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 methods, 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 laboratory 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

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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 nonstructural 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 glycoprotein), 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 learning techniques in this endeavor. The 28 chapters of this volume are organized into four parts: Introduction, Tools and Methodologies, Case Studies and Literature Reports, and finally, Online Tools and Databases. The first chapter of the Introduction part (authored by Kakodkar and group) presents the basics of coronavirus virology and discusses the history and origins of the human coronavirus cluster as well as severe epidemic/pandemic causing coronaviruses. The same group of authors discusses, in the second chapter, the evolution of the human coronaviruses and possible clinical therapies against them. In the third chapter, Khan and colleagues discuss the spread and/or transmission of SARS-CoV-2 and the associated complications and also summarize the therapeutic and prevention options, and the most salient features of COVID- 19. Zhou and colleagues discuss, in the fourth chapter, various promising target proteins for Preface ix treating coronavirus infections in terms of their structure, function, and possible chemical or biological modulators. In the last chapter of Part I, Pillaiyar and others discuss molecular level targets for the development of therapies against coronavirus diseases and mention different candidate drugs. The next part on Tools and Methodologies starts with a chapter contributed by Singh and colleagues, which discusses the role of a computational approach of ligand-based drug designing to identify, screen, or design potential drug molecules against SARS-CoV-2. The same group of authors discusses, in the next chapter, the role of computational drug repurposing against SARS-CoV-2 and explains its methodological aspects. The next chapter authored by Srinivasan and colleagues provides an overview of various computational methods, which can be efficiently used to repurpose drugs against any disease including COVID-19. In the next chapter, Kumar and Ghosh review different computational methods applied in search of inhibitors against the targets of COVID-19. In addition, they attempt to generate multi-target specific ab initio pharmacophore models to search for the specific novel inhibitors from a database of antiviral chemicals. Bianchini and colleagues explore, in the next chapter, the trimer interfaces of the S-glycoprotein in the search of pockets that can be suitable for ligand binding, thus paving the way toward finding an alternative family of antiviral drugs. The next chapter contributed by Kumar explores the available experiments and computations of protein-protein interaction methods to identify anti-SARS-CoV- 2 drugs. Procacci and colleagues describe, in the next chapter, an alchemical molecular dynamics technique based on nonequilibrium thermodynamics which can be combined with alchemical relative binding free energy calculations providing an automatable workflow for drug optimization starting from a set of chemically distant ligands in the fight against the coronavirus pandemic. Fantini discusses, in the next chapter, different therapeutic and vaccine strategies based on the ganglioside-binding domain of the N-terminal domain of the SARS-CoV-2 S protein. In the next chapter, Liu and others discuss a simple but efficient method using SCARdock for the discovery of covalent drugs against COVID-19. The last chapter of this part, contributed by Medhi and colleagues, presents a detailed protocol to scan and validate the therapeutic targets for COVID-19 and screen promising compounds for future in vitro or in vivo validation. Part III of this book deals with literature reports and case studies. The first chapter of this part contributed by Jha and colleagues discusses various structure-based drug design and discovery strategies from target identification to lead optimization against SARS-CoV- 2 along with ongoing and previously reported computational modeling studies performed by different groups of researchers on various SARS-CoV-2 target proteins. Gopal and Skariyachan, in the next chapter, focus on portraying the relevance of utilizing natural lead molecules by virtual screening and pharmacokinetics prediction for the development of effective lead molecules against SARS-CoV-2. Rangel and colleagues, in the next chapter, focus on the structural features of the SARS-CoV-2 Mpro that could be applied to developing new therapies using computational methods. The next chapter, contributed by De and Roy, focuses on computational studies involving potential inhibitors of ACE2-mediated entry of coronaviruses. Kumar and Roy deal with recently published computational studies for the identification or development of novel RdRp inhibitors in the next chapter. The same authors present, in the next chapter, recently published reports on in silico modeling of chloroquine analogues for the design and identification of novel drugs against SARS-CoV- 2. The next chapter, contributed by Medhi and coworkers, covers the importance of human ACE2 receptor in the pathophysiology of COVID-19 infection with the literature reports of x Preface various computational studies for the development of drugs with promise against COVID- 19. Wei and colleagues, in the next chapter, focus on the integrated applications of deep learning models as a pipeline for drug and vaccine discovery which has implications in therapeutic drug targeting for COVID-19. Next, Theerawatanasirikul and Lekcharoensuk describe the procedure of virtual screening for specific molecules targeting proteases of coronaviruses and picornaviruses. Jayaram and colleagues computationally identify, in the last chapter of this part, a few drugs showing good molecular interactions with known targets of SARS-CoV-2. The last part of this volume is on online tools and databases that can be used for computational anti-coronavirus drug research. Aher and Sarkar, in the first chapter of this part, collect and compile information on open-access online tools and antiviral databases essential for the discovery and development of corona vaccine and anti-COVID drugs. Next, Kumar discusses different resources and tools available for drug development against the novel coronavirus. The last chapter of the book is contributed by Kar and Leszczynski, who have enlisted and discussed the top twenty-five small molecule databases, including both synthetic and natural compounds, which can be strategically screened employing multiple computational techniques to discover therapeutics for COVID-19. It is hoped that this volume will be very timely in view of the current COVID-19 pandemic and useful for the researchers working on the development of novel anti- coronavirus drugs.

