An overview of in silico vaccine design against different pathogens and cancer

A novel multi-epitope peptide vaccine candidate targeting hepatitis E virus: An in silico approach

Hepatitis E virus (HEV) is a foodborne virus transmitted through the faecal-oral route that causes viral hepatitis in humans worldwide. Ever since its discovery as a zoonotic agent, HEV was isolated from several species with an expanding range of hosts. HEV possesses several features of other RNA viruses but also has certain HEV-specific traits that make its viral-host interactions inimitable. HEV leads to severe morbidity and mortality in immunocompromised people and pregnant women across the world. The situation in underdeveloped countries is even more alarming. Even after creating a menace across the world, we still lack an effective vaccine against HEV. Till date, there is only one licensed vaccine for HEV available only in China. The development of an anti-HEV vaccine that can reduce HEV-induced morbidity and mortality is required. Live attenuated and killed vaccines against HEV are not accessible due to the lack of a tolerant cell culture system, slow viral replication kinetics and varying growth conditions. Thus, the main focus for anti-HEV vaccine development is now on the molecular approaches. In the current study, we have designed a multi-epitope vaccine against HEV through a reverse vaccinology approach. For the first time, we have used viral ORF3, capsid protein and polyprotein altogether for epitope prediction. These are crucial for viral replication and persistence and are major vaccine targets against HEV. The proposed in silico vaccine construct comprises of highly immunogenic and antigenic T-cell and B-cell epitopes of HEV proteins. The construct is capable of inducing an effective and long-lasting host immune response as evident from the simulation results. In addition, the construct is stable, non-allergic and antigenic for the host. Altogether, our findings suggest that the in silico vaccine construct may be useful as a vaccine candidate for preventing HEV infections.

In Silico Design of CT26 Polytope and its Surface Display by ClearColi™-Derived Outer Membrane Vesicles as a Cancer Vaccine Candidate Against Colon Carcinoma

Simultaneous targeting of several mutations can be useful in colorectal cancer (CRC) due to its heterogeneity and presence of somatic mutations. As CT26 mutations and expression profiles resemble those of human CRC, we focused on designing a polyepitope vaccine based on CT26 neoepitopes. Due to its low immunogenicity, outer membrane vesicles (rOMV) as an antigen delivery system and adjuvant was applied. Herein, based on previous experimental and our in silico studies four CT26 neoepitopes with the ability to bind MHC-I and MHC-II, TCR, and induce IFN-α production were selected. To increase their immunogenicity, the gp70 and PADRE epitopes were added. The order of the neoepitopes was determined through 3D structure analysis using ProSA, Verify 3D, ERRAT, and Ramachandran servers. The stable peptide-protein docking between the selected epitopes and MHC alleles strengthen our prediction. The CT26 polytope vaccine sequence was fused to the C-terminal of cytolysin A (ClyA) anchor protein and rOMVs were isolated from endotoxin-free ClearColi™ strain. The results of the C-ImmSim server showed that the ClyA-CT26 polytope vaccine could induce T and B cells immunity.The ClyA-CT26 polytope was characterized as a soluble, stable, immunogen, and non-allergen vaccine and optimized for expression in ClearColi™ 24 h after induction with 1 mM IPTG at 25 °C. Western blot analysis confirmed the expression of ClyA-CT26 polytope by ClearColi™ and also on ClearColi™-derived rOMVs. In conclusion, we found that ClearColi™-derived rOMVs with CT26 polytope can deliver CRC neoantigens and induce antitumor immunity, but in vivo immunological studies are needed to confirm vaccine efficacy.

