The Impact of Bioinformatics on Vaccine Design and Development

Vaccines are the pharmaceutical products that offer the best cost‐benefit ratio in the prevention or treatment of diseases. In that a vaccine is a pharmaceutical product, vaccine development and production are costly and it takes years for this to be accomplished. Several approaches have been applied to reduce the times and costs of vaccine development, mainly focusing on the selection of appropriate antigens or antigenic structures, carriers, and adjuvants. One of these approaches is the incorporation of bioinformatics methods and analyses into vaccine development. This chapter provides an overview of the application of bioinformatics strategies in vaccine design and development, supplying some successful examples of vaccines in which bioinformatics has furnished a cutting edge in their development. Reverse vaccinology, immunoinformatics, and structural vaccinology are described and addressed in the design and development of specific vaccines against infectious diseases caused by bacteria, viruses, and parasites. These include some emerging or re‐emerging infectious diseases, as well as therapeutic vaccines to fight cancer, allergies, and substance abuse, which have been facilitated and improved by using bioinformatics tools or which are under development based on bioinformatics strategies

In silico CD4+, CD8+ T-cell and B-cell immunity associated immunogenic epitope prediction and HLA distribution analysis of Zika virus

Zika virus (ZIKV) is a mosquito-borne flavivirus distributed all over Africa, South America and Asia. The infection with the virus may cause acute febrile sickness that clinically resembles dengue fever, yet there is no vaccine, no satisfactory treatment, and no means of evaluating the risk of the disease or prognosis in the infected people.In the present study, the efficacy of the host’s immune response in reducing the risk of infectious diseases was taken into account to carry out immuno-informatics driven epitope screening strategy of vaccine candidates against ZIKV. In this study, HLA distribution analysis was done to ensure the coverage of the vast majority of the population. Systematic screening of effective dominant immunogens was done with the help of Immune Epitope & ABCPred databases. The outcomes suggested that the predicted epitopes may be protective immunogens with highly conserved sequences and bear potential to induce both protective neutralizing antibodies, T & B cell responses. A total of 25 CD4+ and 16 CD8+ peptides were screened for T-cell mediated immunity. The predicted epitope "TGLDFSDLYYLTMNNKHWLV" was selected as a highly immunogenic epitope for humoral immunity. These peptides were further screened as non-toxic, immunogenic and non-mutated residues of envelop viral protein. The predicted epitope could work as suitable candidate(s) for peptide based vaccine development. Further, experimental validation of these epitopes is warranted to ensure the potential of B- and T-cells stimulation for their efficient use as vaccine candidates, and as diagnostic agents against ZIKV

Delving into dengue virus drug discovery- insights into the structural characteristics of the RNA-dependent RNA polymerase.

Masters Degrees (Pharmaceutical Sciences). University of KwaZulu-Natal. Westville, 2017.A precipitous increase in the number of flaviviral infections has been noted over the last five years. The present study sought to investigate a notorious flavivirus that has been in circulation for over 30 years. Over the last few decades, DENV has re-emerged in various serotypes and is causing mayhem in the lives of many. Dengue is dreaded for the severe fever it causes in its advanced stage. Dengue has the reputation of what is known as Dengue haemorrhagic fever (DHF) and dengue shock syndrome (DSS). Dengue remains an unmet medical need that demands prompt attention. There remains no cure or preventative therapy due to the intransigence nature of this flavivirus. Its tenacity to resist antiviral therapy has left the scientific community with the burden of finding new and accelerated techniques to curb this virus. The onus is on scientists to probe further into understanding the Dengue virus by the use of cheminformatics and bioinformatics tools in the pursuit for an inhibitor against this pernicious virus. Of the Dengue structural and non-structural enzymes, the NS5 RNA-dependent RNA polymerase has been established as a promising target due to its conserved structure amongst all serotypes and its lack of an enzymatic counterpart in mammalian cells. Attempts have been made to design vaccines and small drug molecules as potential inhibitors against DENV. The virus however is resilient, and exists in 5 serotypes with numerous strains under them, thwarting the efforts of researchers to curb its spread. This prompted us to design a study that would address the above challenges by use of CADD tools, which elaborated on the design of target-specific inhibitors of DENV from an atomistic perspective. This included a pharmacophoric approach, which utilized computational software to map out a pharmacophore model against multiple flaviviruses, as well as a focused review on DENV serotype 2 and 3, which included a route map toward the design of target-specific DENV RdRp inhibitors. We believe that these findings will aid in mitigating the effects of the DENV in the lives of compromised individuals, as well as prevent the transmission of DENV from patients to healthy individuals

Blocking Zika virus vertical transmission.