Kolkata, India November 2020 Kunal Roy

References

1. Schoeman D, Fielding BC (2019) Coronavirus envelope protein: current knowledge. Virol J 16:69. https://doi.org/10.1186/s12985-019-1182-0 2. Fielding BC (2011) Human coronavirus NL63: a clinically important virus? Future Microbiol 6 (2):153–159. https://doi.org/10.2217/fmb.10.166 3. Guo Y-R, Cao Q-D, Hong Z-S, Tan Y-Y, Chen S-D, Jin H-J, Tan K-S, Wang D-Y, Yan Y (2020) The origin, transmission and clinical therapies on coronavirus disease 2019 (COVID-19) outbreak—an update on the status. Mil Med Res 7:11. https://doi.org/10.1186/s40779-020-00240-0 4. Zhavoronkov A, Aladinskiy V, Zhebrak A, Zagribelnyy B, Terentiev V et al (2020) Potential 2019- nCoV 3C-like protease inhibitors designed using generative deep learning approaches. ChemRxiv. https://doi.org/10.26434/chemrxiv.11829102.v2 5. Gordon DE, Jang GM, Bouhaddou M, Xu J, Obernier K et al (2020) A SARS-CoV-2-human protein- protein interaction map reveals drug targets and potential drug-repurposing. bioRxiv. https://doi. org/10.1101/2020.03.22.002386 6. Liu C, Zhou Q, Li Y, Garner LV, Watkins SP et al (2020) Research and development on therapeutic agents and vaccines for COVID-19 and related human coronavirus diseases. ACS Central Sci 6:315–331. https://doi.org/10.1021/acscentsci.0c00272 7. Ton AT, Gentile F, Hsing M, Ban F, Cherkasov A (2020) Rapid identiﬁcation of potential inhibitors of SARS‐CoV‐2 main protease by deep docking of 1.3 billion compounds. Mol Inform 39:2000028. https://doi.org/10.1002/minf.202000028 8. Roy K (ed) (2019) In silico drug design: repurposing techniques and methodologies. Academic Press, New York. https://doi.org/10.1016/C2017-0-04310-0 Preface xi