Multi-epitope vaccine design using in silico analysis of glycoprotein and nucleocapsid of NIPAH virus

According to the 2018 WHO R&D Blueprint, Nipah virus (NiV) is a priority disease, and the development of a vaccine against NiV is strongly encouraged. According to criteria used to categorize zoonotic diseases, NiV is a stage III disease that can spread to people and cause unpredictable outbreaks. Since 2001, the NiV virus has caused annual outbreaks in Bangladesh, while in India it has caused occasional outbreaks. According to estimates, the mortality rate for infected individuals ranges from 70 to 91%. Using immunoinformatic approaches to anticipate the epitopes of the MHC-I, MHC-II, and B-cells, they were predicted using the NiV glycoprotein and nucleocapsid protein. The selected epitopes were used to develop a multi-epitope vaccine construct connected with linkers and adjuvants in order to improve immune responses to the vaccine construct. The 3D structure of the engineered vaccine was anticipated, optimized, and confirmed using a variety of computer simulation techniques so that its stability could be assessed. According to the immunological simulation tests, it was found that the vaccination elicits a targeted immune response against the NiV. Docking with TLR-3, 7, and 8 revealed that vaccine candidates had high binding affinities and low binding energies. Finally, molecular dynamic analysis confirms the stability of the new vaccine. Codon optimization and in silico cloning showed that the proposed vaccine was expressed to a high degree in Escherichia coli. The study will help in identifying a potential epitope for a vaccine candidate against NiV. The developed multi-epitope vaccine construct has a lot of potential, but they still need to be verified by in vitro & in vivo studies.

Novel toxin-based mRNA vaccine against Clostridium perfringens using in silico approaches

Clostridium perfringens is a bacterium that causes gastrointestinal diseases in humans and animals. The several powerful toxins such as alpha toxin (CPA), beta toxin (CPB), enterotoxin (CPE), Epsilon toxin (ETX), and theta toxin, play a major role in its pathogenesis. Traditional vaccine development methods are time-consuming and costly. In silico approaches offer an alternative strategy for designing vaccines by analyzing biological data and predicting immunogenic peptides. In this study, computational tools were utilized to design a RNA vaccine targeting C. perfringens toxins. Toxin protein sequences were retrieved and their linear B-cell, MHCI, and MHCII binding epitopes were predicted. Allergenicity, toxigenicity, and IFN-γ induction were assessed to select non-allergenic, non-toxic, and IFN-γ-inducing epitopes. Molecular docking was performed to identify epitopes that fit within the binding cleft of MHC alleles. A final peptide vaccine construct was designed with selected epitopes separated by a linker sequence. The antigenicity and physicochemical properties of the vaccine were evaluated. Immune response simulation showed enhanced secondary and tertiary immune responses, increased levels of immunoglobulins, cytotoxic T lymphocytes, helper T lymphocytes, macrophage activity, and elevated levels IFN-γ and interleukin-2. Docking analysis was done to assess interactions between the vaccine structure and Toll-like receptors. Codon optimization was performed, and a final RNA vaccine construct was designed. The secondary structure of the RNA vaccine was predicted and validated. Overall, this study demonstrates the potential of in silico approaches for designing an RNA vaccine against C. perfringens toxins, contributing to improved prevention and control of associated diseases.

Quantum biochemical analysis of the binding interactions between a potential inhibitory drug and the Ebola viral glycoprotein

Ebola virus disease (EVD) causes outbreaks and epidemics in West Africa that persist until today. The envelope glycoprotein of Ebola virus (GP) consists of two subunits, GP1 and GP2, and plays a key role in anchoring or fusing the virus to the host cell in its active form on the virion surface. Toremifene (TOR) is a ligand that mainly acts as an estrogen receptor antagonist; however, a recent study showed a strong and efficient interaction with GP. In this context, we aimed to evaluate the energetic affinity features involved in the interaction between GP and toremifene by computer simulation techniques using the Molecular Fractionation Method with Conjugate Caps (MFCC) scheme and quantum-mechanical (QM) calculations, as well as missense mutations to assess protein stability. We identified ASP522, GLU100, TYR517, THR519, LEU186, LEU515 as the most attractive residues in the EBOV glycoprotein structure that form the binding pocket. We divided toremifene into three regions and evaluated that region i was more important than region iii and region ii for the formation of the TOR-GP1/GP2 complex, which might control the molecular remodeling process of TOR. The mutations that caused more destabilization were ARG134, LEU515, TYR517 and ARG559, while those that caused stabilization were GLU523 and ASP522. TYR517 is a critical residue for the binding of TOR, and is highly conserved among EBOV species. Our results may help to elucidate the mechanism of drug action on the GP protein of the Ebola virus and subsequently develop new pharmacological approaches against EVD.Communicated by Ramaswamy H. Sarma.

