Computer aided epitope design as a peptide vaccine component against Lassa virus

An Integrated Approach to Develop a Potent Vaccine Candidate Construct Against Prostate Cancer by Utilizing Machine Learning and Bioinformatics

BACKGROUND

Prostate cancer is the most common malignancy among males. Prostaglandin G/H synthase (PGHS) is an essential enzyme in the synthesis of prostaglandins, and its activation has been linked to many malignancies, including colorectal cancer.

AIMS

Due to the limited effectiveness and specificity of existing prostate cancer therapies, this study was designed to formulate improved treatment techniques.

METHODS

Several immunoinformatic, reverse vaccinology, and molecular modeling methodologies were used to discover B- and T-cell epitopes for the glioblastoma multiforme tumor PGH2_HUMAN. This research evaluated Prostaglandin G/H synthase 2 protein as a potential vaccine candidate against the malignancy. The multi-epitope vaccine architecture is engineered to activate the immune system, with each epitope docked to its respective HLAs. Further, MD simulations analysis was performed to validate the findings.

RESULTS

A multi-epitope subunit vaccine candidate was developed by concatenating the chosen B- and T-cell epitopes. Results yield a codon adaptive index (CAI) of 0.93 and a GC content of 56.77%. Thus, it conforms to a biological requirement for effective protein expression, suggesting competent vaccine efficacy inside the Escherichia coli system. Significant interleukin and cytokine responses were seen, characterized by elevated levels of IL-2 and IFN-γ in the immune system's response to the immunization. Molecular docking demonstrated an efficient binding affinity of -278 kcal/mol, with hydrogen bonding to several residues. Furthermore, the system total root mean square deviation (RMSD) reached 3.23 Å, with a maximum of up to 5.0 Å at the 100 ns time point but remains stable till 400 ns time intervals followed by stable root mean square fluctuation (RMSF) and radius of gyration values. The hydrogen bond cloud residues are the critical sites that significantly influence the binding energies of MMPBSA and MMGBSA via substantial van der Waals interactions.

CONCLUSION

It has been determined that these in silico analyses will further augment the comprehension necessary for advancing the creation of targeted therapies for chemotherapeutic cancer treatments.

Targeting Polyprotein to Design Potential Multiepitope Vaccine against Omsk Hemorrhagic Fever Virus (OHFV) by Evaluating Allergenicity, Antigenicity, and Toxicity Using Immunoinformatic Approaches

Omsk Hemorrhagic Fever Virus (OHFV) is an RNA virus with a single-stranded, positive-sense genome. It is classified under the Flaviviridae family. The genome of this virus is 98% similar to the Alkhurma hemorrhagic fever virus (AHFV), which belongs to the same family. Cases of the virus have been reported in various regions of Saudi Arabia. Both OHFV and AHFV have similarities in pathogenic polyprotein targets. No effective and licensed vaccines are available to manage OHFV infections. Therefore, an effective and safe vaccine is required that can activate protective immunity against OHFV. The current study aimed to design a multiepitope subunit vaccine against the OHFV utilizing several immunoinformatic tools. The polyprotein of OHFV was selected and potent antigenic, non-allergenic, and nontoxic cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and linear B-lymphocyte (LBL) epitopes were chosen. After screening, eight (8) CTL, five (5) HTL, and six (6) B cell epitopes were joined with each other using different linkers. Adjuvant human beta defensin-2 was also linked to the epitopes to increase vaccine antigenic and immunogenic efficiency. The designed vaccine was docked with Toll-like receptor 4 (TLR4) as it activates and induces primary and secondary immune responses against OHFV. Codon optimization was carried out, which resulted in a CAI value of 0.99 and 53.4% GC contents. In addition, the construct was blindly docked to the TLR4 immune receptor and subjected to conformational dynamics simulation analysis to interpret the intricate affinity and comprehend the time-dependent behavior. Moreover, it was predicted that immune responses to the developed vaccine construct reported formation of strong humoral and cellular immune cells. Therefore, the proposed vaccine may be considered in experimental assays to combat OHFV infections. Laboratory experiments for the above predictions are essential in order to evaluate the effectiveness, safety, and protective properties of the subject in question.