9. Ojha PK, Kar S, Krishna JG, Roy K, Leszczynski J (2020) Therapeutics for COVID-19: from computation to practices—where we are, where we are heading to. Mol Divers. https://doi.org/10. 1007/s11030-020-10134-x 10. Roy K, Kar S, Das RN (2015) Understanding the basics of QSAR for applications in pharmaceutical sciences and risk assessment. Academic Press, New York. https://doi.org/10.1016/C2014-0-00286-9 11. Roy K, Kar S, Das RN (2015) A primer on QSAR/QSPR modeling. Springer, New York. https://doi. org/10.1007/978-3-319-17281-1 12. Roy K (ed) (2017) Advances in QSAR modeling. Applications in pharmaceutical, chemical, food, agricultural and environmental sciences. Springer, New York. https://www.springer.com/gp/book/ 9783319568492 Disclaimer

Views expressed in the individual chapters of this book regarding therapeutic treatment strategies of coronavirus infections are solely of the concerned authors and not necessarily endorsed by the Editor and/or Publisher. Current WHO and/or US-FDA recommenda- tions should be followed regarding drugs of choice and dosage regimen for clinical treatment of active novel coronavirus cases. In view of rapid changes in the available information in this ﬁeld, the readers are advised to note that all chapters of this book were ﬁnalized within November 2020. Thus, some of the information shared in these chapters might not be fully updated in the presented version and, in a few cases, might not be valid at the time of reading.

xiii Abbreviations

2019-nCoV 2019-Novel coronavirus 3CLpro 3-Chymotrypsin-like cysteine protease ACE2 Angiotensin-converting enzyme 2 ADMET Absorption, distribution, metabolism, elimination, and toxicity CADD Computer-aided drug design CAS Chemical Abstracts Service COVID-19 Coronavirus disease 2019 FBDD Fragment-based drug design FDA Food and Drug Administration hCoV Human coronavirus hERG Human ether-a-go-go related gene HTVS High-throughput virtual screening LBDD Ligand-based drug design MD Molecular dynamics MERS Middle East respiratory syndrome MM-GBSA Molecular mechanics generalized Born surface area MM-PBSA Molecular mechanics Poisson-Boltzmann surface area Mpro Main protease nsp Nonstructural protein NTD N-terminal domain ORF Open reading frame PDB Protein data bank PLpro Papain-like protease PPI Protein-protein interaction QSAR Quantitative structure-activity relationships RBD Receptor-binding domain RdRp RNA-dependent RNA polymerase RMSD Root-mean-square deviation SARS Severe acute respiratory syndrome SARS-CoV-2 Severe acute respiratory syndrome coronavirus-2 SBDD Structure-based drug design TMPRSS2 Transmembrane protease, serine 2 VS Virtual screening WHO World Health Organization

xv Contents

Dedication ...... v Preface ...... vii Disclaimer ...... xiii Abbreviations ...... xv About the Editor ...... xxi Contributors...... xxiii

PART IINTRODUCTION

History and Recent Advances in Coronavirus Discovery ...... 3 Sora Abdul-Fattah, Aman Pal, Nagham Kaka, and Pramath Kakodkar The Origin, Transmission, and Clinical Therapies in the Management of Coronavirus Diseases ...... 25 Nagham Kaka, Aman Pal, Sora Abdul-Fattah, and Pramath Kakodkar Transmission, Medical Consequences, and Prevention/Treatment of COVID-19 Infection...... 45 Suliman Khan, Rabeea Siddique, and Aigerim Bizhanova Molecular-Level Targets for the Development of Therapies Against Coronavirus Diseases ...... 69 Qiongqiong Angela Zhou, Roger Granet, and Linda V. Garner Candidate Drugs for the Potential Treatment of Coronavirus Diseases...... 85 Thanigaimalai Pillaiyar, Manoj Manickam, Sangeetha Meenakshisundaram, and Ajith Jerom Benjamine