Advancements and hurdles in the development of a vaccine for triple-negative breast cancer: A comprehensive review of multi-omics and immunomics strategies

Triple-Negative Breast Cancer (TNBC) presents a significant challenge in oncology due to its aggressive behavior and limited therapeutic options. This review explores the potential of immunotherapy, particularly vaccine-based approaches, in addressing TNBC. It delves into the role of immunoinformatics in creating effective vaccines against TNBC. The review first underscores the distinct attributes of TNBC and the importance of tumor antigens in vaccine development. It then elaborates on antigen detection techniques such as exome sequencing, HLA typing, and RNA sequencing, which are instrumental in identifying TNBC-specific antigens and selecting vaccine candidates. The discussion then shifts to the in-silico vaccine development process, encompassing antigen selection, epitope prediction, and rational vaccine design. This process merges computational simulations with immunological insights. The role of Artificial Intelligence (AI) in expediting the prediction of antigens and epitopes is also emphasized. The review concludes by encapsulating how Immunoinformatics can augment the design of TNBC vaccines, integrating tumor antigens, advanced detection methods, in-silico strategies, and AI-driven insights to advance TNBC immunotherapy. This could potentially pave the way for more targeted and efficacious treatments.

Whole proteome analysis of MDR Klebsiella pneumoniae to identify mRNA and multiple epitope based vaccine targets against emerging nosocomial and lungs associated infections

Klebsiella pneumonia is a Gram negative facultative anaerobic bacterium involved in various community-acquired pneumonia, nosocomial and lungs associated infections. Frequent usage of several antibiotics and acquired resistance mechanisms has made this bacterium multi-drug resistance (MDR), complicating the treatment of patients. To avoid the spread of this bacterium, there is an urgent need to develop a vaccine based on immuno-informatics approaches that is more efficient than conventional method of vaccine prediction or development. Initially, the complete proteomic sequence of K. pneumonia was picked over for specific and prospective vaccine targets. From the annotation of the whole proteome, eight immunogenic proteins were selected, and these shortlisted proteins were interpreted for CTL, B-cells, and HTL epitopes prediction, to construct mRNA and multi-epitope vaccines. The Antigenicity, allergenicity and toxicity analysis validate the vaccine's design, and its molecular docking was done with immuno-receptor the TLR-3. The docking interaction showed a stronger binding affinity with a minimum energy of -1153.2 kcal/mol and established 23 hydrogen bonds, 3 salt bridges, 1 disulfide bond, and 340 non-binding contacts. Further validation was done using In-silico cloning which shows the highest CAI score of 0.98 with higher GC contents of 72.25% which represents a vaccine construct with a high value of expression in E. coli. Immune Simulation shows that the antibodies (IgM, IgG1, and IgG2) production exceeded 650,000 in 2 to 3 days but the response was completely neutralized in the 5th day. In conclusion, the study provides the effective, safe and stable vaccine construct against Klebsiella pneumonia, which further needs in vitro and in vivo validations.Communicated by Ramaswamy H. Sarma.

Bioinformatics analysis of multi-epitope peptide vaccines against Hepatitis C virus: a molecular docking study

BACKGROUND

Hepatitis C Virus (HCV) infection is one of the causal agents of liver disease burden. Six multiple antigenic peptides were synthesized including (P315, P412, and P517) plus (P1771, P2121, and P2941) to induce humoral and cellular responses, respectively against HCV infection.

