A multi-subunit based, thermodynamically stable model vaccine using combined immunoinformatics and protein structure based approach

Design and computational evaluation of a novel multi-epitope hybrid vaccine against monkeypox virus: Potential targets and immunogenicity assessment for pandemic preparedness

Monkeypox is a type of DNA-enveloped virus that belongs to the orthopoxvirus family, closely related to the smallpox virus. It can cause an infectious disease in humans known as monkeypox disease. Although there are multiple drugs and vaccines designed to combat orthopoxvirus infections, with a primary focus on smallpox, the recent spread of the monkeypox virus to over 50 countries have ignited a mounting global concern. This unchecked viral proliferation has raised apprehensions about the potential for a pandemic corresponding to the catastrophic impact of COVID-19. This investigation explored the structural proteins of monkeypox virus as potential candidates for designing a novel hybrid multi-epitope vaccine. The epitopes obtained from the selected proteins were screened to ensure their non-allergenicity, non-toxicity, and antigenicity to trigger T and B-cell responses. The interaction of the vaccine with toll-like receptor-3 (TLR-3) and major histocompatibility complexes (MHCs) was assessed using Cluspro 2.0. To establish the reliability of the docked complexes, a comprehensive evaluation was conducted using Immune and MD Simulations and Normal Mode Analysis. However, to validate the computational results of this study, additional in-vitro and in-vivo research is essential.

An Immunoinformatics-Based Study of Mycobacterium tuberculosis Region of Difference-2 Uncharacterized Protein (Rv1987) as a Potential Subunit Vaccine Candidate for Preliminary Ex Vivo Analysis

Mycobacterium tuberculosis (Mtb) is the pathogen that causes tuberculosis and develops resistance to many of the existing drugs. The sole licensed TB vaccine, BCG, is unable to provide a comprehensive defense. So, it is crucial to maintain the immunological response to eliminate tuberculosis. Our previous in silico study reported five uncharacterized proteins as potential vaccine antigens. In this article, we considered the uncharacterized Mtb H37Rv regions of difference (RD-2) Rv1987 protein as a promising vaccine candidate. The vaccine quality of the protein was analyzed using reverse vaccinology and immunoinformatics-based quality-checking parameters followed by an ex vivo preliminary investigation. In silico analysis of Rv1987 protein predicted it as surface localized, secretory, single helix, antigenic, non-allergenic, and non-homologous to the host protein. Immunoinformatics analysis of Rv1987 by CD4 + and CD8 + T-cells via MHC-I and MHC-II binding affinity and presence of B-cell epitope predicted its immunogenicity. The docked complex analysis of the 3D model structure of the protein with immune cell receptor TLR-4 revealed the protein's capability for potential interaction. Furthermore, the target protein-encoded gene Rv1987 was cloned, over-expressed, purified, and analyzed by mass spectrometry (MS) to report the target peptides. The qRT-PCR gene expression analysis shows that it is capable of activating macrophages and significantly increasing the production of a number of key cytokines (TNF-α, IL-1β, and IL-10). Our in-silico analysis and ex vivo preliminary investigations revealed the immunogenic potential of the target protein. These findings suggest that the Rv1987 be undertaken as a potent subunit vaccine antigen and that further animal model immuno-modulation studies would boost the novel TB vaccine discovery and/or BCG vaccine supplement pipeline.

Immunoinformatics design of novel multi-epitope vaccine against Trueperella Pyogenes using collagen adhesion protein, fimbriae, and pyolysin

Trueperella pyogenes (T. pyogenes) is an opportunistic pathogen that causes infertility, mastitis, and metritis in animals. T. pyogenes is also a zoonotic disease and is considered an economic loss agent in the livestock industry. Therefore, vaccine development is necessary. Using an immunoinformatics approach, this study aimed to construct a multi-epitope vaccine against T. pyogenes. The collagen adhesion protein, fimbriae, and pyolysin (PLO) sequences were initially retrieved. The HTL, CTL, and B cell epitopes were predicted. The vaccine was designed by binding these epitopes with linkers. To increase vaccine immunogenicity, profilin was added to the N-terminal of the vaccine construct. The antigenic features and safety of the vaccine model were investigated. Docking, molecular dynamics simulation of the vaccine with immune receptors, and immunological simulation were used to evaluate the vaccine's efficacy. The vaccine's sequence was then optimized for cloning. The vaccine construct was designed based on 18 epitopes of T. pyogenes. The computational tools validated the vaccine as non-allergenic, non-toxic, hydrophilic, and stable at different temperatures with acceptable antigenic features. The vaccine model had good affinity and stability to bovine TLR2, 4, and 5 as well as stimulation of IgM, IgG, IL-2, IFN-γ, and Th1 responses. This vaccine also increased long-lived memory cells, dendritic cells, and macrophage population. In addition, codon optimization was done and cloned in the E. coli K12 expression vector (pET-28a). For the first time, this study introduced a novel multi-epitope vaccine candidate based on collagen adhesion protein, fimbriae, and PLO of T. pyogenes. It is expected this vaccine stimulates an effective immune response to prevent T. pyogenes infection.

Design and characterization of a multi-epitope vaccine against Clostridium botulinum A3 Loch Maree intoxication in humans

Clostridium botulinum Loch Maree expresses an extremely potent botulinum neurotoxin subtype, A3 causing botulism and several gastrointestinal disorders in mammals. Several recombinant vaccines have been developed for human botulism and no vaccine is currently available for the treatment of diseases caused by other virulence factors. Hence, we designed, constructed, and characterized a multi-epitope vaccine from new virulence proteins identified from this organism using an immunoinformatics approach. The vaccine construct used in this study was designed from 6B cell linear epitopes, 12 cytotoxic T cell lymphocyte epitopes, and 15 helper T cell lymphocyte epitopes, with a defensin adjuvant and adjusting linker sequences. A molecular modeling approach was used to model, refine, and validate the 3D structure of the vaccine construct. Molecular docking studies were performed to determine the stability of the molecular interactions between the vaccine construct and human toll-like receptor 7. The in silico molecular cloning was used to clone a codon-optimized synthetic vaccine gene in pCYB1 vector and expressed in Escherichia coli. The results of this study identified six new virulence proteins: peptidoglycan hydrolase, SCP-like extracellular protein, N-acetylmuramoyl-l-alanine amidase, putative membrane protein, drug/metabolite exporter, and bacillolysin. The top B-cell, cytotoxic T-cell lymphocyte, and helper T-lymphocyte epitopes were predicted from these virulence proteins with greater accuracy and reliability. HLA-A*02:01 and HLA-A*03:01 were identified as HLA-A-binding alleles for cytotoxic T-cell lymphocyte epitopes. DRB1*0110 and DRB1*0115 are the dominant alleles that bind to helper T-cell lymphocyte epitopes. The synthetic gene construct was highly expressed in a heterologous host and produced considerable amounts of antigenic protein. The multi-epitope vaccine is more conservative in the sequence-structure-function link, immunogenic with less allergenicity, and possibly provokes cellular and humoral immunity. The present study suggests that the designed multi-epitope vaccine is a promising prophylactic candidate for the virulence and intoxication caused by subtype A3 strains.

Immunoinformatics-based multi-epitope containing fused polypeptide vaccine design against visceral leishmaniasis with high immunogenicity and TLR binding

Visceral leishmaniasis (VL) is the most lethal among all leishmaniasis diseases and remains categorized as a neglected tropical disease (NTD). This study aimed to develop a peptide-based multi-epitope vaccine construct against VL using immunoinformatics methodologies. To achieve this, four distinct proteins were screened to identify peptides consisting of 9-15 amino acids with high binding affinity to toll-like receptors (TLRs), strong antigenicity, low allergenicity, and minimal toxicity. The resulting multi-epitope vaccine construct was fused in a tandem arrangement with appropriate linker peptides and exhibited superior properties related to cytotoxic T lymphocytes (CTLs), helper T lymphocytes (HTLs), and B-cell epitopes. Subsequently, a three-dimensional (3D) model of the vaccine construct was generated, refined, and validated for structural stability and immune response capabilities. Molecular docking and simulations confirmed the vaccine construct's stability and binding affinities with TLRs, with TLR4 displaying the highest binding affinity, followed by TLR2 and TLR3. Additionally, simulations predicted robust cellular and humoral antibody-mediated immune responses elicited by the designed vaccine construct. Notably, this vaccine construct includes proteins from various pathways of Leishmania donovani (LD), which have not been previously utilized in VL vaccine design. Thus, this study opens new avenues for the development of vaccines against diverse protozoan diseases.

