Characterization of SARS-CoV-2 Isolate (MZ558159) for in Silico Drug Designing, Reported from India

ABSTRACT

Introduction: Inadequate information available about the genomics and proteomics characterization of SARS-CoV-2 isolates reported from India and other part of the globe. This characterization is important for the in silico drug designing as there are no approved medications available to treat SARS-CoV-2 infection. Aim(s) The aim of the present study is characterization of SARS-CoV-2 (MZ558159) isolate reported from India using homology modelling, validation and in silico drug designing methods. Material(s) and Method(s) Genome sequence of SARS-CoV-2 (MZ558159) was retrieved from NCBI, and four protein sequences selected for the homology modeling, validation and in silico drug designing e.g., QXN18496, QXN18498, QXN18504, and QXN18497. SWISS-MODEL and UCLA-DOE server used for homology modeling. Validation for structure model performed using PROCHECK and molecular docking using MCULE-1-Click server. Result(s) The surface glycoprotein (QXN18496) model corresponding to probability conformation with 93.6%, envelope protein (QXN18498) with 88.9%, nucleocapsid phosphoprotein (QXN18504) with 93.6%, and ORF3a protein (QXN18497) with 91.8% residues in core section of o-o plot that specifies accuracy of prediction model. The corresponding ProSA Z-score score -12.67, -0.01, -4.4, and -2.87 indicates the good quality of the models. Molecular dynamic simulation and docking studies revealed the inhibitor binds effectively at the SARS-CoV-2 (MZ558159) proteins. Predicted inhibitor 2-acetamido-2-deoxy-beta-D-glucopyranose exhibited effective binding affinity against surface glycoprotein (QXN18496). Conclusion(s)The results of study establish inhibitor 2-Acetamido-2-deoxy-beta-D-glucopyranose as valuable lead molecule with great potential for surface glycoprotein (QXN18496).