PART II TOOLS AND METHODOLOGIES

Ligand-Based Approaches for the Development of Drugs Against SARS-CoV-2 ...... 117 Ekampreet Singh, Rameez Jabeer Khan, Rajat Kumar Jha, Gizachew Muluneh Amera, Monika Jain, Rashmi Prabha Singh, Jayaraman Muthukumaran, and Amit Kumar Singh Computational Drug Repurposing for the Development of Drugs Against Coronaviruses ...... 135 Ekampreet Singh, Rameez Jabeer Khan, Rajat Kumar Jha, Gizachew Muluneh Amera, Monika Jain, Rashmi Prabha Singh, Jayaraman Muthukumaran, and Amit Kumar Singh Computational Methods and Tools for Repurposing of Drugs Against Coronaviruses ...... 163 Sohini Chakraborti, Sneha Bheemireddy, and Narayanaswamy Srinivasan Molecular Multi-target Approach on COVID-19 for Designing Novel Chemicals ...... 179 Pawan Kumar and Indira Ghosh

xvii xviii Contents

Structural Bioinformatics to Unveil Weaknesses of Coronavirus Spike Glycoprotein Stability...... 203 Pietro Bongini, Alfonso Trezza, Monica Bianchini, Ottavia Spiga, and Neri Niccolai Protein–Protein Interaction Network for the Identiﬁcation of New Targets Against Novel Coronavirus ...... 213 Suresh Kumar Nonequilibrium Alchemical Simulations for the Development of Drugs Against Covid-19 ...... 231 Marina Macchiagodena, Maurice Karrenbrock, Marco Pagliai, Guido Guarnieri, Francesco Iannone, and Piero Procacci Therapeutic and Vaccine Strategies for Stopping the COVID-19 Pandemic Based on Structural and Molecular Modeling Studies of Virus-Ganglioside Interactions ...... 273 Jacques Fantini Discovery of Covalent Drugs Targeting the Key Enzymes of SARS-CoV-2 Using SCARdock ...... 291 Qi Song, Zhiying Wang, and Sen Liu Machine Learning Techniques for Development of Drugs Against Coronavirus Disease 2019 (COVID-19): A Case Study Protocol...... 307 Saurabh Sharma, Ajay Prakash, Phulen Sarma, and Bikash Medhi

PART III CASE STUDIES AND LITERATURE REPORTS

Dissecting the Drug Development Strategies Against SARS-CoV-2 Through Diverse Computational Modeling Techniques...... 329 Nilanjan Adhikari, Sk. Abdul Amin, and Tarun Jha Recent Perspectives on COVID-19 and Computer-Aided Virtual Screening of Natural Compounds for the Development of Therapeutic Agents Towards SARS-CoV-2...... 433 Dharshini Gopal and Sinosh Skariyachan Computational Modeling of Protease Inhibitors for the Development of Drugs Against Coronaviruses...... 473 Joseph T. Ortega, Beata Jastrzebska, and Hector R. Rangel Computational Modeling of ACE2-Mediated Cell Entry Inhibitors for the Development of Drugs Against Coronaviruses ...... 495 Priyanka De and Kunal Roy Computational Modeling of RdRp Inhibitors for the Development of Drugs against Novel Coronavirus (nCoV) ...... 541 Vinay Kumar and Kunal Roy Computational Modeling of Chloroquine Analogues for Development of Drugs Against Novel Coronavirus (nCoV) ...... 579 Vinay Kumar and Kunal Roy Contents xix

Computational Modeling of ACE2 Inhibitors for Development of Drugs Against Coronaviruses...... 615 Rupa Joshi, Seema Bansal, Deepti Malik, Rubal Singla, Abhishek Mishra, Ajay Prakash, and Bikash Medhi Deep Learning-Based Drug Screening for COVID-19 and Case Studies ...... 631 Konda Mani Saravanan, Haiping Zhang, Md. Tofazzal Hossain, Md. Selim Reza, and Yanjie Wei Virtual Screening of Natural Compounds Targeting Proteases of Coronaviruses and Picornaviruses ...... 661 Sirin Theerawatanasirikul and Porntippa Lekcharoensuk Molecular Simulation–Driven Drug Repurposing for the Identiﬁcation of Inhibitors Against Non-Structural Proteins of SARS-CoV-2...... 683 Amita Pathak, Bhumika Singh, Dheeraj Kumar Chaurasia, and B. Jayaram