Identification, screening and taste mechanisms analysis of two novel umami pentapeptides derived from the myosin heavy chain of Atlantic cod (Gadus morhua)

Umami peptides are new ingredients for the condiment and seasoning industries, with healthy and nutrition characteristics, some of which were identified from aquatic proteins. This study aims to further explore novel umami peptides from Atlantic cod (Gadus morhua) by combining in silico, nano-HPLC-MS/MS, sensory evaluation, and electronic tongue analysis. Two novel peptides, Leu-Val-Asp-Lys-Leu (LVDKL) and Glu-Ser-Lys-Ile-Leu (ESKIL), from the myosin heavy chain of Atlantic cod (Gadus morhua), were screened and confirmed to have strong umami tastes with the thresholds of 0.427 mM and 0.574 mM, respectively. The molecular docking was adopted to explore the interactions between the umami peptides and the umami taste receptor T1R1/T1R3, which showed that the umami peptides interacted with T1R1/T1R3 mainly by electrostatic interaction, hydrogen bond interaction, and hydrophobic interaction. Furthermore, the physicochemical properties of the peptides were investigated by in silico methods and cell viability experiments. This study will provide a better understanding of the umami taste in Atlantic cod and will promote the development of condiments and seasonings.

Development and evaluation of a multi-epitope subunit vaccine against Mycoplasma synoviae infection

Mycoplasma synoviae is an extremely significant avian pathogen, causing substantial financial harm to poultry farmers worldwide, and impacting both chicken and turkey production. Multi-epitope vaccines offer higher immunity and lower allergenicity compared to conventional vaccines. In this study, our objective is to develop a multi-epitope vaccine for M. synoviae (MSMV) and to evaluate the immune responses and protective efficacy of MSMV in chickens. We successfully identified a total of 14 B-cell, 5 MHC-I, and 16 MHC-II binding epitopes from the immunodominant proteins RS01790, BMP, GrpE, RS00900, and RS00275. Subsequently, we synthesized the multi-epitope vaccine by connecting all conserved epitopes using appropriate linkers. The resulting MSMV demonstrated notable antigenicity, non-allergenic properties, and stability. Notably, the MSMV effectively stimulated high levels of antibody production in chickens. Furthermore, MSMV the vaccine elicited a robust cellular immune response in chickens, characterized by a well-balanced Th1/Th2-type cytokine profile and enhanced lymphocyte proliferation. In immune protection experiments, the vaccinated chickens exhibited reduced air sac lesion scores and tracheal mucosal thickness compared to their non-vaccinated chickens. Additionally, vaccinated chickens displayed lower M. synoviae loads in throat swabs. These findings collectively suggested that the MSMV holds significant potential as a promising vaccine candidate for managing M. synoviae infections.

Bioinformatics design of recombinant chimeric protein containing SipD and LptD immunogens and evaluation of its immunogenicity against Salmonella Typhimurium

The growing emergence of resistant bacteria is the current global concern for the humans and animals. Vaccination could be the desirable method to preventing such infectious diseases. Safe and effective vaccines are urgently needed to manage and prevent Salmonella contamination. Subunit vaccines are safe approaches for the protection against Salmonella spp. The bioinformatics methods were performed to determine the gene structure. Gene cassette (rLPSI) was ordered in pET28a (+), and cloned into E.coli BL21 (DE3), and the recombinant protein was expressed using IPTG (1 mM). Mice were immunized by subcutaneous administration of recombinant protein. Then, the mice were challenged by oral administration of 100LD₅₀ of live S. Typhimurium. The Codon adaptation index of the chimeric gene was multiplied by 0.92. Validation results showed that >90% of residues lie in the desired or extra allowed area of the Ramachandran plot. The recombinant protein (65.9 kDa) was expressed in E.coli. Antibody titers in vaccinated mice were significantly different from those in the control groups. Recombinant protein immunization of the mice provided 90% and 70% protection against 10LD₅₀ and 100LD₅₀ of S. Typhimurium, respectively. In general, the results showed the high efficiency of rLPSI chimeric protein as a protective antigen against S. Typhimurium infection. The rLPSI chimeric protein could be an effective recombinant vaccine candidate against S. Typhimurium infection, but more research is needed.

