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            <name>Title</name>
            <description>A name given to the resource</description>
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                <text>Coronavirus</text>
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                <text>Dominio científico: Coronavirus</text>
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          <name>Title</name>
          <description>A name given to the resource</description>
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              <text>In silico Molecular Docking Analysis Targeting SARSCoV-2 Spike Protein and Selected Herbal Constituents</text>
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          <name>Creator</name>
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              <text>Pallab Chaudhuri, Raj Kumar Singh, Kuldeep Dhama, Yashpal S. Malik, Prasad Thomas, Muthu Sankar, Shiv Varan Singh, Karthikeyan Ravichandran, Anbazhagan Subbaiyan</text>
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              <text>In modern drug discovery, molecular docking analysis is routinely used to understand and predictthe interaction between a drug molecule and a target protein from a microbe. Drugs identified inthis way may inhibit the entry and replication of pathogens in host cells. The SARS-CoV-2 associatedcoronavirus disease, COVID-19, has become the most contagious and deadly pandemic disease in theworld today. In abeyance of any specific vaccine or therapeutic against SARS-CoV-2, the burgeoningsituation urges a need for effective drugs to treat the virus-infected patients. Herbal medicines havebeen used as natural remedies for treating various infectious diseases since ancient times. The spike(S) protein of SARS-CoV-2 is important for the attachment and pathogenesis of the virus. Therefore,this study focused on the search of useful ligands for S protein among active constituents present incommon herbs that could serve as efficient remedies for COVID-19. We analysed the binding efficiencyof twelve compounds present in common herbs with the S protein of SARS-CoV-2 through moleculardocking analysis and also results are validated with two different docking tools. The binding efficiencyof ligands was scored based on their predicted pharmacological interactions coupled with bindingenergy estimates. In docking analysis, compound “I” (Epigallocatechin gallate (EGCG)) was found tohave the highest binding affinity with the viral S protein, followed by compounds, “F” (Curcumin),“D”(Apigenin) and “E” (Chrysophanol). The present study corroborates that compound “I” (EGCG) mostlypresent in the integrants of green tea, shows the highest potentiality for acting as an inhibitor of SARSCoV-2. Further, characterization of the amino acid residues comprising the viral binding site and thenature of the hydrogen bonding involved in the ligand-receptor interaction revealed significant findingswith herbal compound “I” (EGCG) binding to the S protein at eight amino acid residues. The bindingsites are situated near to the amino acids which are required for virus pathogenicity. The findings ofthe present study need in vivo experiments to prove the utility of “I”, “F”,“D” and “E” compounds andtheir further use in making herb-based anti-SARS-CoV-2 product in near future. This analysis may helpto create a new ethno-drug formulation for preventing or curing the COVID-19.</text>
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          <name>Date</name>
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              <text>2020</text>
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          <name>Subject</name>
          <description>The topic of the resource</description>
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              <text>molecular docking, spike protein, Herbal medicine, Ligands, in silico, SARS-CoV-2, COVID-19</text>
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          <name>Identifier</name>
          <description>An unambiguous reference to the resource within a given context</description>
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              <text>DOI: 10.22207/JPAM.14.SPL1.37</text>
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        <element elementId="48">
          <name>Source</name>
          <description>A related resource from which the described resource is derived</description>
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              <text>Journal of Pure and Applied Microbiology</text>
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          <name>Publisher</name>
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              <text>Journal of Pure and Applied Microbiology</text>
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          <name>Coverage</name>
          <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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              <text>Microbiology</text>
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