scholarly journals In-silico design of a multi-epitope vaccine candidate against onchocerciasis and related filarial diseases

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Robert Adamu Shey ◽  
Stephen Mbigha Ghogomu ◽  
Kevin Kum Esoh ◽  
Neba Derrick Nebangwa ◽  
Cabirou Mounchili Shintouo ◽  
...  
Keyword(s):  
In Silico ◽  
Vaccine Candidate ◽  
Epitope Vaccine ◽  
In Silico Design

scholarly journals In silico design of a T-cell epitope vaccine candidate for parasitic helminth infection

2020 ◽  
Vol 16 (3) ◽  
pp. e1008243 ◽  
Author(s):  
Ayat Zawawi ◽  
Ruth Forman ◽  
Hannah Smith ◽  
Iris Mair ◽  
Murtala Jibril ◽  
...  
Keyword(s):  
T Cell ◽  
In Silico ◽  
Helminth Infection ◽  
Vaccine Candidate ◽  
Cell Epitope ◽  
T Cell Epitope ◽  
Epitope Vaccine ◽  
Parasitic Helminth ◽  
In Silico Design

scholarly journals In-silico design of envelope based multi-epitope vaccine candidate against Kyasanur forest disease virus

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sathishkumar Arumugam ◽  
Prasad Varamballi
Keyword(s):  
Disease Virus ◽  
In Silico ◽  
Hemorrhagic Fever ◽  
Epitope Vaccine ◽  
Epitope Region ◽  
Vaccine Candidates ◽  
Forest Disease ◽  
In Silico Design ◽  
Antigenic Properties ◽  
Kyasanur Forest Disease

AbstractKyasanur forest disease virus (KFDV) causing tick-borne hemorrhagic fever which was earlier endemic to western Ghats, southern India, it is now encroaching into new geographic regions, but there is no approved medicine or effective vaccine against this deadly disease. In this study, we did in-silico design of multi-epitope subunit vaccine for KFDV. B-cell and T-cell epitopes were predicted from conserved regions of KFDV envelope protein and two vaccine candidates (VC1 and VC2) were constructed, those were found to be non-allergic and possess good antigenic properties, also gives cross-protection against Alkhurma hemorrhagic fever virus. The 3D structures of vaccine candidates were built and validated. Docking analysis of vaccine candidates with toll-like receptor-2 (TLR-2) by Cluspro and PatchDock revealed strong affinity between VC1 and TLR2. Ligplot tool was identified the intermolecular hydrogen bonds between vaccine candidates and TLR-2, iMOD server confirmed the stability of the docking complexes. JCAT sever ensured cloning efficiency of both vaccine constructs and in-silico cloning into pET30a (+) vector by SnapGene showed successful translation of epitope region. IMMSIM server was identified increased immunological responses. Finally, multi-epitope vaccine candidates were designed and validated their efficiency, it may pave the way for up-coming vaccine and diagnostic kit development.

scholarly journals Reverse vaccinology approach to design a novel multi-epitope vaccine candidate against COVID-19: an in silico study

2020 ◽  
pp. 1-16 ◽  
Author(s):  
Maryam Enayatkhani ◽  
Mehdi Hasaniazad ◽  
Sobhan Faezi ◽  
Hamed Gouklani ◽  
Parivash Davoodian ◽  
...  
Keyword(s):  
In Silico ◽  
Vaccine Candidate ◽  
Reverse Vaccinology ◽  
Epitope Vaccine ◽  
In Silico Study

scholarly journals In Silico Design of a New Multi-Epitope Peptide-Based Vaccine Candidate Against Q Fever

2021 ◽  
Vol 55 (6) ◽  
pp. 950-960
Author(s):  
S. Jabarzadeh ◽  
A. Samiminemati ◽  
M. Zeinoddini
Keyword(s):  
In Silico ◽  
Vaccine Candidate ◽  
Q Fever ◽  
Epitope Peptide ◽  
In Silico Design

Immunoinformatics approaches to design: A novel multi-epitope vaccine candidate against SARS-CoV-2 and it’s in silico expression (Preprint)

2021 ◽  
Author(s):  
Ravi Deval ◽  
Ayushi Saxena ◽  
Zeba Mueed ◽  
Dibyabhaba Pradhan ◽  
Pankaj Kumar Rai
Keyword(s):  
B Cell ◽  
In Silico ◽  
Vaccine Candidate ◽  
Rna Virus ◽  
Consensus Sequence ◽  
Structure Model ◽  
Epitope Vaccine ◽  
B Cell Epitopes ◽  
Epitope Vaccines ◽  
Further Development

BACKGROUND SARS-CoV-2, belonging to the Coronaviridae family, is a novel RNA virus, known for causing fatal disease in humans called COVID-19. Researchers all around the world are keen on developing a precise treatment or vaccine against this deadly disease. OBJECTIVE The main objective of this paper is to design a novel multi-epitope vaccine candidate against SARS-CoV-2 using immunoinformatics tools. METHODS A consensus sequence was generated from various genomes of SARS-Cov-2 available from various countries of the outbreak at the ViPR database using JalView software. T cell and B cell epitopes were predicted by restricting them to certain HLA alleles using various servers (nHLApred, NetMHCIIpan v.3.1, ABCpred) and were validated using IEDB tools. Using these epitopes and adjuvant, a multi-epitope vaccine was constructed in-silicoand was later subjected to allergenicity, antigenicity and physicochemical properties profiling along with identification of conformational B-cell epitopes. The designed vaccine was evaluated via codon optimization by the Jcat server and finally, it’s in-silicoexpression was done in pET-28a(+) vector using snap-gene software. RESULTS A total of 18 epitopes (both T and B cell) were predicted that constituted vaccine construct along with adjuvant and end tag. Vaccine construct was validated and its best structure model was successfully docked with human Toll-like receptors. In-silico expression of the designed vector was also seen in pET-28a(+) plasmid. CONCLUSIONS The designed novel vaccine candidate has been validated in-silico to elicit robust immune responses hence; it can be used as a potential model for further development of multi-epitope vaccines in the laboratory.

scholarly journals Design of multi-epitope vaccine candidate against SARS-CoV-2: a in-silico study

2020 ◽  
pp. 1-9 ◽  
Author(s):  
K. Abraham Peele ◽  
T. Srihansa ◽  
S. Krupanidhi ◽  
Vijaya Sai Ayyagari ◽  
T. C. Venkateswarulu
Keyword(s):  
In Silico ◽  
Vaccine Candidate ◽  
Epitope Vaccine ◽  
In Silico Study
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