The outbreak of the Zika virus (ZIKV) has been associated with increased incidence of congenital malformations. Although recent efforts have focused on vaccine development, treatments for infected individuals are needed urgently. Sofosbuvir (SOF), an FDA-approved nucleotide analog inhibitor of the Hepatitis C (HCV) RNA-dependent RNA polymerase (RdRp) was recently shown to be protective against ZIKV both in vitro and in vivo. Here, we show that SOF protected human neural progenitor cells (NPC) and 3D neurospheres from ZIKV infection-mediated cell death and importantly restored the antiviral immune response in NPCs. In vivo, SOF treatment post-infection (p.i.) decreased viral burden in an immunodeficient mouse model. Finally, we show for the first time that acute SOF treatment of pregnant dams p.i. was well-tolerated and prevented vertical transmission of the virus to the fetus. Taken together, our data confirmed SOF-mediated sparing of human neural cell types from ZIKV-mediated cell death in vitro and reduced viral burden in vivo in animal models of chronic infection and vertical transmission, strengthening the growing body of evidence for SOF anti-ZIKV activity

Design of epitope based vaccine against shrimp white spot syndrome virus (WSSV) by targeting the envelope proteins: An immunoinformatic approach

The shrimp white spot syndrome virus (WSSV) causes significant damage to aquaculture production worldwide but a vaccine, eliciting the immunogenicity of shrimps against WSSV has yet to be developed. Thus, a programmed immunoinformatics study was conducted to find out the potential immunogens based on genome-wide screening of WSSV envelope proteins. The measurements of the phylogenetic and evolutionary distances found the common geographical routes of three countries, where the proteins from other six countries were clustered together. Among all the four major envelope proteins i.e., VP19, VP24, VP26, and VP28; AAO69663.1 from VP26 showed the highest antigenicity and thus selected for further studies. The properties of the secondary and tertiary structure including the modelled 3D protein revealed that the protein had all the properties required for a protective immunogen. The peptide regions ranging from 99 to 115 and 98 to 106, representing the sequences “VTAPRTDPAGTGAENSN” and “TVTAPRTDP” were found to be most effective regions for B-cell linear and cytotoxic T lymphocyte (CTL), respectively. The CTL epitope also showed a strong and stable interaction with the MHC class I and class II molecules, reported to be found in fish. Therefore, the present epitope could be used as a potential vaccine candidate against WSSV

In silico CD4+, CD8+ T-cell and B-cell immunity associated immunogenic epitope prediction and HLA distribution analysis of Zika virus

Zika virus (ZIKV) is a mosquito-borne flavivirus distributed all over Africa, South America and Asia. The infection with the virus may cause acute febrile sickness that clinically resembles dengue fever, yet there is no vaccine, no satisfactory treatment, and no means of evaluating the risk of the disease or prognosis in the infected people. In the present study, the efficacy of the host\u27s immune response in reducing the risk of infectious diseases was taken into account to carry out immuno-informatics driven epitope screening strategy of vaccine candidates against ZIKV. In this study, HLA distribution analysis was done to ensure the coverage of the vast majority of the population. Systematic screening of effective dominant immunogens was done with the help of Immune Epitope & ABCPred databases. The outcomes suggested that the predicted epitopes may be protective immunogens with highly conserved sequences and bear potential to induce both protective neutralizing antibodies, T & B cell responses. A total of 25 CD4+ and 16 CD8+ peptides were screened for T-cell mediated immunity. The predicted epitope TGLDFSDLYYLTMNNKHWLV was selected as a highly immunogenic epitope for humoral immunity. These peptides were further screened as non-toxic, immunogenic and non-mutated residues of envelop viral protein. The predicted epitope could work as suitable candidate(s) for peptide based vaccine development. Further, experimental validation of these epitopes is warranted to ensure the potential of B- and T-cells stimulation for their efficient use as vaccine candidates, and as diagnostic agents against ZIKV

An immunoinformatic approach to design a novel vaccine against the human respiratory syncytial virus (hRSV) by targeting M2-1 protein

Background: Human respiratory syncytial virus (hRSV) is the leading cause of upper and lower respiratory infection in infants, adults and immunocompromised persons. The matrix protein, M2-1 of hRSV is a cofactor of viral RNA polymerase that plays a crucial role during replication. This programmed study was designed to scrutinize potential immunogens from the M2-1 protein characterized from four different continents.Methods: Sequence data obtained from NCBI databases were analysed by using a series of web and software based bioinformatics tools to find out the best epitope against hRSV.Results: The phylogenetic data revealed a homogenized clustering of M2-1 protein for the African, European, and Asian clades while proteins from North American collections found to have a significant evolutionary detachment compared to three other clusters. Using various web-based bioinformatics tools, the study identified four common B-cell epitopes present in all the M2-1 proteins from four different clusters with higher antigenicity and conservancy. Among the 17 M2-1 protein investigated for T-cell epitopes, “VLQNLDVGL” peptide from A2 super-type, and “QSACVAMSK” and “CLNGRRCHY” from A3 super-type showed the highest antigenicity at >0.80 conservancy cut-off value. After evaluation of all antigenic properties, only “CLNGRRCHY” peptide qualified as a potential vaccine candidate against hRSV. Molecular docking revealed strong and stable binding of the epitope to major histocompatibility complexes (MHC) molecules in terms of hydrogen bonding.Conclusion: The designed epitope could be used as a possible vaccine candidate against hRSV.Keywords: hRSV; M2-1 protein; phylogenetic cluster; BCL and CTL epitopes; molecular dockin

