scholarly journals Using in-silica Analysis and Reverse Vaccinology Approach for COVID-19 Vaccine Development

2020 ◽  
Vol 2 ◽  
pp. 96-105
Author(s):  
Ajay Agarwal
Keyword(s):  
Vaccine Development ◽  
Virulent Strain ◽  
Reverse Vaccinology ◽  
Global Energy ◽  
Vaccine Candidates ◽  
Energy Score ◽  
Academic Researchers ◽  
Bioinformatics Databases ◽  
Potential Vaccine ◽  
The Given

Background: The recent pandemic of COVID19 that has struck the world is yet to be battled by a potential cure. Countless lives have been claimed due to the existing pandemic and the societal normalcy has been damaged permanently. As a result, it becomes crucial for academic researchers in the field of bioinformatics to combat the existing pandemic. Materials and Methods: The study involved collecting the virulent strain sequence of SARS-nCoV19 for the country USA against human host through publically available bioinformatics databases. Using in-silica analysis, reverse vaccinology, and 3-D modelling, two leader proteins were identified to be potential vaccine candidates for development of a multi-epitope drug. Results: It was revealed that the two leader proteins ORF1ab MT326102 and MT326715 had the highest extinction coefficient and the lowest score on the GRAVY. Along with the given parameters, these leader proteins were highly stable and were also antigenic in nature. The two selected epitopes were then docked against their respective alleles to obtain the global energy scores, which was the lowest of all possible pairs. Conclusion: The epitopes which displayed the lowest global energy score on docking with the alleles were selected and proposed as successful and potential vaccine candidates for multi-epitope vaccine development. Doi: 10.28991/SciMedJ-2020-02-SI-9 Full Text: PDF

scholarly journals Preliminary Work Towards Finding Proteins as Potential Vaccine Candidates for Vibrio cholerae Pakistani Isolates through Reverse Vaccinology

Medicina ◽  
2019 ◽  
Vol 55 (5) ◽  
pp. 195 ◽  
Author(s):  
Samia Zeb ◽  
Amjad Ali ◽  
Sardar Muhammad Gulfam ◽  
Habib Bokhari
Keyword(s):  
Vibrio Cholerae ◽  
Tertiary Structure ◽  
Diarrheal Disease ◽  
Vaccine Development ◽  
Protein A ◽  
Reverse Vaccinology ◽  
Whole Genome Sequence ◽  
Effective Vaccine ◽  
Vaccine Candidates ◽  
Potential Vaccine

Background and Objective: Vibrio cholerae continues to emerge as a dangerous pathogen because of increasing resistance to a number of antibiotics. This paper provides a solution to emerging antibiotic resistance by introducing novel proteins as vaccine candidates against cholera. Materials and Methods: Vibrio cholerae genome versatility is a hurdle for developing a vaccine to combat diarrhoeal infection, so its core gene information was used to determine a potential vaccine candidate. Whole genome sequence data of more than 100 Vibrio cholerae strains were used simultaneously to get core genome information. The VacSol pipeline based on reverse vaccinology was selected to address the problem of safe, cheap, temperature-stable, and effective vaccine candidates which can be used for vaccine development against Vibrio cholerae. VacSol screens vaccine candidates using integrated, well-known, and robust algorithms/tools for proteome analysis. The proteomes of the pathogens were initially screened to predict homology using BLASTp. Proteomes that are non-homologous to humans are then subjected to a predictor for localization. Helicer predicts transmembrane helices for the protein. Proteins failing to comply with the set parameters were filtered at each step, and finally, 11 proteins were filtered as vaccine candidates. Results: This selected group of vaccine candidates consists of proteins from almost all structural parts of Vibrio cholerae. Their blast results show that this filtered group includes flagellin A protein, a protein from the Zn transporter system, a lipocarrier outer membrane protein, a peptidoglycan-associated protein, a DNA-binding protein, a chemotaxis protein, a tRNA Pseuriudine synthase A, and two selected proteins, which were beta lactamases. The last two uncharacterized proteins possess 100% similarity to V. albensis and Enterobacter, respectively. Tertiary structure and active site determination show a large number of pockets on each protein. Conclusions: The most interesting finding of this study is that 10 proteins out of 11 filtered proteins are introduced as novel potential vaccine candidates. These novel vaccine candidates can result in the development of cost-effective and broad-spectrum vaccines which can be used in countries where cholera is a major contributor to diarrheal disease.

