Vaxign: the first web-based vaccine design program for reverse vaccinology and applications for vaccine development.
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ABSTRACT:
SUBMITTER: He Y
PROVIDER: S-EPMC2910479 | biostudies-literature | 2010
REPOSITORIES: biostudies-literature
Publications
Vaxign: the first web-based vaccine design program for reverse vaccinology and applications for vaccine development.
He Yongqun Y Xiang Zuoshuang Z Mobley Harry L T HL
Journal of biomedicine & biotechnology 20100704
Vaxign is the first web-based vaccine design system that predicts vaccine targets based on genome sequences using the strategy of reverse vaccinology. Predicted features in the Vaxign pipeline include protein subcellular location, transmembrane helices, adhesin probability, conservation to human and/or mouse proteins, sequence exclusion from genome(s) of nonpathogenic strain(s), and epitope binding to MHC class I and class II. The precomputed Vaxign database contains prediction of vaccine target ...[more]
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Project description:Vaccination is one of the most significant inventions in medicine. Reverse vaccinology (RV) is a state-of-the-art technique to predict vaccine candidates from pathogen's genome(s). To promote vaccine development, we updated Vaxign2, the first web-based vaccine design program using reverse vaccinology with machine learning. Vaxign2 is a comprehensive web server for rational vaccine design, consisting of predictive and computational workflow components. The predictive part includes the original Vaxign filtering-based method and a new machine learning-based method, Vaxign-ML. The benchmarking results using a validation dataset showed that Vaxign-ML had superior prediction performance compared to other RV tools. Besides the prediction component, Vaxign2 implemented various post-prediction analyses to significantly enhance users' capability to refine the prediction results based on different vaccine design rationales and considerably reduce user time to analyze the Vaxign/Vaxign-ML prediction results. Users provide proteome sequences as input data, select candidates based on Vaxign outputs and Vaxign-ML scores, and perform post-prediction analysis. Vaxign2 also includes precomputed results from approximately 1 million proteins in 398 proteomes of 36 pathogens. As a demonstration, Vaxign2 was used to effectively analyse SARS-CoV-2, the coronavirus causing COVID-19. The comprehensive framework of Vaxign2 can support better and more rational vaccine design. Vaxign2 is publicly accessible at http://www.violinet.org/vaxign2.
| S-EPMC8218197 | biostudies-literature
Project description:To ultimately combat the emerging COVID-19 pandemic, it is desired to develop an effective and safe vaccine against this highly contagious disease caused by the SARS-CoV-2 coronavirus. Our literature and clinical trial survey showed that the whole virus, as well as the spike (S) protein, nucleocapsid (N) protein, and membrane (M) protein, have been tested for vaccine development against SARS and MERS. However, these vaccine candidates might lack the induction of complete protection and have safety concerns. We then applied the Vaxign and the newly developed machine learning-based Vaxign-ML reverse vaccinology tools to predict COVID-19 vaccine candidates. Our Vaxign analysis found that the SARS-CoV-2 N protein sequence is conserved with SARS-CoV and MERS-CoV but not from the other four human coronaviruses causing mild symptoms. By investigating the entire proteome of SARS-CoV-2, six proteins, including the S protein and five non-structural proteins (nsp3, 3CL-pro, and nsp8-10), were predicted to be adhesins, which are crucial to the viral adhering and host invasion. The S, nsp3, and nsp8 proteins were also predicted by Vaxign-ML to induce high protective antigenicity. Besides the commonly used S protein, the nsp3 protein has not been tested in any coronavirus vaccine studies and was selected for further investigation. The nsp3 was found to be more conserved among SARS-CoV-2, SARS-CoV, and MERS-CoV than among 15 coronaviruses infecting human and other animals. The protein was also predicted to contain promiscuous MHC-I and MHC-II T-cell epitopes, and the predicted linear B-cell epitopes were found to be localized on the surface of the protein. Our predicted vaccine targets have the potential for effective and safe COVID-19 vaccine development. We also propose that an "Sp/Nsp cocktail vaccine" containing a structural protein(s) (Sp) and a non-structural protein(s) (Nsp) would stimulate effective complementary immune responses.
