Immunogenicity Prediction by VaxiJen: A Ten Year Overview

Zaharieva, Nevena; Димитров, Иван; Flower, Darren R.; Doytchinova, Irini

doi:10.4172/jpb.1000454

Cited by 31 publications

(20 citation statements)

References 114 publications

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“…The four viral proteins (Supplementary File 1) of COVID-19, HCoV-229E, HCoV-OC43, SARS-CoV, HCoV-NL63, HKU1, MERS-CoV, HKU4, HKU5 and BufCoV-HKU26 were employed to determine the most antigenic sites by using B cell epitope prediction tool of IEDB and VaxiJen scoring. VaxiJen server which was well above the threshold value (0.40), usually reveal the immunogenic potential to stimulate protective response in the host organisms [17]. From the analysis, a total of 17 epitopes from S proteins, 1 epitopes from M proteins, 1 epitopes from E proteins and 5 epitopes from N proteins were found mostly immunogenic in COVID-19 with almost 100% peptides carrying more than threshold value of antigenic score of VaxiJen server (Table 2).…”

Section: Immunogenicity Prediction and Epitope Conservancy Analysismentioning

confidence: 95%

Novel Coronavirus (COVID-19): Molecular Evolutionary Analysis, Global Burden and Possible Threat to Bangladesh

Uddin¹,

Hasan²,

Harun-Al-Rashid³

et al. 2020

Preprint

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Recently a new coronavirus strain, COVID-19 has emerged in Wuhan City, China which cause disease and in many cases deaths to humans. Considering its severity a number of works are working on it and full genomic sequences has already released in the last few weeks to understand the evolutionary origin and molecular characteristics of this virus. Based on currently available genomic information a phylogenetic tree was constructed from four types of representative viral proteins (Spike, Membrane, Envelope and Nucleoproetin) of COVID-19, HCoV-229E, HCoV-OC43, SARS-CoV, HCoV-NL63, HKU1, MERS-CoV, HKU4, HKU5 and BufCoV-HKU26 clearly demonstrated that the ancestral origin and distant evolutionary relation of newly epidemic novel coronavirus (COVID-19). It had been found that COVID-19 was evolutionary related to SARS-CoV. It was also found that COVID-19 proteins were almost more than ninety (90%) similar and identical with SARS-CoV proteins. The cross-checked conservancy analysis of COVID-19 antigenic epitopes showed significant conservancy with SARS-CoV proteins. VaxiJen server reveal almost 100% immunogenic potential of four viral proteins with COVID-19. In this article, we present an effort on molecular evolutionary analysis, temperature comparison and compile and analyze epidemiological outbreak information on the 2019 novel coronavirus based on the several open datasets on COVID-19 (SARS-COV-2) and possible threat to Bangladesh.Authors Md Bashir Uddin and Mahmudul Hasan contributed equally to this work

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Section: Immunogenicity Prediction and Epitope Conservancy Analysismentioning

confidence: 95%

Novel Coronavirus (COVID-19): Molecular Evolutionary Analysis, Global Burden and Possible Threat to Bangladesh

Uddin¹,

Hasan²,

Harun-Al-Rashid³

et al. 2020

Preprint

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“…In addition, use of this approach is not feasible with peptides that bind to MHC‐II molecules as the peptide binding sequence motifs are generally more degenerate than those binding to MHC‐I molecules. Predicted motifs may contain an equal number of false positives, predicted peptide epitopes may not be actual epitopes, and there may be an equal number of false negatives (i.e., peptides not predicted to be epitopes but which are in fact epitopes) . Anchor residues play an integral part in making an effective vaccine by altering their positions …”

Section: T‐cell Epitope Prediction Methodsmentioning

confidence: 99%

“…This method solves numerically the time‐dependent behavior of a molecular system on a microscopic scale and provides detailed information on the structure and conformational changes in proteins and their associated thermodynamic properties . The use of MD simulations does not rely on the availability of binding data (IC50) to make predictions, as it requires only the experimentally determined structure of the proteins involved . MD simulations have enabled the search of epitopes by the direct assessment of the free energy of binding between two peptides .…”