Characterization of exclusively non-commensal Neisseria gonorrhoeae pangenome to prioritize globally conserved and thermodynamically stable vaccine candidates using immune-molecular dynamic simulations

Neisseria gonorrhoeae (Ngo) has emerged as a global threat leading to one of the most common sexually transmitted diseases in the world. It has also become one of the leading antimicrobial resistant organisms, resulting in fewer treatment options and an increased morbidity. Therefore, in recent years, there has been an increased focus on the development of new treatments and preventive strategies to combat its infection. In this study, we have combined the most conserved epitopes from the completely assembled strains of Ngo to develop a universal and a thermodynamically stable vaccine candidate. For our vaccine design, the epitopes were selected for their high immunogenicity, non-allergenicity and non-cytotoxicity, making them the ideal candidates for vaccine development. For the screening process, several reverse vaccinology tools were employed to rigorously extract non-homologous and immunogenic epitopes from the selected proteins. Consequently, a total number of 3 B-cell epitopes and 6 T-cell epitopes were selected and joined by multiple immune-modulating adjuvants and linkers to generate a promiscuous immune response. Additionally, the stability and flexible nature of the vaccine construct was confirmed using various molecular dynamic simulation tools. Overall, the vaccine candidate showed promising binding affinity to various HLA alleles and TLR receptors; however, further studies are needed to assess its efficacy in-vivo. In this way, we have designed a multi-subunit vaccine candidate to potentially combat and control the spread of N. gonorrhoeae.

Proteome level analysis of drug-resistant Prevotella melaninogenica for the identification of novel therapeutic candidates

The management of infectious diseases has become more critical due to the development of novel pathogenic strains with enhanced resistance. Prevotella melaninogenica, a gram-negative bacterium, was found to be involved in various infections of the respiratory tract, aerodigestive tract, and gastrointestinal tract. The need to explore novel drug and vaccine targets against this pathogen was triggered by the emergence of antimicrobial resistance against reported antibiotics to combat P. melaninogenica infections. The study involves core genes acquired from 14 complete P. melaninogenica strain genome sequences, where promiscuous drug and vaccine candidates were explored by state-of-the-art subtractive proteomics and reverse vaccinology approaches. A stringent bioinformatics analysis enlisted 18 targets as novel, essential, and non-homologous to humans and having druggability potential. Moreover, the extracellular and outer membrane proteins were subjected to antigenicity, allergenicity, and physicochemical analysis for the identification of the candidate proteins to design multi-epitope vaccines. Two candidate proteins (ADK95685.1 and ADK97014.1) were selected as the best target for the designing of a vaccine construct. Lead B- and T-cell overlapped epitopes were joined to generate potential chimeric vaccine constructs in combination with adjuvants and linkers. Finally, a prioritized vaccine construct was found to have stable interactions with the human immune cell receptors as confirmed by molecular docking and MD simulation studies. The vaccine construct was found to have cloning and expression ability in the bacterial cloning system. Immune simulation ensured the elicitation of significant immune responses against the designed vaccine. In conclusion, our study reported novel drug and vaccine targets and designed a multi-epitope vaccine against the P. melaninogenica infection. Further experimental validation will help open new avenues in the treatment of this multi-drug-resistant pathogen.

Design and computational analysis of an effective multi-epitope vaccine candidate using subunit B of cholera toxin as a build-in adjuvant against urinary tract infections

Introduction

Urinary tract infection (UTI) is one of the most common infections, usually caused by uropathogenic Escherichia coli (UPEC). However, antibiotics are a usual treatment for UTIs; because of increasing antibiotic-resistant strains, vaccination can be beneficial in controlling UTIs. Using immunoinformatics techniques is an effective and rapid way for vaccine development.

Methods

Three conserved protective antigens (FdeC, Hma, and UpaB) were selected to develop a novel multi-epitope vaccine consisting of subunit B of cholera toxin (CTB) as a mucosal build-in adjuvant to enhance the immune responses. Epitopes-predicted B and T cells and suitable linkers were used to separate them and effectively increase the vaccine's immunogenicity. The vaccine protein's primary, secondary, and tertiary structures were evaluated, and the best 3D model was selected. Since CTB is the TLR2 ligand, molecular docking was made between the vaccine protein and TLR2. Molecular dynamic (MD) simulation was employed to evaluate the stability of the vaccine protein-TLR2 complex. The vaccine construct was subjected to in silico cloning.

Results

The designed vaccine protein has multiple properties in the analysis. The HADDOCK outcomes show an excellent interaction between vaccine protein and TLR2. The MD results confirm the stability of the vaccine protein- TLR2 complex during the simulation. In silico cloning verified the expression efficiency of our vaccine protein.

Conclusion

The results of this study suggest that our designed vaccine protein could be a promising vaccine candidate against UTI, but further in vitro and in vivo studies are needed.

A novel mutation-proof, next-generation vaccine to fight against upcoming SARS-CoV-2 variants and subvariants, designed through AI enabled approaches and tools, along with the machine learning based immune simulation: A vaccine breakthrough

Emerging SARS-CoV-2 variants and subvariants are great concerns for their significant mutations, which are also responsible for vaccine escape. Therefore, the study was undertaken to develop a mutation-proof, next-generation vaccine to protect against all upcoming SARS-CoV-2 variants. We used advanced computational and bioinformatics approaches to develop a multi-epitopic vaccine, especially the AI model for mutation selection and machine learning (ML) strategies for immune simulation. AI-enabled and the top-ranked antigenic selection approaches were used to select nine mutations from 835 RBD mutations. We selected twelve common antigenic B cell and T cell epitopes (CTL and HTL) containing the nine RBD mutations and joined them with the adjuvants, PADRE sequence, and suitable linkers. The constructs' binding affinity was confirmed through docking with TLR4/MD2 complex and showed significant binding free energy (-96.67 kcal mol^-1) with positive binding affinity. Similarly, the calculated eigenvalue (2.428517e-05) from the NMA of the complex reveals proper molecular motion and superior residues' flexibility. Immune simulation shows that the candidate can induce a robust immune response. The designed mutation-proof, multi-epitopic vaccine could be a remarkable candidate for upcoming SARS-CoV-2 variants and subvariants. The study method might guide researchers in developing AI-ML and immunoinformatics-based vaccines for infectious disease.

Immunogenic multi-epitope-based vaccine development to combat cyclosporiasis of immunocompromised patients applying computational biology method

Cyclospora cayetanensis infections, also known as cyclosporiasis, persist to be the prevalent emerging protozoan parasite and an opportunist that causes digestive illness in immunocompromised individuals. In contrast, this causal agent can affect people of all ages, with children and foreigners being the most susceptible populations. For most immunocompetent patients, the disease is self-limiting; in extreme circumstances, this illness can manifest as severe or persistent diarrhea as well as colonize on secondary digestive organs leading to death. According to recent reports, worldwide 3.55% of people are infected by this pathogen, with Asia and Africa being more prevalent. For the treatment, trimethoprim-sulfamethoxazole is the only licensed drug and does not appear to work as well in some patient populations. Therefore, the much more effective strategy to avoid this illness is immunization through the vaccine. This present study uses immunoinformatics for identifying a computational multi-epitope-based peptide vaccine candidate for Cyclospora cayetanensis. Following the review of the literature, a highly efficient, secure, and vaccine complex based on multi-epitopes was designed by utilizing the identified proteins. These selected proteins were then used to predict non-toxic and antigenic HTL-epitopes, B-cell-epitopes, and CTL-epitopes. Ultimately, both a few linkers and an adjuvant were combined to create a vaccine candidate with superior immunological epitopes. Then, to establish the vaccine-TLR complex binding constancy, the TLR receptor and vaccine candidates were placed into the FireDock, PatchDock, and ClusPro servers for molecular docking and iMODS server for molecular-dynamic simulation. Finally, this selected vaccine construct was cloned into Escherichia coli strain-K12; thus, the constructed vaccines against Cyclospora cayetanensiscould improve the host immune response and can be produced experimentally.