scholarly journals in-silica Analysis of SARS-CoV-2 viral strain using Reverse Vaccinology Approach: A Case Study for USA

2020 ◽  
Author(s):  
Ajay Agarwal
Keyword(s):  
Respiratory Disease ◽  
Vaccine Development ◽  
Virulent Strain ◽  
Human Interaction ◽  
Reverse Vaccinology ◽  
World Health ◽  
Genetic Characteristics ◽  
Bioinformatics Databases ◽  
Novel Coronavirus ◽  
Health Organization

AbstractThe recent pandemic of COVID19 that has struck the world is yet to be battled by a potential cure. Countless lives have been claimed due to the existing pandemic and the societal normalcy has been damaged permanently. As a result, it becomes crucial for academic researchers in the field of bioinformatics to combat the existing pandemic. The study involved collecting the virulent strain sequence of SARS-nCoV19 for the country USA against human host through publically available bioinformatics databases. Using in-silica analysis and reverse vaccinology, two leader proteins were identified to be potential vaccine candidates for development of a multi-epitope drug. The results of this study can provide further researchers better aspects and direction on developing vaccine and immune responses against COVID19. This work also aims at promoting the use of existing bioinformatics tools to faster streamline the pipeline of vaccine development.The Situation of COVID19A new infection respiratory disease was first observed in the month of December 2019, in Wuhan, situated in the Hubei province, China. Studies have indicated that the reason of this disease was the emergence of a genetically-novel coronavirus closely related to SARS-CoV. This coronavirus, now named as nCoV-19, is the reason behind the spread of this fatal respiratory disease, now named as COVID-19. The initial group of infections is supposedly linked with the Huanan seafood market, most likely due to animal contact. Eventually, human-to-human interaction occurred and resulted in the transmission of the virus to humans. [13].Since then, nCoV-19 has been rapidly spreading within China and other parts of World. At the time of writing this article (mid-March 2020), COVID-19 has spread across 146 countries. A count of 164,837 cases have been confirmed of being diagnosed with COVID-19, and a total of 6470 deaths have occurred. The cumulative cases have been depicting a rising trend and the numbers are just increasing. WHO has declared COVID-19 to be a “global health emergency”. [14].Current Scenario and ObjectivesCurrently, research is being conducted on a massive level to understand the immunology and genetic characteristics of the disease. However, no cure or vaccine of nCoV-19 has been developed at the time of writing this article.Though, nCoV-19 and SARS-CoV are almost genetically similar, the respiratory syndrome caused by both of them, COVID-19 and SARS respectively, are completely different. Studies have indicated that –“SARS was more deadly but much less infectious than COVID-19”.-World Health Organization

scholarly journals ReVac: a reverse vaccinology computational pipeline for prioritization of prokaryotic protein vaccine candidates

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Adonis D’Mello ◽  
Christian P. Ahearn ◽  
Timothy F. Murphy ◽  
Hervé Tettelin
Keyword(s):  
Machine Learning ◽  
Experimental Testing ◽  
Negative Control ◽  
Reverse Vaccinology ◽  
Learning Approaches ◽  
Protein Vaccine ◽  
Vaccine Candidates ◽  
Variable Expression ◽  
Prediction Tools ◽  
Potential Vaccine

