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جلد 7 شماره 1 صفحات 10-16 برگشت به فهرست نسخه ها
In silico study to predict and characterize of SARS CoV 2 Surface glycoprotein
چکیده:   (348 مشاهده)
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.
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نوع مطالعه: Short communication | موضوع مقاله: Protein modeling
دریافت: 1398/12/27 | پذیرش: 1399/3/22 | انتشار: 1399/7/3
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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-fa.html

In silico study to predict and characterize of SARS CoV 2 Surface glycoprotein. Vaccine Research. 1399; 7 (1) :10-16

URL: http://vacres.pasteur.ac.ir/article-1-179-fa.html



دوره 7، شماره 1 - ( 4-1399 ) برگشت به فهرست نسخه ها
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