AIM

This paper aimed to employ computational tools to evaluate the efficacy of each peptide individually and to determine the most effective one for better vaccine development and/or immunotherapy.

METHODS

VaxiJen web and AllerTOP servers were used for antigenicity and allergenicity prediction, respectively. The ToxinPred web server was used to investigate the peptide toxicity. Each peptide was docked with its corresponding receptors.

RESULTS

No peptides were expected to be toxic. P315 and P2941 are predicted to have robust antigenic properties, lowest allergenicity, and minimal sOPEP energies. In turn, P315 (derived from gpE1) formed the highest hydrophobic bonds with the BCR and CD81 receptors that will elicit B cell function. P2941 (derived from NS5B) was shown to strongly bind to both CD4 and CD8 receptors that will elicit T cell function.

CONCLUSION

P315 successfully bound to B cell (BCR and CD81) receptors. Also, P2941 is strongly bound to T cell (CD4 and CD8) receptors.

Design of a multi-epitope vaccine against brucellosis fused to IgG-fc by an immunoinformatics approach

Introduction

Brucella, a type of intracellular Gram-negative bacterium, has unique features and acts as a zoonotic pathogen. It can lead to abortion and infertility in animals. Eliminating brucellosis becomes very challenging once it spreads among both humans and animals, putting a heavy burden on livestock and people worldwide. Given the increasing spread of brucellosis, it is crucial to develop improved vaccines for susceptible animals to reduce the disease's impact.

Methods

In this study, we effectively used an immunoinformatics approach with advanced computer software to carefully identify and analyze important antigenic parts of Brucella abortus. Subsequently, we skillfully designed chimeric peptides to enhance the vaccine's strength and effectiveness. We used computer programs to find four important parts of the Brucella bacteria that our immune system recognizes. Then, we carefully looked for eight parts that are recognized by a type of white blood cell called cytotoxic T cells, six parts recognized by T helper cells, and four parts recognized by B cells. We connected these parts together using a special link, creating a strong new vaccine. To make the vaccine even better, we added some extra parts called molecular adjuvants. These included something called human β-defensins 3 (hBD-3) that we found in a database, and another part that helps the immune system called PADRE. We attached these extra parts to the beginning of the vaccine. In a new and clever way, we made the vaccine even stronger by attaching a part from a mouse's immune system to the end of it. This created a new kind of vaccine called MEV-Fc. We used advanced computer methods to study how well the MEV-Fc vaccine interacts with certain receptors in the body (TLR-2 and TLR-4).

Results

In the end, Immunosimulation predictions showed that the MEV-Fc vaccine can make the immune system respond strongly, both in terms of cells and antibodies.

Discussion

In summary, our results provide novel insights for the development of Brucella vaccines. Although further laboratory experiments are required to assess its protective effect.

Immunoinformatics applications in the development of therapeutic vaccines against human papillomavirus-related infections and cervical cancer

The human papillomavirus (HPV) represents the most prevalent sexually transmitted infectious agent worldwide. HPV penetrates the epithelium through microlesions and establishes an infectious focus that can lead to the development of cervical cancer. Prophylactic HPV vaccines are available, but do not affect already-established infections. Using in silico prediction tools is a promising strategy for identifying and selecting vaccine candidate T cell epitopes. An advantage of this strategy is that epitopes can be selected according to the degree of conservation within a group of antigenic proteins. This makes achieving comprehensive genotypic coverage possible with a small set of epitopes. Therefore, this paper revises the general characteristics of HPV biology and the current knowledge on developing therapeutic peptide vaccines against HPV-related infections and cervical cancer.