| S-EPMC7350702 | biostudies-literature
Project description:To ultimately combat the emerging COVID-19 pandemic, it is desired to develop an effective and safe vaccine against this highly contagious disease caused by the SARS-CoV-2 coronavirus. Our literature and clinical trial survey showed that the whole virus, as well as the spike (S) protein, nucleocapsid (N) protein, and membrane protein, have been tested for vaccine development against SARS and MERS. We further used the Vaxign reverse vaccinology tool and the newly developed Vaxign-ML machine learning tool to predict COVID-19 vaccine candidates. The N protein was found to be conserved in the more pathogenic strains (SARS/MERS/COVID-19), but not in the other human coronaviruses that mostly cause mild symptoms. By investigating the entire proteome of SARS-CoV-2, six proteins, including the S protein and five non-structural proteins (nsp3, 3CL-pro, and nsp8-10) were predicted to be adhesins, which are crucial to the viral adhering and host invasion. The S, nsp3, and nsp8 proteins were also predicted by Vaxign-ML to induce high protective antigenicity. Besides the commonly used S protein, the nsp3 protein has not been tested in any coronavirus vaccine studies and was selected for further investigation. The nsp3 was found to be more conserved among SARS-CoV-2, SARS-CoV, and MERS-CoV than among 15 coronaviruses infecting human and other animals. The protein was also predicted to contain promiscuous MHC-I and MHC-II T-cell epitopes, and linear B-cell epitopes localized in specific locations and functional domains of the protein. Our predicted vaccine targets provide new strategies for effective and safe COVID-19 vaccine development.
| S-EPMC7239068 | biostudies-literature
Project description:Respiratory syncytial virus (RSV) is primarily associated with respiratory disorders globally. Despite the availability of information, there is still no competitive vaccine available for RSV. Therefore, the present study has been designed to develop a multiepitope-based subunit vaccine (MEV) using a reverse vaccinology approach to curb RSV infections. Briefly, two highly antigenic and conserved proteins of RSV (glycoprotein and fusion protein) were selected and potential epitopes of different categories (B-cell and T-cell) were identified from them. Eminently antigenic and overlapping epitopes, which demonstrated strong associations with their respective human leukocyte antigen (HLA) alleles and depicted collective ~70% coverage of the world's populace, were shortlisted. Finally, 282 amino acids long MEV construct was established by connecting 13 major histocompatibility complex (MHC) class-I with two MHC class-II epitopes with appropriate adjuvant and linkers. Adjuvant and linkers were added to increase the immunogenic stimulation of the MEV. Developed MEV was stable, soluble, non-allergenic, non-toxic, flexible and highly antigenic. Furthermore, molecular docking and molecular dynamics (MD) simulations analyses were carried out. Results have shown a firm and robust binding affinity of MEV with human pathogenic toll-like receptor three (TLR3). The computationally mediated immune response of MEV demonstrated increased interferon-γ production, a significant abundance of immunoglobulin and activation of macrophages which are essential for immune-response against RSV. Moreover, MEV codons were optimized and in silico cloning was performed, to ensure its increased expression. These outcomes proposed that the MEV developed in this study will be a significant candidate against RSV to control and prevent RSV-related disorders if further investigated experimentally.
| S-EPMC7350008 | biostudies-literature
Project description:BackgroundStreptococcus pneumoniae is a major pathogen that poses a significant hazard to global health, causing a variety of infections including pneumonia, meningitis, and sepsis. The emergence of antibiotic-resistant strains has increased the difficulty of conventional antibiotic treatment, highlighting the need for alternative therapies such as multi-epitope vaccines. In this study, immunoinformatics algorithms were used to identify potential vaccine candidates based on the extracellular immunogenic protein Pneumococcal surface protein C (PspC).MethodThe protein sequence of PspC was retrieved from NCBI for the development of the multi-epitope vaccine (MEV), and potential B cell and T cell epitopes were identified. Linkers including EAAAK, AAY, and CPGPG were used to connect the epitopes. Through molecular docking, molecular dynamics, and immunological simulation, the affinity between MEV and Toll-like receptors was determined. After cloning the MEV construct into the PET28a ( +) vector, SnapGene was used to achieve expression in Escherichia coli.ResultThe constructed MEV was discovered to be stable, non-allergenic, and antigenic. Microscopic interactions between ligand and receptor are confirmed by molecular docking and molecular dynamics simulation. The use of an in-silico cloning approach guarantees the optimal expression and translation efficiency of the vaccine within an expression vector.ConclusionOur study demonstrates the potential of in silico approaches for designing effective multi-epitope vaccines against S. pneumoniae. The designated vaccine exhibits the required physicochemical, structural, and immunological characteristics of a successful vaccine against SPN. However, laboratory validation is required to confirm the safety and immunogenicity of the proposed vaccine design.