Section: T‐cell Epitope Prediction Methodsmentioning

confidence: 99%

“…MHC molecules are a class of membrane proteins encoded by a highly polymorphic gene family present in all vertebrates and responsible for displaying antigens to lymphocytes. In humans, the set of genes that encode MHCs are known as the human leukocyte antigen (HLA) system, in which the HLA‐A*02:01 allele has historically been the subject of intense investigation in regards to peptide binding . MHC molecules are further classified into MHC‐I and MHC‐II according to the type of cells expressing them and thus a variety of subsequent differences, such as their structural subunits, the types of T‐cells they engage with, and the class and origin of epitopes they display.…”

Section: Introductionmentioning

confidence: 99%

“…In silico modelling of peptide immunogenicity has confirmed the importance of positions 4–6 in the binding of an antigenic peptide to MHC‐I, highlighting that residues with large and aromatic side chains are also associated with higher immunogenicity . Binding affinity of the peptide–MHC complex is the result of the balance between its association and dissociation, and is a measure widely used to identify potential T‐cell epitopes, with 500 nM being proposed as the threshold binding affinity for peptide selection, with medium binding affinities ranging from 50 to 500 nM, and values <50 nM being considered to reflect high binding affinity . The immunogenicity of a peptide has also been linked to the kinetic stability of the peptide‐MHC complex, such that peptides with higher stability (slow dissociation rate) reside longer in the MHC binding groove, maximizing their chances of being recognized by a TCR .…”

Section: Introductionmentioning

confidence: 99%

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Current methods for the prediction of T‐cell epitopes

et al. 2018

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T-cell epitopes are specific peptide sequences derived from foreign or own proteins that can initiate an immune response and which are recognized by specific T-cells when displayed on the surface of other cells. The prediction of T-cell epitopes is of particular interest in vaccine design, disease prevention and the development of immunotherapeutics. There are two principal categories of predictive methods: peptide-sequence based and peptide-structure-based. Sequence-based methods make use of various approaches to identify likely immunogenic amino acid sequences, such as sequence motifs, decision trees, partial least squares (PLS), quantitative matrices (QM), artificial neural networks (ANN), hidden Markov models (HMM), and support vector machines (SVM).Structure-based methods are more diverse in nature and involve approaches such as quantitative structure-activity relationships (QSAR), molecular modelling, molecular docking and molecular dynamics simulations (MD). This review highlights the key features of all of these approaches, provides some key examples of their application, and compares and contrasts the most important methods currently in use.

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Identification and evaluation of novel vaccine candidates against Shigella flexneri through reverse vaccinology approach

Hajialibeigi

Amani

Gargari

2021

Appl Microbiol Biotechnol

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Shigellosis is a significant type of diarrhea that causes 160,000 deaths annually in a global scale. The mortality occurs mainly in children less than 5 years of age. No licensed vaccine is available, and conventional efforts for developing an effective and safe vaccine against shigellosis have not been succeeded yet. The reverse vaccinology is a novel promising method that screens genome or proteome of an organism for finding new vaccine candidates. In this study, through reverse vaccinology approach, new vaccine candidates against Shigella flexneri were identified and experimentally evaluated. Proteomes of S. flexneri were obtained from UniProt, and then outer membrane and extracellular proteins were predicted and selected for the evaluation of transmembrane domains, protein conservation, host homology, antigenicity, and solubility. From 103 proteins, 7 high-scored proteins were introduced as novel vaccine candidates, and after Band T-cell epitope prediction, the best protein was selected for experimental studies. Recombinant protein was expressed, purified, and injected to BALB/c mice. The adhesion inhibitory effect of sera was also studied. The immunized mice demonstrated full protection against the lethal dose challenge. The sera remarkably inhibited S. flexneri adhesion to Caco-2 epithelial cells. The results indicate that identified antigen can serve for vaccine development against shigellosis and support reverse vaccinology for discovering novel effective antigens. Key points • Seven Shigella new antigens were identified by reverse vaccinology (RV) approach. • The best antigen experimented demonstrated full protection against lethal dose. • In vivo results verified RV analyses and suggest FimG as a new potent vaccine candidate.

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Immunogenicity Prediction by VaxiJen: A Ten Year Overview

Cited by 31 publications

References 114 publications

Novel Coronavirus (COVID-19): Molecular Evolutionary Analysis, Global Burden and Possible Threat to Bangladesh

Novel Coronavirus (COVID-19): Molecular Evolutionary Analysis, Global Burden and Possible Threat to Bangladesh

Current methods for the prediction of T‐cell epitopes

Identification and evaluation of novel vaccine candidates against Shigella flexneri through reverse vaccinology approach

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