Epitope mapping of Acinetobacter baumannii outer membrane protein W (OmpW) and laboratory study of an OmpW-derivative peptide

Outer membrane protein W (OmpW) is a less-known A. baumannii antigen with potential immunogenic properties. The epitopes of this protein are not well-identified yet. Therefore, in the present study, B- and T-cell epitopes of A. baumannii OmpW were found using comprehensive in silico and partially in vitro studies. The T-cell (both class-I and class-II) and B-cell (both linear and conformational) epitopes were predicted and screened through many bioinformatics approaches including the prediction of IFN-γ production, immunogenicity, toxicity, allergenicity, human similarity, and clustering. A single 15-mer epitopic peptide containing a linear B-cell and both classes of T-cell epitopes were found and used for further assays. For in vitro assays, patient- and healthy control-derived peripheral blood mononuclear cells were stimulated with the 15-mer peptide, Phytohemagglutinin, or medium alone, and cell proliferation and IFN-γ production assays were performed. The bioinformatics studies led to mapping OmpW epitopes and introducing a 15-mer peptide. In vitro assays to some extent showed its potency in cell proliferation but not in IFN-γ induction, although the responses were not very expressive and faced some questions/limitations. In general, in the current study, we mapped the most immunogenic epitopes of OmpW that may be used for future studies and also assayed one of these epitopes in vitro, which was shown to have an immunogenicity potential. However, the induced immune responses were not strong which suggests that the present peptide needs a series of biotechnological manipulations to be used as a potential vaccine candidate. More studies in this field are recommended.

Computational and Experimental Evaluation of the Immune Response of Neoantigens for Personalized Vaccine Design

In the last few years, the importance of neoantigens in the development of personalized antitumor vaccines has increased remarkably. In order to study whether bioinformatic tools are effective in detecting neoantigens that generate an immune response, DNA samples from patients with cutaneous melanoma in different stages were obtained, resulting in a total of 6048 potential neoantigens gathered. Thereafter, the immunological responses generated by some of those neoantigens ex vivo were tested, using a vaccine designed by a new optimization approach and encapsulated in nanoparticles. Our bioinformatic analysis indicated that no differences were found between the number of neoantigens and that of non-mutated sequences detected as potential binders by IEDB tools. However, those tools were able to highlight neoantigens over non-mutated peptides in HLA-II recognition (p-value 0.03). However, neither HLA-I binding affinity (p-value 0.08) nor Class I immunogenicity values (p-value 0.96) indicated significant differences for the latter parameters. Subsequently, the new vaccine, using aggregative functions and combinatorial optimization, was designed. The six best neoantigens were selected and formulated into two nanoparticles, with which the immune response ex vivo was evaluated, demonstrating a specific activation of the immune response. This study reinforces the use of bioinformatic tools in vaccine development, as their usefulness is proven both in silico and ex vivo.

Tracing the recent updates on vaccination approaches and significant adjuvants being developed against HIV

INTRODUCTION

Human Immunodeficiency Virus type 1 (HIV1); the causative agent of Acquired Immunodeficiency Syndrome (AIDS), has been a major target of the scientific community to develop an anti-viral therapy. Some successful discoveries have been made during the last two decades in the form of availability of antiviral therapy in endemic regions. Nevertheless, a total cure and safety vaccine has not yet been designed to eradicate HIV from the world.

AREAS COVERED

The purpose of this comprehensive study is to compile recent data regarding therapeutic interventions against HIV and to determine future research needs in this field. A systematic research strategy has been used to gather data from recent, most advanced published electronic sources. Literature based results show that experiments at the invitro level and animal models are continuously in research annals and are providing hope for human trials.

EXPERT OPINION

There is still a gap and more work is needed in the direction of modern drug and vaccination designs. Moreover coordination is necessary among researchers, educationists, public health workers, and the general community to communicate and coordinate the repercussions associated with the deadly disease. It is important for taking timely measures regarding mitigation and adaptation with HIV in future.

