vii viii Preface 2019-nCoV. Researchers should focus on the proteins that are highly conserved across multiple CoVs. Despite the fact that SARS-CoV and SARS-CoV-2 viruses demonstrate only 79% sequence similarity at the genome level, RdRp and 3CLpro protease of SARS-CoV- 2 share over 95% of sequence similarity with those of SARS-CoV [6]. These viruses share a highly conserved receptor-binding domain (RBD) and 76% of sequence similarity in their S proteins based on sequence alignment and homology modeling. Although the PLpro sequences of SARS-CoV-2 and SARS-CoV are only 83% similar, they share similar active sites. The currently identified targets for possible development of drugs against SARS-CoV- 2 infection include [6]: 3CLpro (coronavirus main protease 3CLpro), PLpro (papain-like protease PLpro), RdRp (RNA-dependent RNA polymerase), S protein (viral spike glyco- protein), TMPRSS2 (transmembrane protease serine 2), ACE2 (angiotensin-converting enzyme 2), AT2 (angiotensin AT2 receptor), etc. Computational drug repurposing procedures [8] can easily be implemented to identify suitable drugs for different identified targets. This is an effective approach to find new indications for already known drugs within a short period which can be used to overcome the emergence of resistance to existing antiviral drugs and re-emerging viral infections. This approach typically relies on an integrated pipeline including a virtual screening of drug libraries to find suitable drug-target pairs using molecular similarity methods and homology modeling to model the target [4]. Molecular docking and binding free energy calculations are used to predict drug-target interactions and binding affinity. Molecular dynamics help us to understand the stability of interactions between the ligand and receptor in a time- dependent manner. Although drug repurposing may provide a short-term and nonspecific solution for treatment of COVID-19 patients, it is highly desirable to develop more targeted novel inhibitors. In view of the urgency of developing drugs against coronaviruses including SARS-CoV- 2, computational modeling including both structure-based and ligand-based approaches appears to be very appropriate. The current literature shows worldwide efforts in the search of effective drugs against coronaviruses including SARS-CoV-2 [9]. The present volume intends to document different tools and protocols of structure-based (homology modeling, molecular docking, molecular dynamics, protein-protein interaction network, etc.) and ligand-based (pharmacophore mapping, quantitative structure-activity relationships or QSARs) drug design [10–12] for ranking and prioritization of candidate molecules in search of effective treatment strategy against coronaviruses. Attempts have also been made to cover machine learning/deep
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