Exploratory Algorithm of a Multi-epitope-based Subunit Vaccine Candidate Against Cryptosporidium hominis: Reverse Vaccinology-Based Immunoinformatic Approach

Cryptosporidiosis is the leading protozoan-induced cause of diarrheal illness in children, and it has been linked to childhood mortality, malnutrition, cognitive development, with retardation of growth. Cryptosporidium hominis, the anthroponotically transmitted species within the Cryptosporidium genus, contributes significantly to the global burden of infection, accounting for the majority of clinical cases in numerous nations, as well as its emergence in the last decade is largely due to detections obtained through noteworthy epidemiologic research. Nevertheless, there is no vaccine available, and the only licensed medication, nitazoxanide, has been demonstrated to have efficacy limitations in a number of patient groups recognized to be at high risk of complications. Therefore, current study delineates the computational vaccine design for Cryptosporidium hominis, the notable pathogen for enteric diarrhea. Firstly, a comprehensive literature search was conducted to identify six proteins based on their toxigenicity, allergenicity, antigenicity, and prediction of transmembrane helices to make up a multi-epitope-based subunit vaccine. Following that, antigenic non-toxic HTL epitope, CTL epitope with B cell epitope were predicted from the selected proteins and construct a vaccine candidate with adding an adjuvant and some linkers with immunologically superior epitopes. Afterwards, the constructed vaccine candidates and TLR2 receptor were put into the ClusPro server for molecular dynamic simulation to know the binding stability of the vaccine-TLR2 complex. Following that, Escherichia coli strain K12 was used as a cloning host for the chosen vaccine construct via the JCat server. As a result of the findings, it was resolute that the proposed chimeric peptide vaccine could improve the immune response to Cryptosporidium hominis.

Execution and Design of an Anti HPIV-1 Vaccine with Multiple Epitopes Triggering Innate and Adaptive Immune Responses: An Immunoinformatic Approach

Human Parainfluenza Virus (HPIV) Type-1, which is an anti-sense ribonucleic acid (RNA) virus belonging to the paramyxoviridae family, induces upper and lower respiratory tract infections. The infections caused by the HPIV Type-1 virus are usually confined to northwestern regions of America. HPIV-1 causes infections through the virulence of the hemagglutinin-neuraminidase (HN) protein, which plays a key role in the attachment of the viral particle with the host’s receptor cells. To the best of our knowledge, there is no effective antiviral drugs or vaccines being developed to combat the infection caused by HPIV-1. In the current study, a multiple epitope-based vaccine was designed against HPIV-1 by taking the viral HN protein as a probable vaccine candidate. The multiple epitopes were selected in accordance with their allergenicity, antigenicity and toxicity scoring. The determined epitopes of the HN protein were connected simultaneously using specific conjugates along with an adjuvant to construct the subunit vaccine, with an antigenicity score of 0.6406. The constructed vaccine model was docked with various Toll-like Receptors (TLRs) and was computationally cloned in a pET28a (+) vector to analyze the expression of vaccine sequence in the biological system. Immune stimulations carried out by the C-ImmSim Server showed an excellent result of the body’s defense system against the constructed vaccine model. The AllerTop tool predicted that the construct was non-allergen with and without the adjuvant sequence, and the VaxiJen 2.0 with 0.4 threshold predicted that the construct was antigenic, while the Toxinpred predicted that the construct was non-toxic. Protparam results showed that the selected protein was stable with 36.48 instability index (II) scores. The Grand average of Hydropathicity or GRAVY score indicated that the constructed protein was hydrophilic in nature. Aliphatic index values (93.53) confirmed that the construct was thermostable. This integrated computational approach shows that the constructed vaccine model has a potential to combat laryngotracheobronchitis infections caused by HPIV-I.