Immunoinformatics Patterns and Characteristic of Epitope-Based Peptide Vaccine candidates against COVID-19

Vaccination as defined by the WHO is “the administration of agent-specific, but safe, antigenic components that in vaccinated individuals can induce protective immunity against the corresponding infectious agent”. Regardless of their debated history, the standard vaccine approaches have been unsuccessful in providing vaccines for numerous infectious organisms. In the recent three decades, an enormous amount of immunological data was retrieved from clinical studies  due to the advancement in human genome sequencing. These data are being deposited in databases and numerous scientific literature. The development of several bioinformatics tools to analyze this rapidly increasing immunological databank has given rise to the field of immunoinformatics. This approach allows the selection of immunogenic residues from the pathogen genomes. The ideal residues could be industrialized as vaccine candidates to provide protective immune responses in the hosts. This methodology will significantly decrease the time and cost needed for the vaccine development.  This review focus on  published articles that proposed as vaccine candidates through immunoinformatics analysis. The reviewed  Published immunoinformatics studies provided vaccine peptide candidates against SARS-COV-2, which is based on functional and non functional immunogenic proteins like open reading frame , spike protein, envelope protein and membranous protein .All of which  are designed by unique strategies like reverse vaccinology . Spike protein was the most common used target with different suggeststed B and T cell peptides  due to the difference in methodology between the findings

A candidate multi-epitope vaccine against SARS-CoV-2

In the past two decades, 7 coronaviruses have infected the human population, with two major outbreaks caused by SARS-CoV and MERS-CoV in the year 2002 and 2012, respectively. Currently, the entire world is facing a pandemic of another coronavirus, SARS-CoV-2, with a high fatality rate. The spike glycoprotein of SARS-CoV-2 mediates entry of virus into the host cell and is one of the most important antigenic determinants, making it a potential candidate for a vaccine. In this study, we have computationally designed a multi-epitope vaccine using spike glycoprotein of SARS-CoV-2. The overall quality of the candidate vaccine was validated in silico and Molecular Dynamics Simulation confirmed the stability of the designed vaccine. Docking studies revealed stable interactions of the vaccine with Toll-Like Receptors and MHC Receptors. The in silico cloning and codon optimization supported the proficient expression of the designed vaccine in E. coli expression system. The efficiency of the candidate vaccine to trigger an effective immune response was assessed by an in silico immune simulation. The computational analyses suggest that the designed multi-epitope vaccine is structurally stable which can induce specific immune responses and thus, can be a potential vaccine candidate against SARS-CoV-2.The authors thank Dr. Joseph V.G., Chancellor Garden City University for his constant support to carry out this research work. FC acknowledges partial support from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 853989 (Project ERA4TB). This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation program and EFPIA and Global Alliance for TBDrug Development non profit organization Bill & D.M.Melinda Gates Foundation and University of Dundee. D.M.M was supported by a grant from NIH, R35 GM131731

Immunobioinformatics analysis and phylogenetic tree construction of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Indonesia: spike glycoprotein gene

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), has spread worldwide and as a result, the World Health Organization (WHO) declared it a pandemic. At present, there are no approved vaccines against SARS-CoV-2. Therefore, the aim of this study was to predict epitope-based vaccines using bioinformatics approaches and phylogenetic tree construction of SARS-CoV-2 against the backdrop of the COVID-19 pandemic. In this study, we employed 27 isolates of SARS-CoV-2 spike glycoprotein genes retrieved from GenBank® (National Center for Biotechnology Information, USA) and the GISAID EpiCoV™ Database (Germany). We analyzed the candidate epitopes using the Immune Epitope Database and Analysis Resource. Furthermore, we performed a protective antigen prediction with VaxiJen 2.0. Data for B-cell epitope prediction, protective antigen prediction, and the underlying phylogenetic tree of SARS-CoV-2 were obtained in this research. Therefore, these data could be used to design an epitope-based vaccine against SARS-CoV-2. However, the advanced study is recommended for confirmation (in vitro and in vivo)