PMID- 35506029
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20220507
IS  - 2563-3570 (Electronic)
IS  - 2563-3570 (Linking)
VI  - 3
IP  - 1
DP  - 2022 Jan-Dec
TI  - Identification of Potential Vaccine Candidates Against SARS-CoV-2 to Fight 
      COVID-19: Reverse Vaccinology Approach.
PG  - e32401
LID - 10.2196/32401 [doi]
LID - e32401
AB  - BACKGROUND: The recent emergence of COVID-19 has caused an immense global public 
      health crisis. The etiological agent of COVID-19 is the novel coronavirus 
      SARS-CoV-2. More research in the field of developing effective vaccines against 
      this emergent viral disease is indeed a need of the hour. OBJECTIVE: The aim of 
      this study was to identify effective vaccine candidates that can offer a new 
      milestone in the battle against COVID-19. METHODS: We used a reverse vaccinology 
      approach to explore the SARS-CoV-2 genome among strains prominent in India. 
      Epitopes were predicted and then molecular docking and simulation were used to 
      verify the molecular interaction of the candidate antigenic peptide with 
      corresponding amino acid residues of the host protein. RESULTS: A promising 
      antigenic peptide, GVYFASTEK, from the surface glycoprotein of SARS-CoV-2 
      (protein accession number QIA98583.1) was predicted to interact with the human 
      major histocompatibility complex (MHC) class I human leukocyte antigen 
      (HLA)-A*11-01 allele, showing up to 90% conservancy and a high antigenicity 
      value. After vigorous analysis, this peptide was predicted to be a suitable 
      epitope capable of inducing a strong cell-mediated immune response against 
      SARS-CoV-2. CONCLUSIONS: These results could facilitate selecting SARS-CoV-2 
      epitopes for vaccine production pipelines in the immediate future. This novel 
      research will certainly pave the way for a fast, reliable, and effective platform 
      to provide a timely countermeasure against this dangerous virus responsible for 
      the COVID-19 pandemic.
CI  - (c)Ekta Gupta, Rupesh Kumar Mishra, Ravi Ranjan Kumar Niraj. Originally published 
      in JMIR Bioinformatics and Biotechnology (https://bioinform.jmir.org), 
      26.04.2022.
FAU - Gupta, Ekta
AU  - Gupta E
AUID- ORCID: 0000-0002-4960-8071
AD  - Dr. B. Lal Institute of Biotechnology Jaipur India.
FAU - Mishra, Rupesh Kumar
AU  - Mishra RK
AUID- ORCID: 0000-0002-4655-2762
AD  - Amity University Rajasthan Jaipur India.
FAU - Kumar Niraj, Ravi Ranjan
AU  - Kumar Niraj RR
AUID- ORCID: 0000-0002-8547-6037
AD  - Amity University Rajasthan Jaipur India.
LA  - eng
PT  - Journal Article
DEP - 20220426
PL  - Canada
TA  - JMIR Bioinform Biotech
JT  - JMIR bioinformatics and biotechnology
JID - 101769661
PMC - PMC9048139
OTO - NOTNLM
OT  - COVID-19
OT  - SARS-CoV-2
OT  - antigen
OT  - biochemistry
OT  - genetics
OT  - immunology
OT  - molecular docking
OT  - molecular dynamics simulation
OT  - peptide
OT  - reverse vaccinology
OT  - simulation
OT  - vaccine
OT  - vaccine candidates
OT  - virus
COIS- Conflicts of Interest: None declared.
EDAT- 2022/05/05 06:00
MHDA- 2022/05/05 06:01
PMCR- 2022/04/26
CRDT- 2022/05/04 02:20
PHST- 2021/07/26 00:00 [received]
PHST- 2021/11/02 00:00 [revised]
PHST- 2021/12/27 00:00 [accepted]
PHST- 2022/05/04 02:20 [entrez]
PHST- 2022/05/05 06:00 [pubmed]
PHST- 2022/05/05 06:01 [medline]
PHST- 2022/04/26 00:00 [pmc-release]
AID - v3i1e32401 [pii]
AID - 10.2196/32401 [doi]
PST - epublish
SO  - JMIR Bioinform Biotech. 2022 Apr 26;3(1):e32401. doi: 10.2196/32401. eCollection 
      2022 Jan-Dec.