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A systematic and reverse vaccinology approach to design novel subunit vaccines against Dengue virus type-1 (DENV-1) and human Papillomavirus-16 (HPV-16)
- Source :
- Informatics in Medicine Unlocked, Vol 19, Iss , Pp 100343- (2020)
- Publication Year :
- 2020
- Publisher :
- Elsevier, 2020.
-
Abstract
- Currently, dengue fever and human cervical cancer are two of the most dangerous diseases around the world. Dengue fever is caused by four serotypes of dengue virus (DENV)- 1, 2, 3 and 4 and most of the human cervical cancer cases are found to be caused by human papillomavirus type-16 (HPV-16). In this study, potential epitope-based subunit vaccines were designed using numerous tools of reverse vaccinology, targeting the DENV-1 envelope protein E and HPV-16 major capsid protein L1. Reverse vaccinology is a genome-based approach of vaccine designing, identifying potential antigenic epitopes of a pathogen. After obtaining the target protein sequences, their antigenicity and physicochemical properties were determined. Thereafter, the possible T cell and B cell epitopes were predicted and after analyzing their antigenicity, allergenicity, toxicity, and conservancy, as well as docking results (docked with MHC class-I and class-II alleles), the best epitopes were selected for vaccine construction. Thereafter, two best vaccine constructs (one for each of the virus) were selected for further analysis based on analyzing the docking results (docked with various MHC alleles and TLR molecules) of the initially constructed six vaccines. The molecular dynamics simulation of the two selected docked complexes with the two best vaccines showed quite satisfactory results. Finally, after codon adaptation, the vaccine constructs were inserted into the pET-19b plasmid vector for E. coli strain K12 using an in silico cloning approach. However, more in vitro and in vivo studies might be required on the suggested vaccines for their proper validation.
Details
- Language :
- English
- ISSN :
- 23529148
- Volume :
- 19
- Issue :
- 100343-
- Database :
- Directory of Open Access Journals
- Journal :
- Informatics in Medicine Unlocked
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.3d8fc3646a2143538a4fa54854b7b95a
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.imu.2020.100343