:: Main :: About :: Current Issue :: Archive :: Submit :: Contact ::
:: Volume 7, Issue 1 (6-2020) ::
vacres 2020, 7(1): 10-16 Back to browse issues page
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:   (457 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 ,
Full-Text [PDF 927 kb]   (110 Downloads)    
Type of Study: Short communication | Subject: Protein modeling
Received: 2020/03/17 | Accepted: 2020/06/11 | Published: 2020/09/24
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA



XML     Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

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


Volume 7, Issue 1 (6-2020) Back to browse issues page
Vaccine Research Vaccine Research
Persian site map - English site map - Created in 0.11 seconds with 30 queries by YEKTAWEB 4223
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.