Immunoinformatic-Based Multi-Epitope Vaccine Design for Co-Infection of Mycobacterium tuberculosis and SARS-CoV-2

(1) Background: Many co-infections of Mycobacterium tuberculosis (MTB) and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have emerged since the occurrence of the SARS-CoV-2 pandemic. This study aims to design an effective preventive multi-epitope vaccine against the co-infection of MTB and SARS-CoV-2. (2) Methods: The three selected proteins (spike protein, diacylglycerol acyltransferase, and low molecular weight T-cell antigen TB8.4) were predicted using bioinformatics, and 16 epitopes with the highest ranks (10 helper T lymphocyte epitopes, 2 CD8⁺ T lymphocytes epitopes, and 4 B-cell epitopes) were selected and assembled into the candidate vaccine referred to as S7D5L4. The toxicity, sensitization, stability, solubility, antigenicity, and immunogenicity of the S7D5L4 vaccine were evaluated using bioinformatics tools. Subsequently, toll-like receptor 4 docking simulation and discontinuous B-cell epitope prediction were performed. Immune simulation and codon optimization were carried out using immunoinformatics and molecular biology tools. (3) Results: The S7D5L4 vaccine showed good physical properties, such as solubility, stability, non-sensitization, and non-toxicity. This vaccine had excellent antigenicity and immunogenicity and could successfully simulate immune responses in silico. Furthermore, the normal mode analysis of the S7D5L4 vaccine and toll-like receptor 4 docking simulation demonstrated that the vaccine had docking potential and a stable reaction. (4) Conclusions: The S7D5L4 vaccine designed to fight against the co-infection of MTB and SARS-CoV-2 may be safe and effective. The protective efficacy of this promising vaccine should be further verified using in vitro and in vivo experiments.

Integration of immunoinformatics and cheminformatics to design and evaluate a multitope vaccine against Klebsiella pneumoniae and Pseudomonas aeruginosa coinfection

Introduction: Klebsiella pneumoniae (K. pneumoniae) and Pseudomonas aeruginosa (P. aeruginosa) are the most common Gram-negative bacteria associated with pneumonia and coinfecting the same patient. Despite their high virulence, there is no effective vaccine against them. Methods: In the current study, the screening of several proteins from both pathogens highlighted FepA and OmpK35 for K. pneumonia in addition to HasR and OprF from P. aeruginosa as promising candidates for epitope mapping. Those four proteins were linked to form a multitope vaccine, that was formulated with a suitable adjuvant, and PADRE peptides to finalize the multitope vaccine construct. The final vaccine's physicochemical features, antigenicity, toxicity, allergenicity, and solubility were evaluated for use in humans. Results: The output of the computational analysis revealed that the designed multitope construct has passed these assessments with satisfactory scores where, as the last stage, we performed a molecular docking study between the potential vaccine construct and K. pneumonia associated immune receptors, TLR4 and TLR2, showing affinitive to both targets with preferentiality for the TLR4 receptor protein. Validation of the docking studies has proceeded through molecular dynamics simulation, which estimated a strong binding and supported the nomination of the designed vaccine as a putative solution for K. pneumoniae and P. aeruginosa coinfection. Here, we describe the approach for the design and assessment of our potential vaccine.

Computational Clues of Immunogenic Hotspots in Plasmodium falciparum Erythrocytic Stage Vaccine Candidate Antigens: In Silico Approach

Malaria is the most pernicious parasitic infection, and Plasmodium falciparum is the most virulent species with substantial morbidity and mortality worldwide. The present in silico investigation was performed to reveal the biophysical characteristics and immunogenic epitopes of the 14 blood-stage proteins of the P. falciparum using comprehensive immunoinformatics approaches. For this aim, various web servers were employed to predict subcellular localization, antigenicity, allergenicity, solubility, physicochemical properties, posttranslational modification sites (PTMs), the presence of signal peptide, and transmembrane domains. Moreover, structural analysis for secondary and 3D model predictions were performed for all and stable proteins, respectively. Finally, human helper T lymphocyte (HTL) epitopes were predicted using HLA reference set of IEDB server and screened in terms of antigenicity, allergenicity, and IFN-γ induction as well as population coverage. Also, a multiserver B-cell epitope prediction was done with subsequent screening for antigenicity, allergenicity, and solubility. Altogether, these proteins showed appropriate antigenicity, abundant PTMs, and many B-cell and HTL epitopes, which could be directed for future vaccination studies in the context of multiepitope vaccine design.

