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Title

Predicted peptide patterns from the SARS-CoV-2 proteome for MS-MS based diagnosis

 

Authors

Saketh Kapoor1,* & Pratigya Subba2,*

 

Affiliation

1Stem Cells and Regenerative Medicine Centre, Yenepoya Research Centre, Yenepoya (Deemed to be University), Deralakatte, Mangalore, Karnataka, Pincode-575018, India; 2Centre for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Deralakatte, Mangalore, Karnataka, Pincode-575018, India.

 

Email

Pratigya Subba E-mails: pratigyas@yenepoya.edu.in, psubba09@gmail.com; Phone: +91-9972238973; Saketh Kapoor E-mails: sakethk@yenepoya.edu.in, kapoor.saketh@gmail.com; Phone: +91-8105097846; *Corresponding author

 

Article Type

Research Article

 

Date

Received May 6, 2020; Revised May 23, 2020; Accepted May 25, 2020; Published June 30, 2020

 

Abstract

COVID-19 caused by 2019 novel coronavirus (2019-nCoV2) also known as SARS-CoV-2 has manifested globally since January 2020. COVID-19 was declared as a pandemic by the WHO and has become a serious global health concern. Real-time PCR based and antibodybased assays are being used for the clinical detection of the virus in body fluids and nasopharyngeal swabs. Antibody variability linked to viral mutations is a big concern. Hence, it is of interest to use data patterns from mass spectrometry-based platforms for the identification of SARS-CoV-2. This dataset can be used to perform targeted mass-spectrometric analysis of SARS-CoV-2 peptides. This work can be extrapolated for the detection of SARS-CoV-2 viral peptides in complex biological fluids for early diagnosis of COVID-19.

 

Keywords

SARS-CoV-2, COVID-19, targeted proteomics, Skyline, tryptic peptides.

 

Citation

Kapoor & Subba, Bioinformation 16(6): 477-482 (2020)

 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.