Abstract Background Reverse vaccinology accelerates the discovery of potential vaccine candidates (PVCs) prior to experimental validation. Current programs typically use one bacterial proteome to identify PVCs through a filtering architecture using feature prediction programs or a machine learning approach. Filtering approaches may eliminate potential antigens based on limitations in the accuracy of prediction tools used. Machine learning approaches are heavily dependent on the selection of training datasets with experimentally validated antigens (positive control) and non-protective-antigens (negative control). The use of one or few bacterial proteomes does not assess PVC conservation among strains, an important feature of vaccine antigens. Results We present ReVac, which implements both a panoply of feature prediction programs without filtering out proteins, and scoring of candidates based on predictions made on curated positive and negative control PVCs datasets. ReVac surveys several genomes assessing protein conservation, as well as DNA and protein repeats, which may result in variable expression of PVCs. ReVac’s orthologous clustering of conserved genes, identifies core and dispensable genome components. This is useful for determining the degree of conservation of PVCs among the population of isolates for a given pathogen. Potential vaccine candidates are then prioritized based on conservation and overall feature-based scoring. We present the application of ReVac, applied to 69 Moraxella catarrhalis and 270 non-typeable Haemophilus influenzae genomes, prioritizing 64 and 29 proteins as PVCs, respectively. Conclusion ReVac’s use of a scoring scheme ranks PVCs for subsequent experimental testing. It employs a redundancy-based approach in its predictions of features using several prediction tools. The protein’s features are collated, and each protein is ranked based on the scoring scheme. Multi-genome analyses performed in ReVac allow for a comprehensive overview of PVCs from a pan-genome perspective, as an essential pre-requisite for any bacterial subunit vaccine design. ReVac prioritized PVCs of two human respiratory pathogens, identifying both novel and previously validated PVCs.

scholarly journals PanRV: Pangenome-reverse vaccinology approach for identifications of potential vaccine candidates in microbial pangenome

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Kanwal Naz ◽  
Anam Naz ◽  
Shifa Tariq Ashraf ◽  
Muhammad Rizwan ◽  
Jamil Ahmad ◽  
...  
Keyword(s):  
Reverse Vaccinology ◽  
Vaccine Candidates ◽  
Potential Vaccine

Identification of peritrophins as potential vaccine candidates against sea lice: A reverse vaccinology approach

2019 ◽  
Vol 91 ◽  
pp. 393
Author(s):  
A. Casuso ◽  
G. Núñez-Acuña ◽  
V. Valenzuela-Muñoz ◽  
Y. Leal ◽  
C. Gallardo-Escárate
Keyword(s):  
Reverse Vaccinology ◽  
Sea Lice ◽  
Vaccine Candidates ◽  
Potential Vaccine

Identification of potential vaccine candidates against SARS-CoV-2, A step forward to fight COVID 19: A Reverse Vaccinology Approach (Preprint)

2021 ◽  
Author(s):  
Ekta Gupta ◽  
Rupesh Kumar Mishra ◽  
Ravi Ranjan Kumar Niraj
Keyword(s):  
Viral Disease ◽  
Surface Glycoprotein ◽  
Antigenic Peptide ◽  
Reverse Vaccinology ◽  
Effective Vaccine ◽  
Global Public Health ◽  
Health Crisis ◽  
Vaccine Candidates ◽  
Cell Mediated Immune Response ◽  
Potential Vaccine

UNSTRUCTURED The recent Coronavirus Disease 2019 (COVID-19) causes an immense health crisis to global public health. The etiological agent of COVID-19, a recently arose disease is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Presently, more research in the field of effecting vaccine against this emerged viral disease is indeed a need of the hour. In the current study, we collected SARS-CoV-2 genome which is prominent in India against human host, furthermore using reverse vaccinology here we prove effective vaccine candidates that can be milestone in the battle against COVID19. This novel study divulged one promising antigenic peptide GVYFASTEK from surface glycoprotein (protein accession no. - QIA98583.1) of SARS-CoV-2, which was predicted to be interacted with MHC alleles and showed up to 90% conservancy and high value of antigenicity. Subsequently, the molecular docking and simulation studies were verified molecular interaction of this prime antigenic peptide with the residues of HLA-A*11-01 allele for MHC Class I. After vigorous analysis, this peptide was predicted to be a suitable epitope that is capable to induce a strong cell-mediated immune response against the SARS-CoV-2. Consequences from the current study could facilitate selecting SARS-CoV-2 epitopes for vaccine production pipelines in the immediate future. This novel research will certainly pave the way for a fast, reliable and virtuous platform to provide timely countermeasure of this dangerous pandemic disease, COVID-19.

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