| S-EPMC10716094 | biostudies-literature
Project description:The discovery of vaccine antigens through whole genome sequencing (WGS) contrasts with the classical hypothesis-driven laboratory-based analysis of microbes to identify components to elicit protective immunity. This radical change in scientific direction and action in vaccine research is captured in the term reverse vaccinology. The complete genome sequence of an isolate of Neisseria meningitidis serogroup B (MenB) was systematically analyzed to identify proteins predicted to be secreted or exported to the outer membrane. This identified hundreds of genes coding for potential surface-exposed antigens. These were amplified, cloned in expression vectors and used to immunize mice. Antisera against 350 recombinant antigens were obtained and analyzed in a panel of immunological assays from which 28 were selected as potentially protective based on the -antibody dependent, complement mediated- serum bactericidal activity assay. Testing of these candidate vaccine antigens, using a large globally representative strain collection of Neisseria species isolated from cases of disease and carriage, indicated that no single component would be sufficient to induce broad coverage and that a "universal" vaccine should contain multiple antigens. The final choice of antigens to be included was based on cross-protective ability, assayed by serum bactericidal activity and maximum coverage of the extensive antigenic variability of MenB strains. The resulting multivalent vaccine formulation selected consisted of three recombinant antigens (Neisserial Heparin Binding Antigen or NHBA, Factor H binding protein or fHbp and Neisseria Adhesin A or NadA). To improve immunogenicity and potential strain coverage, an outer membrane vesicle component obtained from the epidemic New Zealand strain (OMVNz) was added to the formulation to create a four component vaccine, called 4CMenB. A series of phase 2 and 3 clinical trials were conducted to evaluate safety and tolerability and to estimate the vaccine effectiveness of human immune responses at different ages and how these were affected by various factors including concomitant vaccine use and lot-to-lot consistency. 4CMenB was approved in Europe in 2013 and introduced in the National Immunization Program in the UK starting from September 2015 when the vaccine was offered to all newborns using a 2, 4, and 12 months schedule., The effectiveness against invasive MenB disease measured at 11 months after the study start and 5 months after the second vaccination was 83% and there have been no safety concerns.
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Project description:Streptococcus mitis (S. mitis) may transform into highly pathogenic bacteria. The aim of the present study was to identify potential antigen targets for designing an effective vaccine against the pathogenic S. mitis321A. The genome of S. mitis321A was sequenced using an Illumina Hiseq2000 instrument. Subsequently, Glimmer 3.02 and Tandem Repeat Finder (TRF) 4.04 were used to predict genes and tandem repeats, respectively, with DNA sequence function analysis using the Basic Local Alignment Search Tool (BLAST) in the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Cluster of Orthologous Groups of proteins (COG) databases. Putative gene antigen candidates were screened with BLAST ahead of phylogenetic tree analysis. The DNA sequence assembly size was 2,110,680 bp with 40.12% GC, 6 scaffolds and 9 contig. Consequently, 1,944 genes were predicted, and 119 TRF, 56 microsatellite DNA, 10 minisatellite DNA and 154 transposons were acquired. The predicted genes were associated with various pathways and functions concerning membrane transport and energy metabolism. Multiple putative genes encoding surface proteins, secreted proteins and virulence factors, as well as essential genes were determined. The majority of essential genes belonged to a phylogenetic lineage, while 321AGL000129 and 321AGL000299 were on the same branch. The current study provided useful information regarding the biological function of the S. mitis321A genome and recommends putative antigen candidates for developing a potent vaccine against S. mitis.
