Volume 8, Issue 4 (11-2022)
Journal of Research in Applied and Basic Medical Sciences 2022, 8(4): 175-188 |
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Ph.D Pacific Institute of Medical Sciences, Sai Tirupati University, Udaipur, Rajasthan, India , rajneesh030041@gmail.com
Abstract: (1045 Views)
Background & Aims: There is 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. The present study based on the characterization of SARS-CoV-2 (MZ558159) isolate reported from India using homology modeling, validation, and in silico drug designing methods.
Materials & Methods: Genome sequence of SARS-CoV-2 (MZ558159) was retrieved from NCBI, and four protein sequences e.g., QXN18496, QXN18498, QXN18504, and QXN18497 were selected for the homology modeling, validation, and in silico drug designing. SWISS-MODEL and UCLA-DOE server were used for homology modeling. Validation for structure model performed using PROCHECK and molecular docking using MCULE-1-Click server.
Results: 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 φ-ψ plot that specifies accuracy of prediction models. 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 that 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: The results of this study established inhibitor 2-Acetamido-2-deoxy-beta-D-glucopyranose as valuable lead molecule with great potential for surface glycoprotein (QXN18496).
Materials & Methods: Genome sequence of SARS-CoV-2 (MZ558159) was retrieved from NCBI, and four protein sequences e.g., QXN18496, QXN18498, QXN18504, and QXN18497 were selected for the homology modeling, validation, and in silico drug designing. SWISS-MODEL and UCLA-DOE server were used for homology modeling. Validation for structure model performed using PROCHECK and molecular docking using MCULE-1-Click server.
Results: 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 φ-ψ plot that specifies accuracy of prediction models. 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 that 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: The results of this study established inhibitor 2-Acetamido-2-deoxy-beta-D-glucopyranose as valuable lead molecule with great potential for surface glycoprotein (QXN18496).
Type of Study: orginal article |
Subject:
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