Designing a multi-epitope vaccine against the Lassa virus through reverse vaccinology, subtractive proteomics, and immunoinformatics approaches

Omoniyi, Akinyemi Ademola; Adebisi, Samuel Sunday; Musa, Sunday Abraham; Nzalak, James Oliver; Danborno, Barnabas; Bauchi, Zainab Mahmood; Badmus, Iswat Taiwo; Olatomide, Oluwasegun Davis; Oladimeji, Olalekan Jerry; Nyengaard, Jens Randel

doi:10.1016/j.imu.2021.100683

Cited by 6 publications

(6 citation statements)

References 103 publications

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“…Using the threshold of 0.4, the viral components were classified into antigens and non-antigens (scores below the threshold) using the VaxiJen server. For accurate component selection, the protegenicity (protective antigen nature), the localization, and transmembrane helices of the protein sequences were further determined 29 , 97 . This process ascertains the suitability of candidate vaccine selection for experimental validation in the vaccine development process by ensuring that the vaccines do not contain transmembrane helix regions (to ease their expression) and the proteins must not share homology with human proteins to escape the potentiality of causing autoimmune response 98 – 100 .…”

Section: Discussionmentioning

confidence: 99%

“…It does this by using a position-specific scoring matrix (PSSM) for immune epitope prediction and machine learning techniques for the prediction of immune interactions. At intervals of four weeks 29 , 86 , three injections were given and all simulation parameters were set at default with time steps set at 1, 84, and 168, where each time step is 8 h and time step 1 is injection at time = 0. To probe for clonal selection, additional 12 injections of the designed vaccine construct were given four weeks apart to mimic repeated antigen exposure seen in a typical endemic area.…”

Section: Methodsmentioning

confidence: 99%

“…Immunoinformatics in vaccine development provides a quick, reliable, and efficient approach to disease vaccine development 27 . The antigenicity of pathogen secretory proteins makes them an excellent candidate for predicting B and T cell epitopes in vaccine production 28 , 29 . Despite the high mortality rate, no antiviral drugs or vaccines for CCHF have been approved 30 , 31 .…”

Section: Introductionmentioning

confidence: 99%

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In silico design and analyses of a multi-epitope vaccine against Crimean-Congo hemorrhagic fever virus through reverse vaccinology and immunoinformatics approaches

Omoniyi

Adebisi

Musa

et al. 2022

Sci Rep

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Crimean Congo Hemorrhagic Fever virus (CCHFV) is a deadly human pathogen that causes an emerging zoonotic disease with a broad geographic spread, especially in Africa, Asia, and Europe, and the second most common viral hemorrhagic fever and widely transmitted tick-borne viral disease. Following infection, the patients are presented with a variety of clinical manifestations and a fatality rate of 40%. Despite the high fatality rate, there are unmet clinical interventions, as no antiviral drugs or vaccines for CCHF have been approved. Immunoinformatics pipeline and reverse vaccinology were used in this study to design a multi-epitope vaccine that may elicit a protective humoral and cellular immune response against Crimean-Congo hemorrhagic fever virus infection. Three essential virulent and antigenic proteins (S, M, and L) were used to predict seven CTL and 18 HTL epitopes that were non-allergenic, antigenic, IFN-γ inducing, and non-toxic. The epitopes were connected using linkers and 50S ribosomal protein L7/L12 was used as an adjuvant and raised a multi-epitope vaccine (MEV) that is 567 amino acids long. Molecular docking and simulation of the predicted 3D structure of the MEV with the toll-like (TLR2, TLR3, and TLR4) receptors and major histocompatibility complex (MCH-I and MCH-II) indicate high interactions and stability of the complexes, MM-GBSA free binding energy calculation revealed a favourable protein–protein complex. Maximum MEV expression was achieved with a CAI value of 0.98 through in silico cloning in the Drosophila melanogaster host. According to the immune simulation, IgG1, T-helper cells, T-cytotoxic cells, INF-γ, and IL-2 were predicted to be significantly elevated. These robust computational analyses demonstrated that the proposed MEV is effective in preventing CCHFV infections. However, it is still necessary to conduct both in vitro and in vivo experiments to validate the potential of the vaccine.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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In silico design and analyses of a multi-epitope vaccine against Crimean-Congo hemorrhagic fever virus through reverse vaccinology and immunoinformatics approaches

Omoniyi

Adebisi

Musa

et al. 2022

Sci Rep

Self Cite

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“…We can also mention the multi-epitope peptide vaccine against antibiotic resistance ( Ismail et al, 2021 ), or the nanodiamond-peptide-based vaccine as an ‘emergency’ pan-vaccine against newly emerging viruses or bacteria ( Billy et al, 2021 ). Vaccinomics approach and advanced bioinformatics tools are helpful in design of effective vaccines against Marburg ( Pervin and Oany, 2021 ), Nipah ( Soltan et al, 2021 ), Zika ( Antonelli et al, 2022 ), Ebola ( Nandy et al, 2018 ; Mustafa et al, 2021 ), Lassa ( Omoniyi et al, 2021 ), rift valley fever ( Fatima et al, 2022 ) viruses as well as malaria ( Aza-Conde et al, 2021 ) caused by parasites—potential agents of pandemics, including bioterrorism. The ‘smart’ vaccine strategy uses advanced machine learning to peptide-based epitope mapping and it precisely predicts the binding between viral peptides and human proteins, leading to an increase in the speed of the design and development of broad spectrum (‘universal’) vaccines ( Du et al, 2022 ).…”

