Immunoinformatics and structural vaccinology driven prediction of multi-epitope vaccine against Mayaro virus and validation through in-silico expression

Khan, Sidra; Khan, Abbas; Rehman, Ashfaq Ur; Ahmad, Irfan; Ullah, Saif; Khan, Abdul Aziz; Ali, Syed Shujait; Afridi, Sahib Gul; Wei, Dong‐Qing

doi:10.1016/j.meegid.2019.06.006

Cited by 89 publications

(66 citation statements)

References 40 publications

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“…Kaur et al developed a multi-epitope peptide-based chimeric vaccine against the Taenia solium by in-silico approaches [ 26 ]. The structural vaccinological analysis and computational validation of the vaccine candidate were also performed against the Mayaro virus [ 27 ]. In considerate to the human pathogenic viruses (West Nile virus and Ebola virus) specific peptide-based vaccine has been developed by employing immuno-pharmacoinformatic techniques [ 28 , 29 ].…”

Section: Discussionmentioning

confidence: 99%

A SARS-CoV-2 vaccine candidate: In-silico cloning and validation

Bhattacharya

Sharma

Patra

et al. 2020

Informatics in Medicine Unlocked

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SARS-CoV-2 is spreading globally at a rapid pace. To contain its spread and prevent further fatalities, the development of a vaccine against SARS-CoV-2 is an urgent prerequisite. Thus, in this article, by utilizing the in-silico approach, a vaccine candidate for SARS-CoV-2 has been proposed. Moreover, the effectiveness and safety measures of our proposed epitopic vaccine candidate have been evaluated by in-silico tools and servers (AllerTOP and AllergenFP servers). We observed that the vaccine candidate has no allergenicity and successfully combined with Toll-like receptor (TLR) protein to elicit an inflammatory immune response. Stable, functional mobility of the vaccine-TLR protein binding interface was confirmed by the Normal Mode Analysis. The in-silico cloning model demonstrated the efficacy of the construct vaccine along with the identified epitopes against SARS-CoV-2. Taken together, our proposed in-silico vaccine candidate has potent efficacy against COVID-19 infection, and successive research work might validate its effectiveness in in vitro and in vivo models.

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Section: Discussionmentioning

confidence: 99%

A SARS-CoV-2 vaccine candidate: In-silico cloning and validation

Bhattacharya

Sharma

Patra

et al. 2020

Informatics in Medicine Unlocked

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“…The occurrence of this response can be determined through the presence of HLA alleles in the host organism. One way to predict the behavior of these antigenic determinants is to evaluate their binding capacity to MHCI and to evaluate their immunogenic capacity by molecular docking [ 47 , 56 ]. In pigs, the major histocompatibility complex (MHC in pigs) and the swine leukocyte antigen (SLA) have an important role mediating cellular immunity, which can eliminate viruses and recognize other antigens in pigs.…”

Section: Discussionmentioning

confidence: 99%

Immunoinformatics approach for predicting epitopes in HN and F proteins of Porcine rubulavirus

et al. 2020

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Porcine rubulavirus (PRV), which belongs to the family Paramyxoviridae, causes blue eye disease in pigs, characterized by encephalitis and reproductive failure in newborn and adult pigs, respectively. There is no effective treatment against PRV and no information on the effectiveness of the available vaccines. Continuous outbreaks have occurred in Mexico since the early 1980s, which have caused serious economic losses to pig producers. Vaccination can be used to control this disease. Searching for effective antigen candidates against PRV, we first sequenced the PAC1 F protein, then we used various immunoinformatics tools to predict antigenic determinants of B-cells and T-cells against the two glycoproteins of the virus (HN and F proteins). Finally, we used AutoDock Vina to determine the binding energies. We obtained the F gene sequence of a PRV strain collected in the early 1990s in Mexico and compared its amino acid profile with previous and more recent strains, obtaining an identity similarity of 97.78 to 99.26%. For the F proteins, seven linear B-cell epitopes, six conformational B-cell epitopes and twenty-nine T-cell MHC class I epitopes were predicted. For the HN proteins, sixteen linear B-cell epitopes, seven conformational B-cell epitopes and thirty-four T-cell MHC class I epitopes were predicted. The ATRSETDYY and AAYTTTTCF epitopes of the HN protein might be important for neutralizing the viral infection. We determined the in silico binding energy between the predicted epitopes on the F and HN proteins and swine MHC-I molecules. The binding energy of these epitopes ranged from-5.8 to-7.8 kcal/mol. The present study aimed to assess the use of HN and F proteins as antigens, either as recombinant proteins or as a series of peptides that could activate different responses of the immune system. This may help identify relevant immunogens, saving time and costs in the development of new vaccines or diagnostic tools.

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“…The procedure used in this study is entirely based on two previous studies [3] [4]. It will not be repeated here but is summarised below in gure 1 after obtaining necessary permission from its authors.…”

Section: Methodsmentioning

confidence: 99%

Multi-epitope peptide sequence in-silico construction from HGV genome

Sharp¹

2020

Preprint

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In this study I have approached through in-silico method or reverse vaccinology taking advantage of the genome sequence of hepatitis G virus. It serves its benefit of identifying antigens seen by both conventional as well as discovering any novel antigen. This peptide candidate can serve a triple purpose of hepatitis C vaccine, hepatitis G vaccine and HIV management addition. 89.2% of the residues were in the favoured region of Ramachandran plot. These points make it favourable for in-vitro trials and further refinement. Because of the high similarity of hepatitis C genome to hepatitis G genome, it is highly probable that this peptide sequence might act as both hepatitis C and hepatitis G vaccine. Patients with past or current HGV infection have higher CD4+ lymphocyte counts and better AIDS-free survival rates. This peptide sequence might cause a breakthrough in the treatment of HIV without exposing them to develop hepatitis.

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Immunoinformatics and structural vaccinology driven prediction of multi-epitope vaccine against Mayaro virus and validation through in-silico expression

Cited by 89 publications

References 40 publications

A SARS-CoV-2 vaccine candidate: In-silico cloning and validation

A SARS-CoV-2 vaccine candidate: In-silico cloning and validation

Immunoinformatics approach for predicting epitopes in HN and F proteins of Porcine rubulavirus

Multi-epitope peptide sequence in-silico construction from HGV genome

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