Immunoinformatics analysis for design of multi-epitope subunit vaccine by using heat shock proteins against Schistosoma mansoni

The development of T cell and B cell that able provide long-term immune response against the schistosomiasisis to the people belongs to the epidemic area. Heat Shock Proteins (HSPs) are up-regulated in schistosomes as their environment changes owing to the developmental cycle, assisting the parasite in living with the adverse circumstances related with its life cycle. Schistosomiasis is still a severe health problem in the people of many countries in worldwide. In this work, to develop a chimeric antigen, we used an advanced and powerful immunoinformatics technique that targeted Schistosoma mansoni (S. mansoni) Heat shock protein (HSPs). Antigenicity, immunogenicity, allergenicity, and physicochemical characteristics were all assessed in silico for the developed subunit vaccine. The 3D structure of the vaccine was constructed and the stability of the vaccine construct was increased by using disulphide engineering. The protein-protein docking and simulation were performed between the vaccine construct and Toll-like receptor-4. The antigenicity probability value obtained for the vaccine construct was 0.93, which indicates that vaccine is non-allergenic and safe for human consumption. Communicated by Ramaswamy H. Sarma.

Immunoinformatics-guided designing and in silico analysis of epitope-based polyvalent vaccines against multiple strains of human coronavirus (HCoV)

OBJECTIVES

The group of human coronaviruses (HCoVs) consists of some highly pathogenic viruses that have caused several outbreaks in the past. The newly emerged strain of HCoV, the SARS-CoV-2 is responsible for the recent global pandemic that has already caused the death of hundreds of thousands of people due to the lack of effective therapeutic options.

METHODS

In this study, immunoinformatics methods were used to design epitope-based polyvalent vaccines which are expected to be effective against four different pathogenic strains of HCoV i.e., HCoV-OC43, HCoV-SARS, HCoV-MERS, and SARS-CoV-2.

RESULTS

The constructed vaccines consist of highly antigenic, non-allergenic, nontoxic, conserved, and non-homologous T-cell and B-cell epitopes from all the four viral strains. Therefore, they should be able to provide strong protection against all these strains. Protein-protein docking was performed to predict the best vaccine construct. Later, the MD simulation and immune simulation of the best vaccine construct also predicted satisfactory results. Finally, in silico cloning was performed to develop a mass production strategy of the vaccine.

CONCLUSION

If satisfactory results are achieved in further in vivo and in vitro studies, then the vaccines designed in this study might be effective as preventative measures against the selected HCoV strains.

Designing a multi-epitope vaccine against coxsackievirus B based on immunoinformatics approaches

Coxsackievirus B (CVB) is one of the major viral pathogens of human myocarditis and cardiomyopathy without any effective preventive measures; therefore, it is necessary to develop a safe and efficacious vaccine against CVB. Immunoinformatics methods are both economical and convenient as in-silico simulations can shorten the development time. Herein, we design a novel multi-epitope vaccine for the prevention of CVB by using immunoinformatics methods. With the help of advanced immunoinformatics approaches, we predicted different B-cell, cytotoxic T lymphocyte (CTL), and helper T lymphocyte (HTL) epitopes, respectively. Subsequently, we constructed the multi-epitope vaccine by fusing all conserved epitopes with appropriate linkers and adjuvants. The final vaccine was found to be antigenic, non-allergenic, and stable. The 3D structure of the vaccine was then predicted, refined, and evaluated. Molecular docking and dynamics simulation were performed to reveal the interactions between the vaccine with the immune receptors MHC-I, MHC-II, TLR3, and TLR4. Finally, to ensure the complete expression of the vaccine protein, the sequence of the designed vaccine was optimized and further performed in-silico cloning. In conclusion, the molecule designed in this study could be considered a potential vaccine against CVB infection and needed further experiments to evaluate its safety and efficacy.

A candidate multi-epitope vaccine against Lumpy skin disease

Lumpy skin disease (LSD) is a fulminant infectious disease that mostly affects cattle and causes considerable economic loss throughout the globe. This study was conducted to develop a new multi-epitope-based vaccine against LSD that can elicit immunological responses using an in silico reverse vaccinology approach. Initially, three antigenic proteins, protein E5, E3 ubiquitin-protein ligase LAP and 62 kDa protein, were manipulated to recognize potential T-cell and B-cell epitopes. To identify superior epitopes, a variety of bioinformatic techniques including antigenicity testing, transmembrane topology screening, allergenicity assessment, conservancy analysis, and toxicity evaluation were used. Finally, three new subunit vaccines (construct V1, V2 and V3) were developed employing the most effective epitopes, suitable adjuvants, pan HLA DR-binding epitope (PADRE) and linkers. Then, based on the antigenicity, solubility, and validation score of the 3D structures, construct V2 was chosen as one of the best candidate vaccines. The results of the molecular dynamic simulation and disulphide engineering indicated that the vaccine (construct V2) was stable. Additionally, the immunological simulation findings supported the vaccine candidate's ability to trigger humoral and cellular immune responses. Further validation of the proposed vaccine candidate may necessitate additional in vitro and in vivo investigations.

Core Proteomics and Immunoinformatic Approaches to Design a Multiepitope Reverse Vaccine Candidate against Chagas Disease

Chagas disease is a tropical ailment indigenous to South America and caused by the protozoan parasite Trypanosoma cruzi, which has serious health consequences globally. Insect vectors transmit the parasite and, due to the lack of vaccine availability and limited treatment options, we implemented an integrated core proteomics analysis to design a reverse vaccine candidate based on immune epitopes for disease control. Firstly, T. cruzi core proteomics was used to identify immunodominant epitopes. Therefore, we designed the vaccine sequence to be non-allergic, antigenic, immunogenic, and to have better solubility. After predicting the tertiary structure, docking and molecular dynamics simulation (MDS) were performed with TLR4, MHC-I, and MHC-II receptors to discover the binding affinities. The final vaccine design demonstrated significant hydrogen bond interactions upon docking with TLR4, MHC-I, and MHC-II receptors. This indicated the efficacy of the vaccine candidate. A server-based immune simulation approach was generated to predict the efficacy. Significant structural compactness and binding stability were found based on MDS. Finally, by optimizing codons on Escherichia coli K12, a high GC content and CAI value were obtained, which were then incorporated into the cloning vector pET2+ (a). Thus, the developed vaccine sequence may be a viable therapy option for Chagas disease.

Insight into the first multi-epitope-based peptide subunit vaccine against avian influenza A virus (H5N6): An immunoinformatics approach

The rampant spread of highly pathogenic avian influenza A (H5N6) virus has drawn additional concerns along with ongoing Covid-19 pandemic. Due to its migration-related diffusion, the situation is deteriorating. Without an existing effective therapy and vaccines, it will be baffling to take control measures. In this regard, we propose a revers vaccinology approach for prediction and design of a multi-epitope peptide based vaccine. The induction of humoral and cell-mediated immunity seems to be the paramount concern for a peptide vaccine candidate; thus, antigenic B and T cell epitopes were screened from the surface, membrane and envelope proteins of the avian influenza A (H5N6) virus, and passed through several immunological filters to determine the best possible one. Following that, the selected antigenic with immunogenic epitopes and adjuvant were linked to finalize the multi-epitope-based peptide vaccine by appropriate linkers. For the prediction of an effective binding, molecular docking was carried out between the vaccine and immunological receptors (TLR8). Strong binding affinity and good docking scores clarified the stringency of the vaccines. Furthermore, molecular dynamics simulation was performed within the highest binding affinity complex to observe the stability, and minimize the designed vaccine's high mobility region to order to increase its stability. Then, Codon optimization and other physicochemical properties were performed to reveal that the vaccine would be suitable for a higher expression at cloning level and satisfactory thermostability condition. In conclusion, predicting the overall in silico assessment, we anticipated that our designed vaccine would be a plausible prevention against avian influenza A (H5N6) virus.

