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      Investigation of N Terminal Domain of SARS CoV 2 Nucleocapsid Protein with Antiviral Compounds Based on Molecular Modeling Approach


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      ScienceOpen Preprints


      SARS-CoV-2, COVID-19, molecular docking, MD simulations

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          The recent outbreak of coronavirus disease (COVID-19) in China caused by SARS-CoV-2 virus continually lead to worldwide human infections and deaths. It is currently no specific viral protein targeted therapeutics yet. The nucleocapsid (N) protein of coronaviruses (CoVs) is a multifunctional RNA-binding protein necessary for viral RNA replication and transcription. Therefore, it is a potential antiviral drug target, serving multiple critical functions during the viral life cycle. Herein, we focus here on the potential to repurpose antiviral compounds approved or in development for treating infections caused by human CoVs. For this purpose, we used the docking methodology to better understand the inhibition mechanism of SARS-CoV-2 N protein with this existing 34 antiviral compounds. The results of this analysis were showed that Nafamostat, Rapamycin, Saracatinib, Imatinib and Camostat are the top hit compounds with binding energy (-10.24 kcal/mol, -9.88 kcal/mol, -9.66 kcal/mol, -9.23 kcal/mol, -9.07 kcal/mol) and K i (0.0313 mM, 0.05736 mM, 0.08304 mM, 0.17224 mM, 0.22413 mM). In addition, this analysis also showed that the most common residues that interact with the compounds are Lys65, Phe66, Arg 68, Glu69, Tyr123, Gly124, Lys127, Ile 130, Val133 and Ala134. These results suggest that these residues are potential drug targeting sites for the SARS-CoV-2 N protein. Subsequently, protein-ligand complex stability was examined with Molecular Dynamics (MD) simulations for the Nafamostat compound, which showed the best binding affinity. According to the results of this study, the interaction between the compound and the crucial residues of the target were maintained. Based on this information, we propose guidelines to develop novel N protein-based antiviral agents that target CoVs.

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          ScienceOpen Preprints
          9 April 2020
          [1 ] Karadeniz Technical University

          This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at .


          MD simulations, SARS-CoV-2, COVID-19, molecular docking


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