scholarly journals An in silico Approach for Epitope Based Vaccine Design Against Ebola virus

2021 ◽  
Vol 05 (01) ◽  
Author(s):  
Smrithi Radhakrishnan ◽  
M. Elizabeth Sobhia
Keyword(s):  
In Silico ◽  
Ebola Virus ◽  
Vaccine Design

Novel Algorithms for In Silico Peptide Vaccine Design with Reference to Ebola Virus

2020 ◽  
Author(s):  
Subhamoy Biswas ◽  
Tathagata Dey ◽  
Shreyans Chatterjee ◽  
Smarajit Manna ◽  
Ashesh Nandy ◽  
...  
Keyword(s):  
In Silico ◽  
Ebola Virus ◽  
Peptide Vaccine ◽  
Vaccine Design ◽  
Novel Algorithms

scholarly journals In silico-based vaccine design against Ebola virus glycoprotein

2017 ◽  
Vol Volume 10 ◽  
pp. 11-28 ◽  
Author(s):  
Raju Dash ◽  
Rasel Das ◽  
Md Junaid ◽  
Md Forhad Chowdhury Akash ◽  
Ashekul Islam ◽  
...  
Keyword(s):  
In Silico ◽  
Ebola Virus ◽  
Vaccine Design ◽  
Virus Glycoprotein

An in silico study: Novel targets for potential drug and vaccine design against drug resistant H. pylori

2018 ◽  
Vol 122 ◽  
pp. 156-161 ◽  
Author(s):  
Chiranjeevi Pasala ◽  
Chandra Sekhar Reddy Chilamakuri ◽  
Sudheer Kumar Katari ◽  
Ravina Madhulitha Nalamolu ◽  
Aparna R. Bitla ◽  
...  
Keyword(s):  
In Silico ◽  
Vaccine Design ◽  
Drug Resistant ◽  
Potential Drug ◽  
In Silico Study ◽  
Novel Targets ◽  
H Pylori

scholarly journals In Silico Vaccine Design Based on Molecular Simulations of Rhinovirus Chimeras Presenting HIV-1 gp41 Epitopes

2009 ◽  
Vol 385 (2) ◽  
pp. 675-691 ◽  
Author(s):  
Mauro Lapelosa ◽  
Emilio Gallicchio ◽  
Gail Ferstandig Arnold ◽  
Eddy Arnold ◽  
Ronald M. Levy
Keyword(s):  
In Silico ◽  
Molecular Simulations ◽  
Vaccine Design ◽  
Hiv 1

scholarly journals In silico analysis and modeling of putative T cell epitopes for vaccine design of Toscana virus

3 Biotech ◽  
2014 ◽  
Vol 5 (4) ◽  
pp. 497-503 ◽  
Author(s):  
Amisha Jain ◽  
Pranav Tripathi ◽  
Aniket Shrotriya ◽  
Ritu Chaudhary ◽  
Ajeet Singh
Keyword(s):  
T Cell ◽  
In Silico ◽  
In Silico Analysis ◽  
Vaccine Design ◽  
T Cell Epitopes ◽  
Toscana Virus ◽  
Silico Analysis

scholarly journals In silico prediction of B cell epitopes of the hemolysis-associated protein 1 for vaccine design against leptospirosis

2020 ◽  
Vol 1 (1) ◽  
pp. 32-37
Author(s):  
Sakineh Poorhosein Fookolaee ◽  
Somayyeh Talebishelimaki ◽  
Mohammad Taha Saadati Rad ◽  
Mostafa Akbarian Rokni
Keyword(s):  
B Cell ◽  
In Silico ◽  
Vaccine Design ◽  
In Silico Prediction ◽  
B Cell Epitopes

scholarly journals Epitope order Matters in multi-epitope-based peptide (MEBP) vaccine design: An in silico study

2021 ◽  
Author(s):  
Muthu Raj Salaikumaran ◽  
Prasanna Sudharson Kasamuthu ◽  
V L S Prasad Burra
Keyword(s):  
In Silico ◽  
Experimental Validation ◽  
Vaccine Development ◽  
Experimental Testing ◽  
Peptide Vaccine ◽  
Vaccine Design ◽  
Vaccine Candidates ◽  
Vaccine Potency ◽  
Experimental Protocols ◽  
The Many

With different countries facing multiple waves, with some SARS-CoV-2 variants more deadly and virulent, the COVID-19 pandemic is becoming more dangerous by the day and the world is facing an even more dreadful extended pandemic with exponential positive cases and increasing death rates. There is an urgent need for more efficient and faster methods of vaccine development against SARS-CoV-2. Compared to experimental protocols, the opportunities to innovate are very high in immunoinformatics/in silico approaches especially with the recent adoption of structural bioinformatics in peptide vaccine design. In recent times, multi-epitope-based peptide vaccine candidates (MEBPVCs) have shown extraordinarily high humoral and cellular responses to immunization. Most of the publications claim that respective reported MEBPVC(s) assembled using a set of in silico predicted epitopes, to be the computationally validated potent vaccine candidate(s) ready for experimental validation. However, in this article, for a given set of predicted epitopes, it is shown that the published MEBPVC is one among the many possible variants and there is high likelihood of finding more potent MEBPVCs than the published candidate. To test the same, a methodology is developed where novel MEBP variants are derived by changing the epitope order of the published MEBPVC. Further, to overcome the limitations of current qualitative methods of assessment of MEBPVC, to enable quantitative comparison, ranking, and the discovery of more potent MEBPVCs, novel predictors, Percent Epitope Accessibility (PEA), Receptor specific MEBP vaccine potency(RMVP), MEBP vaccine potency(MVP) are introduced. The MEBP variants indeed showed varied MVP scores indicating varied immunogenicity. When the MEBP variants were ranked in descending order of their MVP scores, the published MEBPVC had the least MVP score. Further, the MEBP variants with IDs, SPVC_387 and SPVC_206, had the highest MVP scores indicating these variants to be more potent MEBPVCs than the published MEBPVC and hence should be prioritized for experimental testing and validation. Through this method, more vaccine candidates will be available for experimental validation and testing. This study also opens the opportunity to develop new software tools for designing more potent MEBPVCs in less time. The computationally validated top-ranked MEBPVCs must be experimentally tested, validated, and verified. The differences and deviations between experimental results and computational predictions provide an opportunity for improving and developing more efficient algorithms and reliable scoring schemes and software.

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