In silico study to predict and characterize of SARS CoV 2 Surface glycoprotein

Kumar, Avnish; Sharma, Bhuvnesh Prasad

doi:10.29252/vacres.7.1.10

Volume 7, Issue 1 (6-2020) vacres 2020, 7(1): 10-16 | Back to browse issues page

‎ 10.29252/vacres.7.1.10

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Kumar A, Sharma B P. In silico study to predict and characterize of SARS CoV 2 Surface glycoprotein. vacres 2020; 7 (1) :10-16
URL: http://vacres.pasteur.ac.ir/article-1-179-en.html

In silico study to predict and characterize of SARS CoV 2 Surface glycoprotein

Avnish Kumar ^*

, Bhuvnesh Prasad Sharma

Department of Biotechnology, School of Life Sciences, Dr. Bhimrao Ambedkar University Agra-282004, UP India

Abstract: (3263 Views)

Introduction: Coronavirus family member SARS- CoV-2 is a current worldwide threat. It enters into the epithelium membrane of respiratory tract with the help of its antigenic spike proteins and cause Coronavirus disease 2019 (COVID -19). Methods: Considering SARS- CoV-2 a potent vaccine or diagnostic candidate, a bioinformatical study was done to determine its structure homology modeling, physiological properties and structure validation with presence of antigenic sites. Results: The surface glycoprotein of SARS-CoV-2 was found to be a stable protein with stereochemically good structure. It also contains 65 antigenic sites. Conclusion: The present study suggests further wet-lab research to develop a vaccine or diagnostic kit using this promising surface glycoprotein.

Keywords: COVID-19, 6VSB, corona vaccine, Spike protein, Glycoprotein

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Type of Study: Short communication | Subject: Protein modeling
Received: 2020/03/17

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