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      Target-Based In Silico Screening for Phytoactive Compounds Targeting SARS-CoV-2

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          Abstract

          Abstract

          Coronavirus disease 2019 (COVID-19), resulting from infection by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), can cause severe and fatal pneumonia along with other life-threatening complications. The COVID-19 pandemic has taken a heavy toll on the healthcare system globally and has hit the economy hard in all affected countries. As a result, there is an unmet medical need for both the prevention and treatment of COVID-19 infection. Several herbal remedies have claimed to show promising clinical results, but the mechanisms of action are not clear. We set out to identify the anti-viral natural products of these herbal remedies that presumably inhibit the life cycle of SARS-CoV-2. Particularly we chose four key SARS-CoV-2 viral enzymes as targets: Papain-like protease, Main protease, RNA dependent RNA polymerase, and 2’-O-ribose methyltransferase, which were subjected to an unbiased in silico screening against a small molecule library of 33,765 compounds originating from herbs and medicinal plants. The small molecules were then ranked based on their free energy of fitting into the “druggable” pockets on the surface of each target protein. We have analyzed the best “fit” molecules and annotated them according to their plant sources and pharmacokinetic properties. Here we present a list of potential anti-viral ingredients of herbal remedies targeting SARS-CoV-2 and explore the potential mechanisms of action of these compounds as a framework for further development of chemoprophylaxis agents against COVID-19.

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          Supplementary Information

          The online version contains supplementary material available at 10.1007/s12539-021-00461-4.

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          Most cited references56

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          A Novel Coronavirus from Patients with Pneumonia in China, 2019

          Summary In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.)
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            Is Open Access

            A new coronavirus associated with human respiratory disease in China

            Emerging infectious diseases, such as severe acute respiratory syndrome (SARS) and Zika virus disease, present a major threat to public health 1–3 . Despite intense research efforts, how, when and where new diseases appear are still a source of considerable uncertainty. A severe respiratory disease was recently reported in Wuhan, Hubei province, China. As of 25 January 2020, at least 1,975 cases had been reported since the first patient was hospitalized on 12 December 2019. Epidemiological investigations have suggested that the outbreak was associated with a seafood market in Wuhan. Here we study a single patient who was a worker at the market and who was admitted to the Central Hospital of Wuhan on 26 December 2019 while experiencing a severe respiratory syndrome that included fever, dizziness and a cough. Metagenomic RNA sequencing 4 of a sample of bronchoalveolar lavage fluid from the patient identified a new RNA virus strain from the family Coronaviridae, which is designated here ‘WH-Human 1’ coronavirus (and has also been referred to as ‘2019-nCoV’). Phylogenetic analysis of the complete viral genome (29,903 nucleotides) revealed that the virus was most closely related (89.1% nucleotide similarity) to a group of SARS-like coronaviruses (genus Betacoronavirus, subgenus Sarbecovirus) that had previously been found in bats in China 5 . This outbreak highlights the ongoing ability of viral spill-over from animals to cause severe disease in humans.
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              AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading.

              AutoDock Vina, a new program for molecular docking and virtual screening, is presented. AutoDock Vina achieves an approximately two orders of magnitude speed-up compared with the molecular docking software previously developed in our lab (AutoDock 4), while also significantly improving the accuracy of the binding mode predictions, judging by our tests on the training set used in AutoDock 4 development. Further speed-up is achieved from parallelism, by using multithreading on multicore machines. AutoDock Vina automatically calculates the grid maps and clusters the results in a way transparent to the user. Copyright 2009 Wiley Periodicals, Inc.
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                Author and article information

                Contributors
                yongzhao168@gmail.com
                tianyu@bjmu.edu.cn
                yisheng@yorku.ca
                Journal
                Interdiscip Sci
                Interdiscip Sci
                Interdisciplinary Sciences, Computational Life Sciences
                Springer Singapore (Singapore )
                1913-2751
                1867-1462
                25 July 2021
                : 1-16
                Affiliations
                [1 ]GRID grid.418265.c, Beijing Computing Center, , Beijing Academy of Science and Technology, ; 7 Fengxian Road, Beijing, 100094 China
                [2 ]GRID grid.411642.4, ISNI 0000 0004 0605 3760, Department of Urology, , Peking University Third Hospital, ; Beijing, 100191 China
                [3 ]GRID grid.410318.f, ISNI 0000 0004 0632 3409, Institute of Chinese Materia Medica, , China Academy of Chinese Medical Sciences, ; Beijing, 100700 China
                [4 ]GRID grid.34429.38, ISNI 0000 0004 1936 8198, The Department of Molecular and Cellular Biology, , University of Guelph, ; Guelph, ON Canada
                [5 ]GRID grid.440050.5, ISNI 0000 0004 0408 2525, CIFAR Azrieli Global Scholars Program, , Canadian Institute for Advanced Research, ; Toronto, ON Canada
                [6 ]GRID grid.21100.32, ISNI 0000 0004 1936 9430, The Department of Biology, , York University, ; Life Sciences Building 327B, 4700 Keele Street, Toronto, ON M3J 1P3 Canada
                Author information
                http://orcid.org/0000-0003-4083-7983
                Article
                461
                10.1007/s12539-021-00461-4
                8310681
                34308530
                77c5b2f8-dddb-46b6-bf82-b0fa7c763658
                © International Association of Scientists in the Interdisciplinary Areas 2021

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                : 7 January 2021
                : 1 July 2021
                : 4 July 2021
                Categories
                Original Research Article

                in silico screening,covid-19,natural compounds,papain-like protease,main protease,rna-dependent rna polymerase,2’-o-methyltransferase

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