Section: Landscape Of Opportunities: Topical Insightsmentioning

confidence: 99%

Smart therapies against global pandemics: A potential of short peptides

et al. 2022

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BackgroundAs we entered the third year of this pandemic, since the World Health Organisation (WHO) declared in March 2020 the novel coronavirus severe acute respiratory syndrome (SARS-CoV2) outbreak as a global pandemic COVID-19 (COronaVIrus Disease 19), we are still fighting with newer and newer viral mutations. The pandemic has passed the grim milestone of over 6.4 million COVID19 deaths, from more than 550 million reported cases thus far. In fact, more than 15 million people can die by the end of this year. It is highly likely that this pandemic will become endemic, while the full evolutionary potential of coronaviruses has yet to be revealed. The next pandemic is coming. A microbe with features of SARS-Middle East respiratory syndrome (MERS) and SARS-CoV-2 could lead to significantly more catastrophic loss of life. The co-evolution with other viruses should not be neglected. According to the WHO, we should expect diverse zoonotic, outbreakprone microbes, including highly pathogenic strains of influenza, Nipah, Ebola, Zika, or hemorrhagic fever viruses. 'It's an evolutionary certainty that there will be another virus with the potential to be more transmittable and deadly than this one', said Tedros Adhanom Ghebreyesus, director-general of the WHO. On the other hand, in both poor countries and regions of armed conflict, where vaccination is hampered, historic diseases are re-emerging, with migration and displacement influencing transmission risk and limiting control, and raising potential for additional outbreaks. Furthermore, there are other looming terrible threats to humanity as damaging as the bubonic plagues, such as bioterrorism or antibiotic resistant microorganisms. In most cases, both effective prevention and treatment options are limited.

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“…Integration of immune-informatics in vaccine development offers a rapid, accurate, and efficient method for creating disease vaccines ( 17 ). Pathogen secretory proteins are a great candidate for predicting B and T cell epitopes in the development of vaccines due to their antigenicity ( 18 , 19 ). The aim of this research is to construct a novel multi-epitope vaccine responsible to elicit humoral and cell mediated immune response against human monkeypox by extracting highly immunogenic epitopes from cell surface binding protein using an in silico immune-informatics pipeline.…”

Section: Introductionmentioning

confidence: 99%

Immuno-informatics profiling of monkeypox virus cell surface binding protein for designing a next generation multi-valent peptide-based vaccine

et al. 2022

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Monkeypox is a viral etiological agent with hallmarks analogous to those observed in smallpox cases in the past. The ongoing outbreak of Monkeypox viral infection is becoming a global health problem. Multi-valent peptide based next generation vaccines provides us a promising solution to combat these emerging infectious diseases by eliciting cell-mediated and humoral immune response. Considering the success rate of subtractive proteomics pipeline and reverse vaccinology approach, in this study, we have developed a novel, next-generation, multi-valent, in silico peptide based vaccine construct by employing cell surface binding protein. After analyzing physiochemical and biological properties of the selected target, the protein was subjected to B cell derived T cell epitope mapping. Iterative scrutinization lead to the identification of two highly antigenic, virulent, non-allergic, non-toxic, water soluble, and Interferon-gamma inducer epitopes i.e. HYITENYRN and TTSPVRENY. We estimated that the shortlisted epitopes for vaccine construction, roughly correspond to 99.74% of the world’s population. UK, Finland and Sweden had the highest overall population coverage at 100% which is followed by Austria (99.99%), Germany (99.99%), France (99.98%), Poland (99.96), Croatia (99.93), Czech Republic (99.87%), Belgium (99.87), Italy (99.86%), China (97.83%), India (97.35%) and Pakistan (97.13%). The designed vaccine construct comprises of 150 amino acids with a molecular weight of 16.97242 kDa. Molecular docking studies of the modelled MEMPV (Multi-epitope Monkeypox Vaccine) with MHC I (PDB ID: 1I1Y), MHC II (PDB ID: 1KG0), and other immune mediators i.e. toll like receptors TLR3 (PDB ID: 2A0Z), and TLR4 (PDB ID: 4G8A) revealed strong binding affinity with immune receptors. Host immune simulation results predicted that the designed vaccine has strong potency to induce immune responses against target pathogen in the form of cellular and antibody-dependent immunity. Our findings suggest that the hypothesized vaccine candidate can be utilized as a potential therapeutic against Monkeypox however experimental study is required to validate the results and safe immunogenicity.

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Designing a multi-epitope vaccine against the Lassa virus through reverse vaccinology, subtractive proteomics, and immunoinformatics approaches

Cited by 6 publications

References 103 publications

In silico design and analyses of a multi-epitope vaccine against Crimean-Congo hemorrhagic fever virus through reverse vaccinology and immunoinformatics approaches

In silico design and analyses of a multi-epitope vaccine against Crimean-Congo hemorrhagic fever virus through reverse vaccinology and immunoinformatics approaches

Smart therapies against global pandemics: A potential of short peptides

Immuno-informatics profiling of monkeypox virus cell surface binding protein for designing a next generation multi-valent peptide-based vaccine

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