Strategy to Configure Multi-epitope Recombinant Immunogens with Weightage on Proinflamatory Response using SARS-CoV-2 Spike Glycoprotein (S-protein) and RNA-dependent RNA Polymerase (RdRp) as Model Targets

Development of a suitable recombinant peptide vaccine against pathogens requires designing of effective immunogenic polypeptide taking various aspects and complexity of immune-response into consideration. Implementing SARS-CoV-2 spike glycoprotein (S-protein) and RNA-dependent RNA polymerase (RdRp) as model targets, in this study, we outline and assess a strategy for in silico recombinant vaccine designing. After mapping the linear B-cell epitopes and MHC1-binding T-cell epitopes six epitopes were sorted from each of the proteins on the basis of extent of residue-conservancy among three types of coronaviruses namely SARS-CoV-2, SARS-CoV and MERS-CoV. Each of the selected epitopes were profiled for their pro-inflammatory potential through molecular docking analysis with surface bound Toll-like receptors, namely TLR2, TLR4 and TLR5. Based on a custom scoring function, the epitopes were ranked for highest and least pro-inflammatory potential. Segments of Spike and RdRp harboring such epitopes were combined using linkers to design immunogenic recombinant polypeptide. Antigenicity and allergenicity of each of the combination was scored; and the best fitting one was docked against TLR2, TLR4 and TLR5 for assessing pro-inflammatory potential. Codon optimization and in silico cloning in expression vector indicated that the designed peptide can be satisfactorily expressed in bacteria, reinforcing the viability of the strategy in identification and designing of potential immunogens.

Prediction and evaluation of multi epitope based sub-unit vaccine against Salmonella typhimurium

Salmonella enteric serovar Typhimurium is the most common enteric pathogen in humans and animals. Consumption of contaminated food or water triggers inflammation that allows Salmonella to spread into the gut and causes gastrointestinal diseases. The infection spreads by intestinal invasion, phagocyte internalization and subsequent dissemination in many other patients. This research used TolA, a Salmonella typhimurium membrane protein, to computationally design a multi-epitope vaccine against the pathogen. Complete consistency of the candidate vaccine was checked In silico, and molecular dynamics simulations confirmed the vaccine's stability. According to docking report, the vaccine has a good affinity with toll-like receptors. In silico cloning and codon optimization techniques improved the vaccine's efficacy in Salmonella typhimurium manifestation process. The candidate vaccine induced an efficient immune response, as determined by In silico immune simulation. Computational studies revealed that the engineered multi-epitope vaccine is structurally stable, capable of eliciting particular immunological reactions, and therefore a candidate for a latent Salmonella typhimurium vaccine. However, wet lab studies and further investigations are required to confirm the results.

In silico designing of vaccine candidate against Clostridium difficile

Clostridium difficile is a spore-forming gram-positive bacterium, recognized as the primary cause of antibiotic-associated nosocomial diarrhoea. Clostridium difficile infection (CDI) has emerged as a major health-associated infection with increased incidence and hospitalization over the years with high mortality rates. Contamination and infection occur after ingestion of vegetative spores, which germinate in the gastro-intestinal tract. The surface layer protein and flagellar proteins are responsible for the bacterial colonization while the spore coat protein, is associated with spore colonization. Both these factors are the main concern of the recurrence of CDI in hospitalized patients. In this study, the CotE, SlpA and FliC proteins are chosen to form a multivalent, multi-epitopic, chimeric vaccine candidate using the immunoinformatics approach. The overall reliability of the candidate vaccine was validated in silico and the molecular dynamics simulation verified the stability of the vaccine designed. Docking studies showed stable vaccine interactions with Toll‐Like Receptors of innate immune cells and MHC receptors. In silico codon optimization of the vaccine and its insertion in the cloning vector indicates a competent expression of the modelled vaccine in E. coli expression system. An in silico immune simulation system evaluated the effectiveness of the candidate vaccine to trigger a protective immune response.