The Giardial Arginine Deiminase Participates in Giardia-Host Immunomodulation in a Structure-Dependent Fashion via Toll-like Receptors

Beyond the problem in public health that protist-generated diseases represent, understanding the variety of mechanisms used by these parasites to interact with the human immune system is of biological and medical relevance. Giardia lamblia is an early divergent eukaryotic microorganism showing remarkable pathogenic strategies for evading the immune system of vertebrates. Among various multifunctional proteins in Giardia, arginine deiminase is considered an enzyme that plays multiple regulatory roles during the life cycle of this parasite. One of its most important roles is the crosstalk between the parasite and host. Such a molecular "chat" is mediated in human cells by membrane receptors called Toll-like receptors (TLRs). Here, we studied the importance of the 3D structure of giardial arginine deiminase (GlADI) to immunomodulate the human immune response through TLRs. We demonstrated the direct effect of GlADI on human TLR signaling. We predicted its mode of interaction with TLRs two and four by using the AlphaFold-predicted structure of GlADI and molecular docking. Furthermore, we showed that the immunomodulatory capacity of this virulent factor of Giardia depends on the maintenance of its 3D structure. Finally, we also showed the influence of this enzyme to exert specific responses on infant-like dendritic cells.

Design, construction and in vivo functional assessment of a hinge truncated sFLT01

Gene therapy for the treatment of ocular neovascularization has reached clinical trial phases. The AAV2-sFLT01 construct was already evaluated in a phase 1 open-label trial administered intravitreally to patients with advanced neovascular age-related macular degeneration. SFLT01 protein functions by binding to VEGF and PlGF molecules and inhibiting their activities simultaneously. It consists of human VEGFR1/Flt-1 (hVEGFR1), a polyglycine linker, and the Fc region of human IgG1. The IgG1 upper hinge region of the sFLT01 molecule makes it vulnerable to radical attacks and prone to causing immune reactions. This study pursued two goals: (i) minimizing the immunogenicity and vulnerability of the molecule by designing a truncated molecule called htsFLT01 (hinge truncated sFLT01) that lacked the IgG1 upper hinge and lacked 2 amino acids from the core hinge region; and (ii) investigating the structural and functional properties of the aforesaid chimeric molecule at different levels (in silico, in vitro, and in vivo). Molecular dynamics simulations and molecular mechanics energies combined with Poisson-Boltzmann and surface area continuum solvation calculations revealed comparable free energy of binding and binding affinity for sFLT01 and htsFLT01 to their cognate ligands. Conditioned media from human retinal pigment epithelial (hRPE) cells that expressed htsFLT01 significantly reduced tube formation in HUVECs. The AAV2-htsFLT01 virus suppressed vascular development in the eyes of newborn mice. The htsFLT01 gene construct is a novel anti-angiogenic tool with promising improvements compared to existing treatments.

Evaluating complete surface-associated and secretory proteome of Leishmania donovani for discovering novel vaccines and diagnostic targets

The protozoa Leishmania donovani causes visceral leishmaniasis (kala-azar), the third most common vector-borne disease. The visceral organs, particularly the spleen, liver, and bone marrow, are affected by the disease. The lack of effective treatment regimens makes curing and eradicating the disease difficult. The availability of complete L. donovani genome/proteome data allows for the development of specific and efficient vaccine candidates using the reverse vaccinology method, while utilizing the unique sequential and structural features of potential antigenic proteins to induce protective T cell and B cell responses. Such shortlisted candidates may then be tested quickly for their efficacy in the laboratory and later in clinical settings. These antigens will also be useful for designing antigen-based next-generation sero-diagnostic assays. L. donovani's cell surface-associated proteins and secretory proteins are among the first interacting entities to be exposed to the host immune machinery. As a result, potential antigenic epitope peptides derived from these proteins could serve as competent vaccine components. We used a stepwise filtering-based in silico approach to identify the entire surface-associated and secretory proteome of L. donovani, which may provide rationally selected most exposed antigenic proteins. Our study identified 12 glycosylphosphatidylinositol-anchored proteins, 45 transmembrane helix-containing proteins, and 73 secretory proteins as potent antigens unique to L. donovani. In addition, we used immunoinformatics to identify B and T cell epitopes in them. Out of the shortlisted surface-associated and secretory proteome, 66 protein targets were found to have the most potential overlapping B cell and T cell epitopes (linear and conformational; MHC class I and MHC class II).

Proteome Exploration of Legionella pneumophila To Identify Novel Therapeutics: a Hierarchical Subtractive Genomics and Reverse Vaccinology Approach

Legionella pneumophila is a human pathogen distributed worldwide, causing Legionnaires’ disease (LD), a severe form of pneumonia and respiratory tract infection. L. pneumophila is emerging as an antibiotic-resistant strain, and controlling LD is now difficult. Hence, developing novel drugs and vaccines against L. pneumophila is a major research priority.

Multi-epitope based subunit vaccine construction against Banna virus targeting on two outer proteins (VP4 and VP9): A computational approach

Recently, RNA viruses have gained a mammoth concern for causing various outbreaks, and due to pandemics, they are acquiring additional attention throughout the world. An emerging RNA as well as vector-borne Banna Virus (BAV) is a human pathogen resulting in encephalitis, fever, headache, muscle aches, and severe coma. Besides human, pathogenic BAV was also detected from pigs, cattle, ticks, midges, and mosquitoes in Indonesia, China, and Vietnam. Due to high mutation tendency and dearth of a species barrier, this virus will consider as a significant threat in the near future throughout the planet, particularly in Africa. Despite of severe human case fatalities in several countries, there are no specific therapeutics, available vaccines, and other preventive measures against BAV. Thus, to find out the effective therapeutics and preventive strategies are crying exigency. In the present study, a unique multi-epitope-based peptide vaccine candidate is constructed using bioinformatics' tools that efficiently instigate immune cells for generating BAV antibodies. The potential vaccine candidates were developed using both T and B -cell epitopes. UniprotKB database was used to retrieve of two outer proteins (VP9 and VP4), and homologous sequences of BAV taxid: 7763, 649,604, 77,763, and 8453 were searched by NCBI BLAST. These serotypes are the most closely associated with the disease. Then combining the best-selected epitopes in various combinations with different adjuvants, three distinct vaccine candidates were formed. The validity tests were performed for the screened vaccine candidate regarding stability, allergenicity, and antigenicity parameters. Moreover, molecular dynamic simulations of the selected vaccine with TLR-8 immune receptor confirmed the stability of the binding pose and showed a significant response to immune cells. Thus, the results established that the designed chimeric peptide vaccine could enhance the immune response against BAV.

