PMID- 36475332
OWN - NLM
STAT- MEDLINE
DCOM- 20230516
LR  - 20230516
IS  - 1875-6697 (Electronic)
IS  - 1573-4099 (Linking)
VI  - 19
IP  - 3
DP  - 2023
TI  - In silico Prediction and Evaluation of Human Parainfluenza Virus-3 CD4(+) T Cell 
      Epitopes.
PG  - 163-175
LID - 10.2174/1573409919666221205122633 [doi]
AB  - BACKGROUND: Human parainfluenza viruses type 3 (HPIV-3) through bronchiolitis and 
      pneumonia is a common cause of lower respiratory tract infections. It is the main 
      cause of hospitalization of infants and young children and also one of the main 
      causes of morbidity and mortality in immuno-compromised and transplant patients. 
      Despite many efforts, there is currently no specific anti-HPIV-3 drug or approved 
      vaccine to prevent and control the virus. Identification of HPIV-3 epitopes with 
      the capability of binding to human leukocyte antigen (HLA) class II molecules can 
      be helpful in designing new vaccine candidates against HPIV-3 infection, and also 
      can be useful for the in vitro stimulation and proliferation of HPIV-3-specific T 
      cells for transplant and immunocompromised patients. OBJECTIVE: To predict and 
      comprehensively evaluate CD4(+)T cell epitope (HLA-II binders) from four main 
      HPIV-3 antigens. METHODS: In the present work, we predicted and comprehensively 
      evaluated CD4(+)T cell epitope (HLA-II binders) from four main HPIV-3 antigens, 
      including fusion protein (F), hemagglutininneuraminidase (HN), nucleocapsid (N) 
      and matrix (M) proteins using bio- and immunoinformatics software. The toxicity, 
      allergenicity, Blast screening and population coverage of the predicted epitopes 
      were evaluated. The binding ability of the final selected epitopes was evaluated 
      via a docking study. RESULTS: After several filtering steps, including blast 
      screening, toxicity and allergenicity assay, population coverage and docking 
      study, 9 epitopes were selected as candidate epitopes. The selected epitopes 
      showed high population coverage and docking studies revealed a significantly 
      higher binding affinity for the final epitopes in comparison with the negative 
      control peptides. CONCLUSION: The final selected epitopes could be useful in 
      designing vaccine candidates and for the treatment of immune-compromised 
      individuals and patients with transplantation.
CI  - Copyright(c) Bentham Science Publishers; For any queries, please email at 
      epub@benthamscience.net.
FAU - Bemani, Peyman
AU  - Bemani P
AD  - Applied Biotechnology Research Center, Baqiyatallah University of Medical 
      Sciences, Tehran, Iran.
FAU - Mohammadi, Mozafar
AU  - Mohammadi M
AD  - Applied Biotechnology Research Center, Baqiyatallah University of Medical 
      Sciences, Tehran, Iran.
LA  - eng
PT  - Journal Article
PL  - United Arab Emirates
TA  - Curr Comput Aided Drug Des
JT  - Current computer-aided drug design
JID - 101265750
RN  - 0 (Epitopes, T-Lymphocyte)
RN  - 0 (HLA Antigens)
RN  - 0 (Vaccines)
SB  - IM
MH  - Child
MH  - Humans
MH  - Child, Preschool
MH  - Epitopes, T-Lymphocyte
MH  - Parainfluenza Virus 3, Human
MH  - HLA Antigens
MH  - *Vaccines
MH  - CD4-Positive T-Lymphocytes
MH  - *Paramyxoviridae Infections
OTO - NOTNLM
OT  - CD4<sup>+</sup> T cell
OT  - HLA-DRB
OT  - HPIV-3
OT  - Human parainfluenza virus 3
OT  - docking
OT  - epitope prediction
EDAT- 2022/12/08 06:00
MHDA- 2023/05/16 06:42
CRDT- 2022/12/07 02:33
PHST- 2022/04/30 00:00 [received]
PHST- 2022/09/21 00:00 [revised]
PHST- 2022/10/19 00:00 [accepted]
PHST- 2023/05/16 06:42 [medline]
PHST- 2022/12/08 06:00 [pubmed]
PHST- 2022/12/07 02:33 [entrez]
AID - CAD-EPUB-128007 [pii]
AID - 10.2174/1573409919666221205122633 [doi]
PST - ppublish
SO  - Curr Comput Aided Drug Des. 2023;19(3):163-175. doi: 
      10.2174/1573409919666221205122633.