Exploring SARS-COV-2 structural proteins to design a multi-epitope vaccine using immunoinformatics approach: An in silico study

In December 2019, a new virus called SARS-CoV-2 was reported in China and quickly spread to other parts of the world. The development of SARS-COV-2 vaccines has recently received much attention from numerous researchers. The present study aims to design an effective multi-epitope vaccine against SARS-COV-2 using the reverse vaccinology method. In this regard, structural proteins from SARS-COV-2, including the spike (S), envelope (E), membrane (M), and nucleocapsid (N) proteins, were selected as target antigens for epitope prediction. A total of five helper T lymphocytes (HTL) and five cytotoxic T lymphocytes (CTL) epitopes were selected after screening the predicted epitopes for antigenicity, allergenicity, and toxicity. Subsequently, the selected HTL and CTL epitopes were fused via flexible linkers. Next, the cholera toxin B-subunit (CTxB) as an adjuvant was linked to the N-terminal of the chimeric structure. The proposed vaccine was analyzed for the properties of physicochemical, antigenicity, and allergenicity. The 3D model of the vaccine construct was predicted and docked with the Toll-like receptor 4 (TLR4). The molecular dynamics (MD) simulation was performed to evaluate the stable interactions between the vaccine construct and TLR4. The immune simulation was also conducted to explore the immune responses induced by the vaccine. Finally, in silico cloning of the vaccine construct into the pET-28 (+) vector was conducted. The results obtained from all bioinformatics analysis stages were satisfactory; however, in vitro and in vivo tests are essential to validate these results.

Molecular Dynamic Simulation Search for Possible Amphiphilic Drug Discovery for Covid-19

To determine whether quaternary ammonium (k21) binds to Severe Acute Respiratory Syndrome–Coronavirus 2 (SARS-CoV-2) spike protein via computational molecular docking simulations, the crystal structure of the SARS-CoV-2 spike receptor-binding domain complexed with ACE-2 (PDB ID: 6LZG) was downloaded from RCSB PD and prepared using Schrodinger 2019-4. The entry of SARS-CoV-2 inside humans is through lung tissues with a pH of 7.38–7.42. A two-dimensional structure of k-21 was drawn using the 2D-sketcher of Maestro 12.2 and trimmed of C18 alkyl chains from all four arms with the assumption that the core moiety k-21 was without C18. The immunogenic potential of k21/QA was conducted using the C-ImmSim server for a position-specific scoring matrix analyzing the human host immune system response. Therapeutic probability was shown using prediction models with negative and positive control drugs. Negative scores show that the binding of a quaternary ammonium compound with the spike protein’s binding site is favorable. The drug molecule has a large Root Mean Square Deviation fluctuation due to the less complex geometry of the drug molecule, which is suggestive of a profound impact on the regular geometry of a viral protein. There is high concentration of Immunoglobulin M/Immunoglobulin G, which is concomitant of virus reduction. The proposed drug formulation based on quaternary ammonium to characterize affinity to the SARS-CoV-2 spike protein using simulation and computational immunological methods has shown promising findings.