In-silico immunoinformatic analysis of SARS-CoV-2 virus for the development of putative vaccine construct

COVID-19 (CoronaVirus disease 2019) is caused by the SARS-CoV-2 virus (severe acute respiratory syndrome corona virus 2). SARS-CoV-2 virus is highly contagious and affects the human respiratory tract resulting in symptoms such as high fever, body ache, cough, dysfunctions of tastebuds and smelling sense of body. The objective of the present study involves immunoinformatic analysis to predict COVID-19 protein for vaccine construct based on the genomic information SARS-CoV-2 virus. At present, as per WHO estimates, around 133 COVID-19 novel vaccines under development. Three amino acid sequences of SARS-CoV-2 were retrieved from the NCBI database for the analysis of vaccine construct. This study involves computational and immunoinformatic methods. The Immunoinformatic tools used in the present study are NetCTL server, IFN epitope server, Toxin PRED, BCPred, CTL + HTL + ADJUVANTS + LINKERS, AlgPredserver, VaxiJenserver, ProtParam to predict vaccine construct. The secondary and tertiary structure prediction is done by PSIPRED, I-TASSER, Galaxy refine, prosA + Ramachandran. Finally, docking of the vaccine constructs and ligand was done with the help of Cluspro 2.0. C-ImmSimm webserver to simulate the potential vaccine construct. The present study demonstrated three potential Vaccine constructs for the SARS-CoV-2 virus, which were docked with TLR8 (Toll-likereceptor8). Interestingly from these, all constructs one having a high potential for the inhibition effect of the SARS-CoV-2virus. Immunological simulation data shows significant elevated amount of memory B cell; also, the high response was seen in TH(Helper) and TC(cytotoxic) cell population from the vaccine construct proposed in the current study. Hence, these constructs are suitable vaccine candidates that might be useful in developing a novel vaccine.

Immunoinformatics Approach to Design Multi-Epitope- Subunit Vaccine against Bovine Ephemeral Fever Disease

Bovine ephemeral fever virus (BEFV) is an overlooked pathogen, recently gaining widespread attention owing to its associated enormous economic impacts affecting the global livestock industries. High endemicity with rapid spread and morbidity greatly impacts bovine species, demanding adequate attention towards BEFV prophylaxis. Currently, a few suboptimum vaccines are prevailing, but were confined to local strains with limited protection. Therefore, we designed a highly efficacious multi-epitope vaccine candidate targeted against the geographically distributed BEFV population. By utilizing immunoinformatics technology, all structural proteins were targeted for B- and T-cell epitope prediction against the entire allele population of BoLA molecules. Prioritized epitopes were adjoined by linkers and adjuvants to effectively induce both cellular and humoral immune responses in bovine. Subsequently, the in silico construct was characterized for its physicochemical parameters, high immunogenicity, least allergenicity, and non-toxicity. The 3D modeling, refinement, and validation of ligand (vaccine construct) and receptor (bovine TLR7) then followed molecular docking and molecular dynamic simulation to validate their stable interactions. Moreover, in silico cloning of codon-optimized vaccine construct in the prokaryotic expression vector (pET28a) was explored. This is the first time HTL epitopes have been predicted using bovine datasets. We anticipate that the designed construct could be an effective prophylactic remedy for the BEF disease that may pave the way for future laboratory experiments.

Immunoinformatics and molecular dynamics approaches: Next generation vaccine design against West Nile virus

West Nile Virus (WNV) is a life threatening flavivirus that causes significant morbidity and mortality worldwide. No preventive therapeutics including vaccines against WNV are available for human use. In this study, immunoinformatics approach was performed to design a multi epitope-based subunit vaccine against this deadly pathogen. Human (HLA) and Mice (H-2) allele specific potential T-cell and B-cell epitopes were shortlisted through a stringent procedure. Molecular docking showed selected epitopes that have stronger binding affinity with human TLR-4. Molecular dynamics simulation confirmed the stable nature of the docked complex. Furthermore, in silico cloning analysis ensures efficient expression of desired gene in the microbial system. Interestingly, previous studies showed that two of our selected epitopes have strong immune response against WNV. Therefore, selected epitopes could be strong vaccine candidates to prevent WNV infections in human. However, further in vitro and in vivo investigations could be strengthening the validation of the vaccine candidate against WNV.

Design of a new multi-epitope vaccine against Brucella based on T and B cell epitopes using bioinformatics methods

Brucellosis is one of the most serious and widespread zoonotic diseases, which seriously threatens human health and the national economy. This study was based on the T/B dominant epitopes of Brucella outer membrane protein 22 (Omp22), outer membrane protein 19 (Omp19) and outer membrane protein 28 (Omp28), with bioinformatics methods to design a safe and effective multi-epitope vaccine. The amino acid sequences of the proteins were found in the National Center for Biotechnology Information (NCBI) database, and the signal peptides were predicted by the SignaIP-5.0 server. The surface accessibility and hydrophilic regions of proteins were analysed with the ProtScale software and the tertiary structure model of the proteins predicted by I-TASSER software and labelled with the UCSF Chimera software. The software COBEpro, SVMTriP and BepiPred were used to predict B cell epitopes of the proteins. SYFPEITHI, RANKpep and IEDB were employed to predict T cell epitopes of the proteins. The T/B dominant epitopes of three proteins were combined with HEYGAALEREAG and GGGS linkers, and carriers sequences linked to the N- and C-terminus of the vaccine construct with the help of EAAAK linkers. Finally, the tertiary structure and physical and chemical properties of the multi-epitope vaccine construct were analysed. The allergenicity, antigenicity and solubility of the multi-epitope vaccine construct were 7.37–11.30, 0.788 and 0.866, respectively. The Ramachandran diagram of the mock vaccine construct showed 96.0% residues within the favoured and allowed range. Collectively, our results showed that this multi-epitope vaccine construct has a high-quality structure and suitable characteristics, which may provide a theoretical basis for future laboratory experiments.

Combination of highly antigenic nucleoproteins to inaugurate a cross-reactive next generation vaccine candidate against Arenaviridae family

Arenaviral infections often result lethal hemorrhagic fevers, affecting primarily in African and South American regions. To date, there is no FDA-approved licensed vaccine against arenaviruses and treatments have been limited to supportive therapy. Hence, the study was employed to design a highly immunogenic cross-reactive vaccine against Arenaviridae family using reverse vaccinology approach. The whole proteome of Lassa virus (LASV), Lymphocytic Choriomeningitis virus (LCMV), Lujo virus and Guanarito virus were retrieved and assessed to determine the most antigenic viral proteins. Both T-cell and B-cell epitopes were predicted and screened based on transmembrane topology, antigenicity, allergenicity, toxicity and molecular docking analysis. The final constructs were designed using different adjuvants, top epitopes, PADRE sequence and respective linkers and were assessed for the efficacy, safety, stability and molecular cloning purposes. The proposed epitopes were highly conserved (84%–100%) and showed greater cumulative population coverage. Moreover, T cell epitope GWPYIGSRS was conserved in Junin virus (Argentine mammarenavirus) and Sabia virus (Brazilian mammarenavirus), while B cell epitope NLLYKICLSG was conserved in Machupo virus (Bolivian mammarenavirus) and Sabia virus, indicating the possibility of final vaccine construct to confer a broad range immunity in the host. Docking analysis of the refined vaccine with different MHC molecules and human immune receptors were biologically significant. The vaccine-receptor (V1-TLR3) complex showed minimal deformability at molecular level and was compatible for cloning into pET28a(+) vector of E. coli strain K12. The study could be helpful in developing vaccine to combat arenaviral infections in the future. However, further in vitro and in vivo trials using model animals are highly recommended for the experimental validation of our findings.

Design of a Multi-epitope Vaccine Against Acinetobacter baumannii Using Immunoinformatics Approach

Acinetobacter baumannii is one of the most successful pathogens causing nosocomial infections and has significantly multidrug-resistant. So far, there are no certain treatments to protect against infection with A. baumannii, therefore an effective A. baumannii vaccine needed. The purpose of this study was to predict antigenic epitopes of CarO protein for designing the A. baumannii vaccine using immunoinformatics analysis. CarO protein is one of the most important factors in the resistance against the antibiotic Carbapenem. In this study, T and B-cell epitopes of CarO protein were predicted and screened based on the antigenicity, toxicity, allergenicity features. The epitopes were linked by suitable linkers. Four different adjuvants were attached to the vaccine constructs which among them, vaccine construct 3 was chosen to predict the secondary and the 3D structure of the vaccine. The refinement process was performed to improve the quality of the 3D model structure; the validation process is performed using the Ramachandran plot and ProSA z-score. The designed vaccine's binding affinity to six various HLA molecules and TLR 2 and TLR4 were evaluated by molecular docking. Finally, in silico gene cloning was performed in the pET28a (+) vector. The findings suggest that the vaccine may be a promising vaccine to prevent A. baumannii infection.