| S-EPMC5983942 | biostudies-literature
Project description:Mycobacterium tuberculosis (Mtb) is responsible for high mortality rates in many low- and middle-income countries. This infectious disease remains accountable for around 1.4 million deaths yearly. Finding effective control measures against Mtb has become imperative. Vaccination has been regarded as the safe and lasting control measure to curtail the impact of Mtb. This study used the Mtb protein biomarker PE_PGRS17 to design a multi-epitope vaccine. A previous study predicted a strong antigenic property of PE_PGRS17. Immunogenic properties such as antigenicity, toxicity, and allergenicity were predicted for the PE_PGRS17 biomarker, specific B- and T-cell epitope sequences, and the final multiple epitope vaccine (MEV) construct. Algorithmic tools predicted the T- and B-cell epitopes and those that met the immunogenic properties were selected to construct the MEV candidate for predicted vaccine development. The epitopes were joined via linkers and an adjuvant was attached to the terminals of the entire vaccine construct. Immunogenic properties, and physicochemical and structural predictions gave insight into the MEV construct. The assembled vaccine candidate was docked with a receptor and validated using web-based tools. An immune simulation was performed to imitate the immune response after exposure to a dosed administrated predicted MEV subunit. An in silico cloning and codon optimisation gave insight into optimal expression conditions regarding the MEV candidate. In conclusion, the generated MEV construct may potentially emit both cellular and humoral responses which are vital in the development of a peptide-based vaccine against Mtb; nonetheless, further experimental validation is still required.
| S-EPMC9095442 | biostudies-literature
Project description:Crimean-Congo hemorrhagic fever (CCHF) is a viral disease caused by the Crimean-Congo hemorrhagic fever virus (CCHFV) of the Nairovirus genus. CCHF has occurred endemically in several regions of Africa, Southern Europe, and Central and Southeast Asia, with a case fatality rate of 5 to 80%. The World health organization enlisted CCHF as one of the top prioritized diseases for research and development in emergency contexts that making it a public health concern as no effective vaccine is available till date. Therefore, the present study aims to develop an effective multi-epitope subunit vaccine using immunoinformatics and reverse vaccinology approach against this virus. The B-cell and T-cell epitopes were predicted from structural and non-structural proteins, and filtered by immunogenicity, allergenicity, toxicity, conservancy, and cross-reactivity. The computational analysis revealed that the epitopes could induce an adequate immune response and had strong associations with their respective human leukocyte antigen (HLA) alleles with 98.94% of total world population coverage. Finally, the vaccine with 427 amino acids was constructed by connecting 8 cytotoxic T-lymphocytes, 4 helper T-lymphocytes, and 10 B-cell epitopes with appropriate linkers and β-defensin as an adjuvant. The antigenicity, allergenicity, solubility, and physiochemical properties of the vaccine were evaluated, followed by structural modelling, refinement, and validation. In addition, molecular docking and molecular dynamic simulations revealed a robust binding affinity and stability of the vaccine-immune receptor complex. Moreover, the codons were optimized for its higher expression in Escherichia coli (E. coli) K12 strain followed by in silico cloning. The proposed subunit vaccine developed in this study could be a potential candidate against CCHFV. However, further experimental validation is required to ensure the immunogenicity and safety profile of the proposed vaccine for combating and eradicating CCHFV.Supplementary informationThe online version contains supplementary material available at 10.1007/s10989-022-10430-0.
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Project description:BackgroundThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic began in 2019 but it remains as a serious threat today. To reduce and prevent spread of the virus, multiple vaccines have been developed. Despite the efforts in developing vaccines, Omicron strain of the virus has recently been designated as a variant of concern (VOC) by the World Health Organization (WHO).ObjectiveTo develop a vaccine candidate against Omicron strain (B.1.1.529, BA.1) of the SARS-CoV-19.MethodsWe applied reverse vaccinology methods for BA.1 and BA.2 as the vaccine target and a control, respectively. First, we predicted MHC I, MHC II and B cell epitopes based on their viral genome sequences. Second, after estimation of antigenicity, allergenicity and toxicity, a vaccine construct was assembled and tested for physicochemical properties and solubility. Third, AlphaFold2, RaptorX and RoseTTAfold servers were used to predict secondary structures and 3D structures of the vaccine construct. Fourth, molecular docking analysis was performed to test binding of our construct with angiotensin converting enzyme 2 (ACE2). Lastly, we compared mutation profiles on the epitopes between BA.1, BA.2, and wild type to estimate the efficacy of the vaccine.ResultsWe collected a total of 10 MHC I, 9 MHC II and 5 B cell epitopes for the final vaccine construct for Omicron strain. All epitopes were predicted to be antigenic, non-allergenic and non-toxic. The construct was estimated to have proper stability and solubility. The best modelled tertiary structures were selected for molecular docking analysis with ACE2 receptor.ConclusionsThese results suggest the potential efficacy of our newly developed vaccine construct as a novel vaccine candidate against Omicron strain of the coronavirus.
| S-EPMC9166176 | biostudies-literature