Towards a novel peptide vaccine for Middle East respiratory syndrome coronavirus and its possible use against pandemic COVID-19

Middle East respiratory syndrome coronavirus (MERS-CoV) is an emerging health concern due to its high mortality rate of 35%. At present, no vaccine is available to protect against MERS-CoV infections. Therefore, an in silico search for potential antigenic epitopes in the non-redundant proteome of MERS-CoV was performed herein. First, a subtractive proteome-based approach was employed to look for the surface exposed and host non-homologous proteins. Following, immunoinformatics analysis was performed to predict antigenic B and T cell epitopes that were used in the design of a multi-epitopes peptide. Molecular docking study was carried out to predict vaccine construct affinity of binding to Toll-like receptor 3 (TLR3) and understand its binding conformation to extract ideas about its processing by the host immune system. We identified membrane protein, envelope small membrane protein, non-structural protein ORF3, non-structural protein ORF5, and spike glycoprotein as potential candidates for subunit vaccine designing. The designed multi-epitope peptide then linked to β-defensin adjuvant is showing high antigenicity. Further, the sequence of the designed vaccine construct is optimized for maximum expression in the Escherichia coli expression system. A rich pattern of hydrogen and hydrophobic interactions of the construct was observed with the TLR3 allowing stable binding of the construct at the docked site as predicted by the molecular dynamics simulation and MM-PBSA binding energies. We expect that the panel of subunit vaccine candidates and the designed vaccine construct could be highly effective in immunizing populations from infections caused by MERS-CoV and could possible applied on the current pandemic COVID-19.

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.

In-silico identification of the vaccine candidate epitopes against the Lassa virus hemorrhagic fever

Lassa virus (LASV), a member of the Arenaviridae, is an ambisense RNA virus that causes severe hemorrhagic fever with a high fatality rate in humans in West and Central Africa. Currently, no FDA approved drugs or vaccines are available for the treatment of LASV fever. The LASV glycoprotein complex (GP) is a promising target for vaccine or drug development. It is situated on the virion envelope and plays key roles in LASV growth, cell tropism, host range, and pathogenicity. In an effort to discover new LASV vaccines, we employ several sequence-based computational prediction tools to identify LASV GP major histocompatibility complex (MHC) class I and II T-cell epitopes. In addition, many sequence- and structure-based computational prediction tools were used to identify LASV GP B-cell epitopes. The predicted T- and B-cell epitopes were further filtered based on the consensus approach that resulted in the identification of thirty new epitopes that have not been previously tested experimentally. Epitope-allele complexes were obtained for selected strongly binding alleles to the MHC-I T-cell epitopes using molecular docking and the complexes were relaxed with molecular dynamics simulations to investigate the interaction and dynamics of the epitope-allele complexes. These predictions provide guidance to the experimental investigations and validation of the epitopes with the potential for stimulating T-cell responses and B-cell antibodies against LASV and allow the design and development of LASV vaccines.

Inter-Lineage Variation of Lassa Virus Glycoprotein Epitopes: A Challenge to Lassa Virus Vaccine Development

Lassa virus (LASV), which causes considerable morbidity and mortality annually, has a high genetic diversity across West Africa. LASV glycoprotein (GP) expresses this diversity, but most LASV vaccine candidates utilize only the Lineage IV LASV Josiah strain GP antigen as an immunogen and homologous challenge with Lineage IV LASV. In addition to the sequence variation amongst the LASV lineages, these lineages are also distinguished in their presentations. Inter-lineage variations within previously mapped B-cell and T-cell LASV GP epitopes and the breadth of protection in LASV vaccine/challenge studies were examined critically. Multiple alignments of the GP primary sequence of strains from each LASV lineage showed that LASV GP has diverging degrees of amino acid conservation within known epitopes among LASV lineages. Conformational B-cell epitopes spanning different sites in GP subunits were less impacted by LASV diversity. LASV GP diversity should influence the approach used for LASV vaccine design. Expression of LASV GP on viral vectors, especially in its prefusion configuration, has shown potential for protective LASV vaccines that can overcome LASV diversity. Advanced vaccine candidates should demonstrate efficacy against all LASV lineages for evidence of a pan-LASV vaccine.