PART IV ONLINE TOOLS AND DATABASES

Online Tools and Antiviral Databases for the Development of Drugs Against Coronaviruses ...... 717 Rahul Balasaheb Aher and Dhiman Sarkar Online Resource and Tools for the Development of Drugs Against Novel Coronavirus ...... 735 Suresh Kumar Drug Databases for Development of Therapeutics Against Coronaviruses ...... 761 Supratik Kar and Jerzy Leszczynski

Index ...... 781 About the Editor

KUNAL ROY is Professor and 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 44; total citations till date 10270). 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 OpiniononDrugDiscovery(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), 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 (2003–2004); 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- fundedprojects(UGC,AICTE,CSIR,ICMR,DBT,DAE).Prof.Royhasrecentlybeenplacedin 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).

xxi Contributors

SORA ABDUL-FATTAH • School of Medicine, National University of Ireland Galway, Galway, Ireland NILANJAN ADHIKARI • Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India RAHUL BALASAHEB AHER • Combi Chem Bioresource Centre, Organic Chemistry Division (OCD), CSIR-National Chemical Laboratory, Pune, Maharashtra, India GIZACHEW MULUNEH AMERA • Department of Biotechnology, School of Engineering and Technology, Sharda University, Greater Noida, UP, India SK.ABDUL AMIN • Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India SEEMA BANSAL • Department of Pharmacology, Post Graduate Institute of Medical Education and Research, PGIMER, Chandigarh, India AJITH JEROM BENJAMINE • Department of Computer Science and Engineering, PSG Institute of Technology and Applied Research, Coimbatore, Tamil Nadu, India SNEHA BHEEMIREDDY • Molecular Biophysics Unit, Indian Institute of Science, Bengaluru, Karnataka, India MONICA BIANCHINI • Department of Information Engineering and Mathematics, University of Siena, Siena, Italy AIGERIM BIZHANOVA • Department of Cerebrovascular Diseases, The Second Afﬁliated Hospital of Zhengzhou University, Zhengzhou, P. R. China PIETRO BONGINI • Department of Information Engineering and Mathematics, University of Siena, Siena, Italy; Department of Information Engineering, University of Florence, Florence, Italy SOHINI CHAKRABORTI • Molecular Biophysics Unit, Indian Institute of Science, Bengaluru, Karnataka, India DHEERAJ KUMAR CHAURASIA • Supercomputing Facility for Bioinformatics & Computational Biology, Indian Institute of Technology Delhi, New Delhi, India PRIYANKA DE • Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India JACQUES FANTINI • INSERM UMR_S 1072, Aix-Marseille Universite´, Marseille, France LINDA V. GARNER • CAS, a division of the American Chemical Society, Columbus, OH, USA INDIRA GHOSH • School of Computational and Integrative Sciences (SCIS), Jawaharlal Nehru University, New Delhi, India DHARSHINI GOPAL • Department of Bioinformatics, Manipal Academy of Higher Education, Manipal, Karnataka, India ROGER GRANET • CAS, a division of the American Chemical Society, Columbus, OH, USA GUIDO GUARNIERI • DTE-ICT-HPC, ENEA, Portici Research Centre, Portici (NA), Italy MD.TOFAZZAL HOSSAIN • Center for High Performance Computing, Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, P. R. China