An immunoinformatics approach for the design of a multi-epitope subunit vaccine for urogenital schistosomiasis

Discovery of T and B memory cells capable of eliciting long-term immunity against schistosomiasisis is important for people in endemic areas. Changes in schistosomes environment due to developmental cycle, induces up-regulation of Heat Shock Proteins (HSPs) which assist the parasite in coping with the hostile conditions associated with its life cycle. This study therefore focused on exploring the role of HSPs in urogenital schistosomiasis to develop new multi-epitope subunit vaccine against the disease using immunoinformatic approaches. The designed subunit vaccine was subjected to in silico antigenicity, immunogenicity, allergenicity and physicochemical parameters analysis. A 3D structure of the vaccine construct was predicted, followed by disulphide engineering for stability, codon adaptation and in silico cloning for proper expression and molecular protein–protein docking of vaccine construct in the vector against toll-like receptor 4 receptor, respectively. Consequently, a 493 amino acid multi-epitope vaccine construct of antigenicity probability of 0.91 was designed. This was predicted to be stable, non-allergenic in nature and safe for human use.

Comprehensive genome based analysis of Vibrio parahaemolyticus for identifying novel drug and vaccine molecules: Subtractive proteomics and vaccinomics approach

Multidrug-resistant Vibrio parahaemolyticus has become a significant public health concern. The development of effective drugs and vaccines against Vibrio parahaemolyticus is the current research priority. Thus, we aimed to find out effective drug and vaccine targets using a comprehensive genome-based analysis. A total of 4822 proteins were screened from V. parahaemolyticus proteome. Among 16 novel cytoplasmic proteins, ‘VIBPA Type II secretion system protein L’ and ‘VIBPA Putative fimbrial protein Z’ were subjected to molecular docking with 350 human metabolites, which revealed that Eliglustat, Simvastatin and Hydroxocobalamin were the top drug molecules considering free binding energy. On the contrary, ‘Sensor histidine protein kinase UhpB’ and ‘Flagellar hook-associated protein of 25 novel membrane proteins were subjected to T-cell and B-cell epitope prediction, antigenicity testing, transmembrane topology screening, allergenicity and toxicity assessment, population coverage analysis and molecular docking analysis to generate the most immunogenic epitopes. Three subunit vaccines were constructed by the combination of highly antigenic epitopes along with suitable adjuvant, PADRE sequence and linkers. The designed vaccine constructs (V1, V2, V3) were analyzed by their physiochemical properties and molecular docking with MHC molecules- results suggested that the V1 is superior. Besides, the binding affinity of human TLR-1/2 heterodimer and construct V1 could be biologically significant in the development of the vaccine repertoire. The vaccine-receptor complex exhibited deformability at a minimum level that also strengthened our prediction. The optimized codons of the designed construct was cloned into pET28a(+) vector of E. coli strain K12. However, the predicted drug molecules and vaccine constructs could be further studied using model animals to combat V. parahaemolyticus associated infections.

Blueprint of epitope-based multivalent and multipathogenic vaccines: targeted against the dengue and zika viruses

Both dengue virus (DENV) and zika virus (ZIKV) belong to the highly infectious Flaviviridae family that has already caused several outbreaks and epidemics in many countries. DENV and ZIKV cause two of the most wide spread mosquito-borne viral diseases in the world, dengue fever (DENF) and zika fever (ZIKF), respectively. In many regions around the world, both of these diseases can outbreak together and can be lethal as well as life-threatening. Unfortunately, there is no functional and satisfactory vaccine available to combat these viruses. Therefore, in this study, we have attempted to design a blue print of potential multivalent and multipathogenic vaccines using immunoinformatics approach, which can combat both the DENV and ZIKV infections, simultaneously. Initially, three vaccines were designed; containing highly antigenic, non-allergenic, and non-toxic epitopes of T-cell (100% conserved) and B-cell from all the four DENV serotypes and ZIKV. In total, nine cytotoxic T-lymphocytic (CTL), nine helper T-lymphocytic (HTL), and seven B-cell lymphocytic (BCL) epitopes were used to construct three vaccines using three different adjuvants, designated as 'V1', 'V2', and 'V3'. Later, V3 was found to be the best vaccine construct, determined by molecular docking analysis. Thereafter, several in silico validation studies including molecular dynamics simulation and immune simulation were performed which indicated that V3 might be quite stable and should generate substantial immune response in the biological environment. However, further in vivo and in vitro validation might be required to finally confirm the safety and efficacy of our suggested vaccine constructs.Communicated by Ramaswamy H. Sarma.

Contriving Multi-Epitope Subunit of Vaccine for COVID-19: Immunoinformatics Approaches

COVID-19 has recently become the most serious threat to public health, and its prevalence has been increasing at an alarming rate. The incubation period for the virus is ~1-14 days and all age groups may be susceptible to a fatality rate of about 5.9%. COVID-19 is caused by a novel single-stranded, positive (+) sense RNA beta coronavirus. The development of a vaccine for SARS-CoV-2 is an urgent need worldwide. Immunoinformatics approaches are both cost-effective and convenient, as in silico predictions can reduce the number of experiments needed. In this study, with the aid of immunoinformatics tools, we tried to design a multi-epitope vaccine that can be used for the prevention and treatment of COVID-19. The epitopes were computed by using B cells, cytotoxic T lymphocytes (CTL), and helper T lymphocytes (HTL) base on the proteins of SARS-CoV-2. A vaccine was devised by fusing together the B cell, HTL, and CTL epitopes with linkers. To enhance the immunogenicity, the β-defensin (45 mer) amino acid sequence, and pan-HLA DR binding epitopes (13aa) were adjoined to the N-terminal of the vaccine with the help of the EAAAK linker. To enable the intracellular delivery of the modeled vaccine, a TAT sequence (11aa) was appended to C-terminal. Linkers play vital roles in producing an extended conformation (flexibility), protein folding, and separation of functional domains, and therefore, make the protein structure more stable. The secondary and three-dimensional (3D) structure of the final vaccine was then predicted. Furthermore, the complex between the final vaccine and immune receptors (toll-like receptor-3 (TLR-3), major histocompatibility complex (MHC-I), and MHC-II) were evaluated by molecular docking. Lastly, to confirm the expression of the designed vaccine, the mRNA of the vaccine was enhanced with the aid of the Java Codon Adaptation Tool, and the secondary structure was generated from Mfold. Then we performed in silico cloning. The final vaccine requires experimental validation to determine its safety and efficacy in controlling SARS-CoV-2 infections.

Identification of immunogenic T-cell peptides of Mycobacterium tuberculosis PE_PGRS33 protein

The development of a more efficient vaccine is needed to improve tuberculosis control. One of the current approaches is to identify immunogenic T-cell peptides that can elicit a protective and specific immune response. These peptides come from immunogenic proteins of the pathogen. The PE_PGRS33 protein of Mycobacterium tuberculosis has been proved immunogenic. However, little is known about immunogenic T-cell peptides of PE_PGRS33 and their interactions with MHC-II molecules. Therefore, we used the SYFPHEITHI database to determine the immunogenic PE_PGRS33 T-cell peptides. Next, we built homology models by using MOE v2018.1 software in order to obtain information about the specific interactions between the peptides and I-A^k. The AlgPred server was employed to look for allergenic sites in PE_PGRS33. We developed a sequence alignment between PE_PGRS33 and all the human proteins by using BLAST. Three peptides were commercially synthesized, and their activity was evaluated in vitro by the stimulation of PBMC from household contacts of TB patients. Our in silico results showed five immunogenic T-cell peptides. BLAST analysis showed low homology of PE_PGRS33 with human proteins and AlgPred did not reveal allergenic sites in PE_PGRS33. The three peptides triggered the activation of CD4⁺ T cells from the households contacts, showed by the production of IFN-γ. We identified three immunogenic peptides of PE_PGRS33 that demonstrated activity in vitro which allows to deepen into the immune response towards mycobacterial antigens, moving forward to the identification of new vaccine candidates.