Immunoinformatics and Vaccine Development: An Overview

The use of vaccines have resulted in a remarkable improvement in global health. It has saved several lives, reduced treatment costs and raised the quality of animal and human lives. Current traditional vaccines came empirically with either vague or completely no knowledge of how they modulate our immune system. Even at the face of potential vaccine design advance, immune-related concerns (as seen with specific vulnerable populations, cases of emerging/re-emerging infectious disease, pathogens with complex lifecycle and antigenic variability, need for personalized vaccinations, and concerns for vaccines' immunological safety -specifically vaccine likelihood to trigger non-antigen-specific responses that may cause autoimmunity and vaccine allergy) are being raised. And these concerns have driven immunologists toward research for a better approach to vaccine design that will consider these challenges. Currently, immunoinformatics has paved the way for a better understanding of some infectious disease pathogenesis, diagnosis, immune system response and computational vaccinology. The importance of this immunoinformatics in the study of infectious diseases is diverse in terms of computational approaches used, but is united by common qualities related to host–pathogen relationship. Bioinformatics methods are also used to assign functions to uncharacterized genes which can be targeted as a candidate in vaccine design and can be a better approach toward the inclusion of women that are pregnant into vaccine trials and programs. The essence of this review is to give insight into the need to focus on novel computational, experimental and computation-driven experimental approaches for studying of host–pathogen interactions and thus making a case for its use in vaccine development.

Exploring Lassa Virus Proteome to Design a Multi-epitope Vaccine Through Immunoinformatics and Immune Simulation Analyses

Lassa virus (LASV) is responsible for a type of acute viral haemorrhagic fever referred to as Lassa fever. Lack of adequate treatment and preventive measures against LASV resulted in a high mortality rate in its endemic regions. In this study, a multi-epitope vaccine was designed using immunoinformatics as a prophylactic agent against the virus. Following a rigorous assessment, the vaccine was built using T-cell (N_CTL = 8 and N_HTL = 6) and B-cell (N_LBL = 4) epitopes from each LASV-derived protein in addition with suitable linkers and adjuvant. The physicochemistry, immunogenic potency and safeness of the designed vaccine (~ 68 kDa) were assessed. In addition, chosen CTL and HTL epitopes of our vaccine showed 97.37% worldwide population coverage. Besides, disulphide engineering also improved the stability of the chimeric vaccine. Molecular docking of our vaccine protein with toll-like receptor 2 (TLR2) showed binding efficiency followed by dynamics simulation for stable interaction. Furthermore, higher levels of cell-mediated immunity and rapid antigen clearance were suggested by immune simulation and repeated-exposure simulation, respectively. Finally, the optimized codons were used in in silico cloning to ensure higher expression within E. coli K12 bacterium. With further assessment both in vitro and in vivo, we believe that our proposed peptide-vaccine would be potential immunogen against Lassa fever.

Designing a multi-epitope based vaccine to combat Kaposi Sarcoma utilizing immunoinformatics approach

Kaposi's sarcoma-associated herpesvirus (KSHV) responsible for causing Kaposi sarcoma (KS), an opportunistic angioproliferative neoplasm is emerging rapidly. Despite this there is no permanent cure for this disease. The present study was aimed to design a multi-epitope based vaccine targeting the major glycoproteins of KSHV which plays an important role in the virus entry. After the application of rigorous immunoinformatics analysis and several immune filters, the multi-epitope vaccine was constructed, consisting of CD4, CD8 and IFN-γ inducing epitopes. Several physiochemical characteristics, allergenicity and antigenicity of the multi-epitope vaccine were analyzed in order to ensure its safety and immunogenicity. Further, the binding affinity and stability of the vaccine with Toll like receptor -9 (TLR-9) was analyzed by molecular docking and dynamics simulation studies. In addition, an in silico cloning was performed to ensure the expression and translation efficiency of the vaccine, utilizing pET-28a (+) vector. Such T-cell-based immunotherapies which leverage this mechanism could prove their potential against cancer. Further, the authors propose to test the present findings in the lab settings to ensure the safety, immunogenicity and efficacy of the presented vaccine which may help in controlling KSHV infection.