xxiii xxiv Contributors

FRANCESCO IANNONE • DTE-ICT-HPC, ENEA, Portici Research Centre, Portici (NA), Italy MONIKA JAIN • Department of Biotechnology, School of Engineering and Technology, Sharda University, Greater Noida, UP, India BEATA JASTRZEBSKA • Department of Pharmacology, School of Medicine, Case Western Reserve University, Cleveland, OH, USA B. JAYARAM • Department of Chemistry, Indian Institute of Technology Delhi, New Delhi, India; Supercomputing Facility for Bioinformatics & Computational Biology, Indian Institute of Technology Delhi, New Delhi, India; Kusuma School of Biological Sciences, Indian Institute of Technology Delhi, New Delhi, India RAJAT KUMAR JHA • Department of Biotechnology, School of Engineering and Technology, Sharda University, Greater Noida, UP, India TARUN JHA • Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India RUPA JOSHI • Department of Pharmacology, Post Graduate Institute of Medical Education and Research, PGIMER, Chandigarh, India NAGHAM KAKA • School of Medicine, National University of Ireland Galway, Galway, Ireland PRAMATH KAKODKAR • School of Medicine, National University of Ireland Galway, Galway, Ireland SUPRATIK KAR • Department of Chemistry, Physics and Atmospheric Sciences, Interdisciplinary Center for Nanotoxicity, Jackson State University, Jackson, MS, USA MAURICE KARRENBROCK • Department of Chemistry, University of Florence, Sesto Fiorentino (FI), Italy RAMEEZ JABEER KHAN • Department of Biotechnology, School of Engineering and Technology, Sharda University, Greater Noida, UP, India SULIMAN KHAN • Department of Cerebrovascular Diseases, The Second Afﬁliated Hospital of Zhengzhou University, Zhengzhou, P. R. China PAWAN KUMAR • National Institute of Immunology (NII), New Delhi, India SURESH KUMAR • Faculty of Health and Life Sciences, Management and Science University, Shah Alam, Selangor, Malaysia VINAY KUMAR • Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India PORNTIPPA LEKCHAROENSUK • Department of Microbiology and Immunology, Faculty of Veterinary Medicine, Kasetsart University, Bangkok, Thailand JERZY LESZCZYNSKI • Department of Chemistry, Physics and Atmospheric Sciences, Interdisciplinary Center for Nanotoxicity, Jackson State University, Jackson, MS, USA SEN LIU • National “111” Center for Cellular Regulation and Molecular Pharmaceutics, Key Laboratory of Industrial Fermentation (Ministry of Education), Hubei University of Technology, Wuhan, China; Institute of Biomedical and Pharmaceutical Sciences, Hubei Key Laboratory of Industrial Microbiology, Hubei University of Technology, Wuhan, China MARINA MACCHIAGODENA • Department of Chemistry, University of Florence, Sesto Fiorentino (FI), Italy DEEPTI MALIK • Department of Pharmacology, Post Graduate Institute of Medical Education and Research, PGIMER, Chandigarh, India; Department of Biochemistry, All India Institute of Medical Sciences, Bilaspur, Himachal Pradesh, India Contributors xxv