Mining of Marburg Virus Proteome for Designing an Epitope-Based Vaccine

Marburg virus (MARV) is one of the most harmful zoonotic viruses with deadly effects on both humans and nonhuman primates. Because of its severe outbreaks with a high rate of fatality, the world health organization put it as a risk group 4 pathogen and focused on the urgent need for the development of effective solutions against that virus. However, up to date, there is no effective vaccine against MARV in the market. In the current study, the complete proteome of MARV (seven proteins) was analyzed for the antigenicity score and the virulence or physiological role of each protein where we nominated envelope glycoprotein (Gp), Transcriptional activator (VP30), and membrane-associated protein (VP24) as the candidates for epitope prediction. Following that, a vaccine construct was designed based on CTL, HTL, and BCL epitopes of the selected protein candidates and to finalize the vaccine construct, several amino acid linkers, β-defensin adjuvant, and PADRE peptides were incorporated. The generated potential vaccine was assessed computationally for several properties such as antigenicity, allergenicity, stability, and other structural features where the outcomes of these assessments nominated this potential vaccine to be validated for its binding affinity with two molecular targets TLR-8 and TLR-4. The binding score and the stability of the vaccine-receptor complex, which was deeply studied through molecular docking-coupled dynamics simulation, supported the selection of our designed vaccine as a putative solution for MARV that should be validated through future wet-lab experiments. Here, we describe the computational approach for designing and analysis of this potential vaccine.

In silico Analysis of Peptide-Based Biomarkers for the Diagnosis and Prevention of Latent Tuberculosis Infection

Background

Latent tuberculosis infection (LTBI) is the primary source of active tuberculosis (ATB), but there are no specific methods for diagnosing and preventing LTBI.

Methods

Dominant T and B cell epitopes predicted from five antigens related to LTBI and Mycobacterium tuberculosis region of difference (LTBI-RD) were used to construct a novel polypeptide molecule (PPM). Then, the physicochemical properties, secondary structure, tertiary structure of the PPM, and its binding ability to toll-like receptor 2 (TLR2) and TLR4 were analyzed by bioinformatics tools. Finally, immune stimulation and expression optimization of the PPM were carried out.

Results

Four helper T lymphocytes (HTL) epitopes, five cytotoxic T lymphocytes (CTL) epitopes, and three B cell epitopes were predicted and screened from five LTBI-RD related antigens. These epitopes were connected in series with linkers and adjuvants to construct a novel PPM termed C543P. The results indicated that antigenicity and immunogenicity scores of the C543P candidate were 0.936399 and 1.36469, respectively. The structural analysis results showed that the C543P candidate had good stability. Its secondary structure contained 43.6% α-helix, the Z-score after tertiary structure optimization was −7.9, and the Ramachandran diagram showed that 88.77% amino acid residues of the C543P candidate were in the allowable region. Furthermore, the C543P candidate showed an excellent affinity to TLR2 (−1091.7kcal/mol) and TLR4 (−1102.7kcal/mol). In addition, we also analyzed the immunological characteristics of the C543P candidate. Immune stimulation prediction showed that the C543P candidate could effectively activate T and B lymphocytes and produce high levels of Th1 cytokines such as IFN-γ and IL-2.

Conclusion

We constructed a novel PPM with acceptable antigenicity, immunogenicity, stability, and ability to induce robust immune responses. This study provides a new diagnostic biomarker or peptides-based vaccine for LTBI diagnosis and prevention.

