A combination of epitope prediction and molecular docking allows for good identification of MHC class I restricted T-cell epitopes

Zhang, Xue Wu

doi:10.1016/j.compbiolchem.2013.03.003

Cited by 16 publications

(10 citation statements)

References 28 publications

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“…In addition, our predicted epitope delineated greater binding affinities to HLA-A*68:02 than its native ligand. Importantly, a study from Zhang reported the highest binding affinity of NTASWFTAL towards the HLA-A2/A0201-restricted T-cell epitopes [56]. The results from the molecular docking studies in the current study also revealed that epitope NTASWFTAL formed H-bond with both chain-A and chain-B of the HLA molecule and attractive charges were also responsible for the binding.…”

Section: Discussionsupporting

confidence: 60%

Epitope-Based Immunoinformatics Approach on Nucleocapsid Protein of Severe Acute Respiratory Syndrome-Coronavirus-2

Rakib

Sami

et al. 2020

Molecules

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With an increasing fatality rate, severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has emerged as a promising threat to human health worldwide. Recently, the World Health Organization (WHO) has announced the infectious disease caused by SARS-CoV-2, which is known as coronavirus disease-2019 (COVID-2019), as a global pandemic. Additionally, the positive cases are still following an upward trend worldwide and as a corollary, there is a need for a potential vaccine to impede the progression of the disease. Lately, it has been documented that the nucleocapsid (N) protein of SARS-CoV-2 is responsible for viral replication and interferes with host immune responses. We comparatively analyzed the sequences of N protein of SARS-CoV-2 for the identification of core attributes and analyzed the ancestry through phylogenetic analysis. Subsequently, we predicted the most immunogenic epitope for the T-cell and B-cell. Importantly, our investigation mainly focused on major histocompatibility complex (MHC) class I potential peptides and NTASWFTAL interacted with most human leukocyte antigen (HLA) that are encoded by MHC class I molecules. Further, molecular docking analysis unveiled that NTASWFTAL possessed a greater affinity towards HLA and also available in a greater range of the population. Our study provides a consolidated base for vaccine design and we hope that this computational analysis will pave the way for designing novel vaccine candidates.

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Section: Discussionsupporting

confidence: 60%

Epitope-Based Immunoinformatics Approach on Nucleocapsid Protein of Severe Acute Respiratory Syndrome-Coronavirus-2

Rakib

Sami

et al. 2020

Molecules

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show abstract

“…Although this study highlighted the limitations of such algorithms, the predictions were successful for peptides of SARS-CoV-1, as the predicted HLA restriction was concordant with the experimental HLA restriction for six out of seven N protein peptides (4 HLA-B*40:01, 1 HLA-B*55:02 and 1 HLA-B*15:25 restric-tions). Interestingly, Zhang [16] designed a novel in silico approach for the identification of HLA class I T cell epitopes through epitope prediction models in combination with molecular docking techniques (3D structural modelling of peptide-HLA-TcR complex) and applied it to predict T cell epitopes in SARS-CoV-1 S, N and M proteins (the major structural proteins of SARS-CoV-1), with 90% accuracy (correlation with experimental data) for S protein.…”

Section: Bioinformatic and Experimental Studiesmentioning

confidence: 99%

HLA studies in the context of coronavirus outbreaks

Sanchez‐Mazas¹

2020

Swiss Med Wkly

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The unique health situation that we humans are currently living in at the global scale due to the COVID-19 pandemic urges scientists to gain maximum understanding about the characteristics of the new SARS-CoV-2 coronavirus, the way it contaminates individuals, and the genetic and non-genetic factors that influence our susceptibility or protection to its too often severe consequences. Little is known at the moment about specific immune mechanisms that would work against SARS-CoV-2, although such knowledge is expected to play a vital role in the absence of efficient drugs and vaccines, as is the case today. In this context, a particular focus has to be given to the human leucocyte antigen (HLA) system that governs our adaptive immunity.HLA genes are known to display the highest level of diversity of our genome, with thousands of different alleles reported nowadays, each allele being also a combination of multiple single nucleotide polymorphisms (SNPs). This unique level of polymorphism likely results from thousands of generations (since the emergence of modern humans) of HLA molecular evolution where natural selection favoured genetic variation, balancing selection in the form of heterozygous advantage (in its different versions) being the most widely accepted model. The idea of such a model is that heterozygous individuals would display a higher fitness than homozygotes in pathogen-rich environments, different HLA molecules assuming complementary abilities to present pathogen-derived peptides to T cells and elicit an immune response. The consequence of this kind of selection, at the population level, is that HLA allele frequency distributions are more even than expected under neutral evolution, most human populations displaying between 85% and 95% heterozygosity at each HLA locus.

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“…All peptides collected from the IEDB database (Vita et al 2019) were of viral origin and were confirmed in experimental immunoassays. Similar data were extracted from selected publications (Chen et al 2005;Liu et al 2010;Ogishi and Yotsuyanagi 2019;Tsao et al 2006;Y.-D. Wang et al 2004;Zhang 2013). The number of pHLAs (per immunoassay category) used for training is given in Table 2.…”

Section: Immunogenicity Datamentioning

confidence: 99%

AI aided design of epitope-based vaccine for the induction of cellular immune responses against SARS-CoV-2

Mazzocco¹,

Niemiec²,

Myronov

et al. 2020

Preprint

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The heavy burden imposed by the COVID-19 pandemic on our society triggered the race towards the development of therapies or preventive strategies. Among these, antibodies and vaccines are particularly attractive because of their high specificity, low probability of drug-drug interaction, and potentially long-standing protective effects. While the threat at hand justifies the pace of research, the implementation of therapeutic strategies cannot be exempted from safety considerations. There are several potential adverse events reported after the vaccination or antibody therapy, but two are of utmost importance: antibody-dependent enhancement (ADE) and cytokine storm syndrome (CSS). On the other hand, the depletion or exhaustion of T-cells has been reported to be associated with worse prognosis in COVID-19 patients. This observation suggests a potential role of vaccines eliciting cellular immunity, which might simultaneously limit the risk of ADE and CSS. Such risk was proposed to be associated with FcR-induced activation of proinflammatory macrophages (M1) by Fu et al. 2020 and Iwasaki et al. 2020. All aspects of the newly developed vaccine (including the route of administration, delivery system, and adjuvant selection) may affect its effectiveness and safety. In this work we use a novel in silico approach (based on AI and bioinformatics methods) developed to support the design of epitope-based vaccines. We evaluated the capabilities of our method for predicting the immunogenicity of epitopes. Next, the results of our approach were compared with other vaccine-design strategies reported in the literature. The risk of immuno-toxicity was also assessed. The analysis of epitope conservation among other Coronaviridae was carried out in order to facilitate the selection of peptides shared across different SARS-CoV-2 strains and which might be conserved in emerging zootic coronavirus strains. Finally, the potential applicability of the selected epitopes for the development of a vaccine eliciting cellular immunity for COVID-19 was discussed, highlighting the benefits and challenges of such an approach.

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A combination of epitope prediction and molecular docking allows for good identification of MHC class I restricted T-cell epitopes

Cited by 16 publications

References 28 publications

Epitope-Based Immunoinformatics Approach on Nucleocapsid Protein of Severe Acute Respiratory Syndrome-Coronavirus-2

Epitope-Based Immunoinformatics Approach on Nucleocapsid Protein of Severe Acute Respiratory Syndrome-Coronavirus-2

HLA studies in the context of coronavirus outbreaks

AI aided design of epitope-based vaccine for the induction of cellular immune responses against SARS-CoV-2

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