Identification of functional epitopes of structural proteins and in-silico designing of dual acting multiepitope anti-tick vaccine against emerging Crimean-Congo hemorrhagic fever virus

Recurrent outbreaks of Crimean-Congo hemorrhagic fever (CCHF) virus infection in different parts of world are a major global health concern. The CCHF viral infection is associated with severe hemorrhagic fevers and mortality up to 40%. More than 30 countries in Asia, Europe and Africa are affected with CCHF infection. Prevention of infection through vaccine becomes more important when no effective antiviral and associated therapies are available. Further ticks play a crucial role in maintenance and transmission of CCHFV. Therefore, the control of transmission by ticks is warranted for ultimate prevention of outbreak. The study employed a series of immunoinformatics approaches to design novel multiepitope vaccine targeting highly immunodominant epitopes of major structural proteins (Nucleoprotein and Glycoprotein complex) of CCHFV. Vaccine was designed by incorporating linear and conformational B cell, helper and cytotoxic T cell epitopes from these crucial immunogenic proteins adjoined with appropriate linkers and adjuvant. This vaccine construct was also complemented with a highly immunogenic and conserved protective tick salivary antigen named subolesin to impart dual activity as a unique transmission blocking vaccine. The B-cell peptides were also experimentally validated. The designed vaccine was further in silico validated for its physiochemical properties, allergenicity and immunogenicity etc. The proposed candidate vaccine construct has the potential to function both as a vaccine against CCHF virus as well as a universal anti-tick vaccine.

Designing a vaccine for fascioliasis using immunogenic 24 kDa mu-class glutathione s-transferase

Fascioliasis, caused by the liver fluke Fasciola gigantica, is a significant zoonotic disease of the livestock and human, causing substantial economic loss worldwide. Triclabendazole (TCBZ) is the only drug available for the management of the disease against which there is an alarming increase in drug resistance. No vaccine is available commercially for the protection against this disease. Increasing resistance to TCBZ and the lack of a successful vaccine against fascioliasis demands the development of vaccines. In the present study, a structural immunoinformatics approach was used to design a multi-epitope subunit vaccine using the glutathione S-transferase (GST) protein of Fasciola gigantica. The GST antigen is a safe, non-allergic, highly antigenic, and effective vaccine candidate against various parasitic flukes and worms. The cytotoxic T lymphocytes, helper T lymphocytes, and B-cell epitopes were selected for constructing the vaccine based on their immunogenic behavior and binding affinity. The physicochemical properties, allergenicity, and antigenicity of the designed vaccine were analyzed. To elucidate the tertiary structure of the vaccine, homology modeling was performed, followed by structure refinement and docking against the TLR2 immune receptor. Molecular dynamics simulations showed a stable interaction between the vaccine and the receptor complex. Finally, in silico cloning was performed to evaluate the expression and translation of the vaccine construct in the E. coli expression system. Further studies require experimental validation for the safety and immunogenic behavior of the designed vaccine.

Exploiting the reverse vaccinology approach to design novel subunit vaccines against Ebola virus

Ebola virus is a highly pathogenic RNA virus that causes the Ebola haemorrhagic fever in human. This virus is considered as one of the dangerous viruses in the world with very high mortality rate. To date, no epitope-based subunit vaccine has yet been discovered to fight against Ebola although the outbreaks of this deadly virus took many lives in the past. In this study, approaches of reverse vaccinology were utilized in combination with different tools of immunoinformatics to design subunit vaccines against Ebola virus strain Mayinga-76. Three potential antigenic proteins of this virus i.e., matrix protein VP40, envelope glycoprotein and nucleoprotein were selected to construct the subunit vaccine. The MHC class-I, MHC class-II and B-cell epitopes were determined initially and after some robust analysis i.e., antigenicity, allergenicity, toxicity, conservancy and molecular docking study, EV-1, EV-2 and EV-3 were constructed as three potential vaccine constructs. These vaccine constructs are also expected to be effective on few other strains of Ebola virus since the highly conserved epitopes were used for vaccine construction. Thereafter, molecular docking study was conducted on these vaccines and EV-1 emerged as the best vaccine construct. Afterward, molecular dynamics simulation study revealed the good performances and stability of the intended vaccine protein. Finally, codon adaptation and in silico cloning were carried out to design a possible plasmid (pET-19b plasmid vector was used) for large scale production of the EV-1 vaccine. However, further in vitro and in vivo studies might be required on the predicted vaccines for final validation.

Toward a chimeric vaccine against multiple isolates of Mycobacteroides - An integrative approach

AIM

Nontuberculous mycobacterial (NTM) infection such as endophthalmitis, dacryocystitis, and canaliculitis are pervasive across the globe and are currently managed by antibiotics. However, the recent cases of Mycobacteroides developing drug resistance reported along with the improper practice of medicine intrigued us to explore its genomic and proteomic canvas at a global scale and develop a chimeric vaccine against Mycobacteroides.

MAIN METHODS

We carried out a vivid genomic study on five recently sequenced strains of Mycobacteroides and explored their Pan-core genome/proteome in three different phases. The promiscuous antigenic proteins were identified via a subtractive proteomics approach that qualified for virulence causation, resistance and essentiality factors for this notorious bacterium. An integrated pipeline was developed for the identification of B-Cell, MHC (Major histocompatibility complex) class I and II epitopes.

KEY FINDINGS

Phase I identified the shreds of evidence of reductive evolution and propensity of the Pan-genome of Mycobacteroides getting closed soon. Phase II and Phase III produced 8 vaccine constructs. Our final vaccine construct, V6 qualified for all tests such as absence for allergenicity, presence of antigenicity, etc. V6 contains β-defensin as an adjuvant, linkers, Lysosomal-associated membrane protein 1 (LAMP1) signal peptide, and PADRE (Pan HLA-DR epitopes) amino acid sequence. Besides, V6 also interacts with a maximum number of MHC molecules and the TLR4/MD2 (Toll-like receptor 4/Myeloid differentiation factor 2) complex confirmed by docking and molecular dynamics simulation studies.

SIGNIFICANCE

The knowledge harnessed from the current study can help improve the current treatment regimens or in an event of an outbreak and propel further related studies.

In silico prediction of the epitopes for the immunogenic proteins present in Mycobacterium avium subsp. paratuberculosis

Johne’s disease caused by Mycobacterium avium subsp. paratuberculosis is a widespread problem in ruminants worldwide. Diagnosis of the disease during the early stages of infection is difficult. In search of newer proteins with antigenic and immunogenic characters, in silico epitope analysis of the immunogenic proteins was performed which identifies the proteins expressed during the early stages of infection and which could stimulate cell mediated immune response. T cell epitopes were predicted for the six immunogenic proteins and the epitopes were sorted based on the percentile ranking and repetition among MHC Class I alleles. 3D modeling and protein-protein interaction studies revealed that ELPLPQTYVD, DVVGYDRTQD, PDLQSVLGATPGAG, DGLRAQDD, DGLRAQDD and PGHVTDD epitopes interact with the MHC Class I molecule through hydrogen bonding. These epitopes are identified as potent candidates for the immunodiagnostic studies and could be further evaluated using in vitro studies.

Multi-epitope based vaccine against yellow fever virus applying immunoinformatics approaches

Yellow fever disease is considered a re-emerging major health issue which has caused recent outbreaks with a high number of deaths. Tropical countries, mainly African and South American, are the most affected by Yellow fever outbreaks. Despite the availability of an attenuated vaccine, its use is limited for some groups such as pregnant and nursing women, immunocompromised and immunosuppressed patients, elderly people >65 years, infants <6 months and patients with biological disorders like thymus disorders. In order to achieve new preventive measures, we applied immunoinformatics approaches to develop a multi-epitope-based subunit vaccine for Yellow fever virus. Different epitopes, related to humoral and cell-mediated immunity, were predicted for complete polyproteins of two Yellow fever strains (Asibi and 17 D vaccine). Those epitopes common for both strains were mapped into a set of 137 sequences of Yellow fever virus, including 77 sequences from a recent outbreak at the state of Minas Gerais, southeast Brazil. Therefore, the present work uses robust bioinformatics approaches for the identification of a multi-epitope vaccine against the Yellow fever virus. Our results indicate that the identified multi-epitope vaccine might stimulate humoral and cellular immune responses and could be a potential vaccine candidate against Yellow fever virus infection. Hence, it should be subjected to further experimental validations. Communicated by Ramaswamy H. Sarma.

