In Silico Identification and Analysis of Potentially Bioactive Antiviral Phytochemicals against SARS-CoV-2: A Molecular Docking and Dynamics Simulation Approach

<table class="table-group" id="tab6"><tr><td><table class="table"><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr class="thead"><td class="align_left">Drug</td><td class="align_center">XP Gscore (kcal Mol−1)</td><td class="align_center">MM-GBSA scores (kcal Mol−1)</td><td class="align_center">Hydrogen bonds</td><td class="align_center">Hydrophobic bonds</td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td class="align_left">Lovastatin</td><td class="align_center">-6.01</td><td class="align_center">-52.85</td><td class="align_center">HIS163, GLU166, GLN189</td><td class="align_center">LEU27, CYS44, MET49, TYR54, PHE140, LEU141, CYS145, GLY154, MET165</td></tr><tr><td class="align_left">Molnupiravir</td><td class="align_center">-5.035</td><td class="align_center">-43.48</td><td class="align_center">GLU166</td><td class="align_center">CYS44, MET49, PRO52, TYR54, CYS145, MET165, LEU167, PRO168</td></tr><tr><td class="align_left">Paxlovid</td><td class="align_center">-5.185</td><td class="align_center">-43.34</td><td class="align_center">GLU166, ASN142</td><td class="align_center">CYS44, MET49, PRO52, TYR54, PHE140, LEU141, GLY143, MET165, LEU167</td></tr><tr class="table-tr"><td colspan="5"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>XP Gscore and MM-GBSA values between the main protease (PDB ID: 7NT3) and the best hit phytochemical and control drugs.</div>

BioMed Research International

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Table 6

Table 6: In Silico Identification and Analysis of Potentially Bioactive Antiviral Phytochemicals against SARS-CoV-2: A Molecular Docking and Dynamics Simulation Approach 

Table 6 | In Silico Identification and Analysis of Potentially Bioactive Antiviral Phytochemicals against SARS-CoV-2: A Molecular Docking and Dynamics Simulation Approach 