MANOJ MANICKAM • Department of Chemistry, PSG Institute of Technology and Applied Research, Coimbatore, Tamil Nadu, India BIKASH MEDHI • Department of Pharmacology, Postgraduate Institute of Medical Education & Research, PGIMER, Chandigarh, India SANGEETHA MEENAKSHISUNDARAM • Department of Chemistry, Sri Krishna College of Engineering and Technology, Coimbatore, Tamil Nadu, India ABHISHEK MISHRA • Department of Pharmacology, Post Graduate Institute of Medical Education and Research, PGIMER, Chandigarh, India JAYARAMAN MUTHUKUMARAN • Department of Biotechnology, School of Engineering and Technology, Sharda University, Greater Noida, UP, India NERI NICCOLAI • Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy; Le Ricerche del BarLume free Association, Siena, Italy JOSEPH T. ORTEGA • Department of Pharmacology, School of Medicine, Case Western Reserve University, Cleveland, OH, USA MARCO PAGLIAI • Department of Chemistry, University of Florence, Sesto Fiorentino (FI), Italy AMAN PAL • School of Medicine, National University of Ireland Galway, Galway, Ireland AMITA PATHAK • Department of Chemistry, Indian Institute of Technology Delhi, New Delhi, India; Supercomputing Facility for Bioinformatics & Computational Biology, Indian Institute of Technology Delhi, New Delhi, India THANIGAIMALAI PILLAIYAR • Department of Pharmaceutical and Medicinal Chemistry, PharmaCenter Bonn, Pharmaceutical Institute, University of Bonn, Bonn, Germany AJAY PRAKASH • Department of Pharmacology, Post Graduate Institute of Medical Education and Research, PGIMER, Chandigarh, India PIERO PROCACCI • Department of Chemistry, University of Florence, Sesto Fiorentino (FI), Italy HECTOR R. RANGEL • Laboratorio de Virologıá Molecular, Centro de Microbiologıá y Biologıá Celular, Instituto Venezolano de Investigaciones Cientı´ficas, Caracas, Venezuela MD.SELIM REZA • Center for High Performance Computing, Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, P. R. China KUNAL ROY • Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India KONDA MANI SARAVANAN • Center for High Performance Computing, Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, P. R. China DHIMAN SARKAR • Combi Chem Bioresource Centre, Organic Chemistry Division (OCD), CSIR-National Chemical Laboratory, Pune, Maharashtra, India PHULEN SARMA • DHR, Department of Pharmacology, GIMER, Chandigarh, India SAURABH SHARMA • ICMR, Department of Pharmacology, PGIMER, Chandigarh, India RABEEA SIDDIQUE • Department of Cerebrovascular Diseases, The Second Affiliated Hospital of Zhengzhou University, Zhengzhou, P. R. China AMIT KUMAR SINGH • Department of Biotechnology, School of Engineering and Technology, Sharda University, Greater Noida, UP, India BHUMIKA SINGH • Supercomputing Facility for Bioinformatics & Computational Biology, Indian Institute of Technology Delhi, New Delhi, India EKAMPREET SINGH • Department of Biotechnology, School of Engineering and Technology, Sharda University, Greater Noida, UP, India xxvi Contributors

RASHMI PRABHA SINGH • Department of Biotechnology, IILM College of Engineering & Technology, Greater Noida, UP, India RUBAL SINGLA • Department of Pharmacology, Post Graduate Institute of Medical Education and Research, PGIMER, Chandigarh, India SINOSH SKARIYACHAN • Department of Microbiology, St. Pius X College Rajapuram, Kasaragod, Kerala, India QI SONG • National “111” Center for Cellular Regulation and Molecular Pharmaceutics, Key Laboratory of Industrial Fermentation (Ministry of Education), Hubei University of Technology, Wuhan, China; Institute of Biomedical and Pharmaceutical Sciences, Hubei Key Laboratory of Industrial Microbiology, Hubei University of Technology, Wuhan, China OTTAVIA SPIGA • Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy NARAYANASWAMY SRINIVASAN • Molecular Biophysics Unit, Indian Institute of Science, Bengaluru, Karnataka, India SIRIN THEERAWATANASIRIKUL • Department of Anatomy, Faculty of Veterinary Medicine, Kasetsart University, Bangkok, Thailand ALFONSO TREZZA • Department of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy ZHIYING WANG • National “111” Center for Cellular Regulation and Molecular Pharmaceutics, Key Laboratory of Industrial Fermentation (Ministry of Education), Hubei University of Technology, Wuhan, China; Institute of Biomedical and Pharmaceutical Sciences, Hubei Key Laboratory of Industrial Microbiology, Hubei University of Technology, Wuhan, China YANJIE WEI • Center for High Performance Computing, Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, P. R. China HAIPING ZHANG • Center for High Performance Computing, Joint Engineering Research Center for Health Big Data Intelligent Analysis Technology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, P. R. China QIONGQIONG ANGELA ZHOU • CAS, a division of the American Chemical Society, Columbus, OH, USA