An immunoinformatics approach for design and validation of multi-subunit vaccine against Cryptosporidium parvum

An immunoinformatics-based approach is explored for potential multi-subunit vaccine candidates against Cryptosporidium parvum. We performed protein structure based systematic methodology for the development of a proficient multi-subunit vaccine candidate against C. parvum based on their probability of antigenicity, allergenicity and transmembrane helices as the screening criteria. The best-screened epitopes like B-cell epitopes (BCL), Helper T-lymphocytes (HTL) and cytotoxic T- lymphocytes (CTL) were joined by using the appropriate linkers to intensify and develop the presentation and processing of the antigenic molecules. Modeller software was used to generate the best 3D model of the subunit protein. RAMPAGE and other web servers were employed for the validation of the modeled protein. Furthermore, the predicted modeled structure was docked with the two known receptors like TLR2 and TLR4 through ClusPro web server. Based on the docking score, the multi-subunit vaccine docked with TLR2 was subjected to energy minimization by molecular dynamics (MD) simulation to examine their stability within a solvent system. From the simulation study, we found that the residue Glu-107 of subunit vaccine formed a hydrogen bond interaction with Arg-299 of the TLR2 receptor throughout the time frame of the MD simulation. The overall results showed that the multi-subunit vaccine could be an efficient vaccine candidate against C. parvum.

Strategic Development of a Next-Generation Multi-Epitope Vaccine To Prevent Nipah Virus Zoonotic Infection

Nipah virus (NiV) is an emerging zoonotic pathogen, reported for the recent severe outbreaks of encephalitis and respiratory illness in humans and animals, respectively. Many antiviral drugs have been discovered to inhibit this pathogen, but none of them were that much efficient. To overcome the complications associated with this severe pathogenic virus, we have designed a multi-epitope subunit vaccine using computational immunology strategies. Identification of structural and nonstructural proteins of Nipah virus assisted in the vaccine designing. The selected proteins are known to be involved in the survival of the virus. The antigenic binders (B-cell, HTL, and CTL) from the selected proteins were prognosticated. These antigenic binders will be able to generate the humoral as well as cell-mediated immunity. All the epitopes were united with the help of suitable linkers and with an adjuvant at the N-terminal of the vaccine, for the enhancement of immunogenicity. The physiological characterization, along with antigenicity and allergenicity of the designed vaccine candidates, was estimated. The 3D structure prediction and its validation were performed. The validated vaccine model was then docked and simulated with the TLR-3 receptor to check the stability of the docked complex. This next-generation approach will provide a new vision for the development of a high immunogenic vaccine against the NiV.

Contriving a chimeric polyvalent vaccine to prevent infections caused by herpes simplex virus (type-1 and type-2): an exploratory immunoinformatic approach

Herpes simplex virus type 1 (HSV-1) and 2 (HSV-2) cause a variety of infections including oral-facial infections, genital herpes, herpes keratitis, cutaneous infection and so on. To date, FDA-approved licensed HSV vaccine is not available yet. Hence, the study was conducted to identify and characterize an effective epitope based polyvalent vaccine against both types of Herpes Simplex Virus. The selected proteins were retrieved from ViralZone and assessed to design highly antigenic epitopes by binding analyses of the peptides with MHC class-I and class-II molecules, antigenicity screening, transmembrane topology screening, allergenicity and toxicity assessment, population coverage analysis and molecular docking approach. The final vaccine was constructed by the combination of top CTL, HTL and BCL epitopes from each protein along with suitable adjuvant and linkers. Physicochemical and secondary structure analysis, disulfide engineering, molecular dynamic simulation and codon adaptation were further employed to develop a unique multi-epitope peptide vaccine. Docking analysis of the refined vaccine structure with different MHC molecules and human immune TLR-2 receptor demonstrated higher interaction. Complexed structure of the modeled vaccine and TLR-2 showed minimal deformability at molecular level. Moreover, translational potency and microbial expression of the modeled vaccine was analyzed with pET28a(+) vector for E. coli strain K12 and the vaccine constructs had no similarity with entire human proteome. The study enabled design of a novel chimeric polyvalent vaccine to confer broad range immunity against both HSV serotypes. However, further wet lab based research using model animals are highly recommended to experimentally validate our findings.Communicated by Ramaswamy H. Sarma.

Immunoinformatics approaches for designing a novel multi epitope peptide vaccine against human norovirus (Norwalk virus)

Norovirus is known as a major cause of several acute gastroenteritis (AGE) outbreaks each year. A study was conducted to develop a unique multi epitope subunit vaccine against human norovirus by adopting reverse vaccinology approach. The entire viral proteome of Norwalk virus was retrieved and allowed for further in silico study to predict highly antigenic epitopes through antigenicity, transmembrane topology screening, allergenicity assessment, toxicity analysis, population coverage analysis and molecular docking approach. Capsid protein VP1 and protein VP2 were identified as most antigenic viral proteins which generated a plethora of antigenic epitopes. Physicochemical properties and secondary structure of the designed vaccine were assessed to ensure its thermostability, hydrophilicity, theoretical PI and structural behavior. Molecular docking analysis of the refined vaccine with different MHCs and human immune TLR8 receptor demonstrated higher binding interaction as well. Complexed structure of the modeled vaccine and TLR8 showed minimal deformability at molecular level. The designed construct was reverse transcribed and adapted for E. coli strain K12 prior to insertion within pET28a(+) vector for its heterologous cloning and expression, and sequence of vaccine constructs showed no similarity with human proteins. However, the study could initiate in vitro and in vivo studies regarding effective vaccine development against human norovirus.

Prioritization of potential vaccine targets using comparative proteomics and designing of the chimeric multi-epitope vaccine against Pseudomonas aeruginosa

Multidrug-resistant Pseudomonas aeruginosa is one of the worldwide health problems involved in elevated mortality and morbidity. Therefore, it is important to find a therapeutic for this pathogen. In the present study, we have designed a chimeric vaccine against P. aeruginosa with the help of comparative proteomics and reverse vaccinology approaches. Using comparative subtractive proteomic analysis of 1,191 proteomes of P. aeruginosa, a total of twenty unique non-redundant proteomes were selected. In these proteomes, fifteen outer membrane proteins (OMPs) of P. aeruginosa were selected based on the basis of hydrophilicity, non-secretory nature, low transmembrane helix (<1), essentiality, virulence, pathway association, antigenic, and protein-protein network analysis. Reverse vaccinology approach was used to identify antigenic and immunogenic MHC class I, MHC class II and B cell epitopes present in the selected OMPs that can enhance T cell and B cell mediated immunogenicity. The selected epitopes were shortlisted based on their allergenicity, toxicity potentials, solubility, and hydrophilicity analysis. Immunogenic peptides were used to design a multi-epitope vaccine construct. Immune-modulating adjuvants and PADRE (Pan HLA-DR epitopes) sequence were added with epitopes sequence to enhance the immunogenicity. All the epitopes, adjuvants and PADRE sequence were joined by linkers. The designed vaccine constructs (VT1, VT2, VT3, and VT4) were analyzed by their physiochemical properties using different tools. Selected chimeric vaccine constructs (VT1, VT3, and VT4) were further shortlisted by their docking score with different HLA alleles. The final selected VT4 construct was docked with TLR4/MD2 complex and confirmed by molecular dynamics simulation studies. The final vaccine VT-4 construct was in-silico cloned in pET28a. Therefore, the designed construct VT4 may be studied to control the interaction of P. aeruginosa with host and infection caused by P. aeruginosa.