Vaccinomics to Design a Multi-Epitopes Vaccine for Acinetobacter baumannii

Antibiotic resistance (AR) is the result of microbes’ natural evolution to withstand the action of antibiotics used against them. AR is rising to a high level across the globe, and novel resistant strains are emerging and spreading very fast. Acinetobacter baumannii is a multidrug resistant Gram-negative bacteria, responsible for causing severe nosocomial infections that are treated with several broad spectrum antibiotics: carbapenems, β-lactam, aminoglycosides, tetracycline, gentamicin, impanel, piperacillin, and amikacin. The A. baumannii genome is superplastic to acquire new resistant mechanisms and, as there is no vaccine in the development process for this pathogen, the situation is more worrisome. This study was conducted to identify protective antigens from the core genome of the pathogen. Genomic data of fully sequenced strains of A. baumannii were retrieved from the national center for biotechnological information (NCBI) database and subjected to various genomics, immunoinformatics, proteomics, and biophysical analyses to identify potential vaccine antigens against A. baumannii. By doing so, four outer membrane proteins were prioritized: TonB-dependent siderphore receptor, OmpA family protein, type IV pilus biogenesis stability protein, and OprD family outer membrane porin. Immuoinformatics predicted B-cell and T-cell epitopes from all four proteins. The antigenic epitopes were linked to design a multi-epitopes vaccine construct using GPGPG linkers and adjuvant cholera toxin B subunit to boost the immune responses. A 3D model of the vaccine construct was built, loop refined, and considered for extensive error examination. Disulfide engineering was performed for the stability of the vaccine construct. Blind docking of the vaccine was conducted with host MHC-I, MHC-II, and toll-like receptors 4 (TLR-4) molecules. Molecular dynamic simulation was carried out to understand the vaccine-receptors dynamics and binding stability, as well as to evaluate the presentation of epitopes to the host immune system. Binding energies estimation was achieved to understand intermolecular interaction energies and validate docking and simulation studies. The results suggested that the designed vaccine construct has high potential to induce protective host immune responses and can be a good vaccine candidate for experimental in vivo and in vitro studies.

Recent Advances in Vaccine Technology and Design

If up until three years ago, infectious diseases were a lesser concern when compared to non-communicable diseases in Western countries, the ongoing pandemic has reminded us that things are not so clean-cut [...].

In silico designed Staphylococcus aureus B-cell multi-epitope vaccine did not elicit antibodies against target antigens suggesting multi-domain approach

The vaccine development strategies have evolved from using an entire organism as an immunogen to a single antigen and further towards an epitope. Since an epitope is a relatively tiny and immunologically relevant part of an antigen, it has the potential to stimulate more robust and specific immune responses while causing minimal adverse effects. As a result, the recent focus of vaccine development has been to develop multi-epitope vaccines that can target multiple virulence mechanisms. Accordingly, we designed multi-epitope vaccine candidates B (multi-B-cell epitope immunogen) and CTB-B (an adjuvant - cholera toxin subunit B (CTB) - attached to immunogen B) against S. aureus by employing immunoinformatics approaches. The designed vaccines are composed of B-cell epitope segments (20-mer) of the eight well-characterized S. aureus virulence factors, namely ClfB, FnbpA, Hla, IsdA, IsdB, LukE, SdrD, and SdrE connected in series. The designed vaccines were expressed, purified, and administered to C57BL/6 mice with Freund adjuvant to evaluate the immunogenicity and protective efficacy. The results revealed that the immunized mice showed high IgG titer for the immunogen, and the antibody titer increased significantly following the second immunization. However, the generated antibodies did not protect mice from infection. The interaction of anti-B antibodies with source virulence factors showed that the generated antibodies have no binding affinity with any of the corresponding virulence factors. Our results demonstrate the limitation of in silico designed B-cell multi-epitope vaccine and suggest that a protein domain carrying both linear and conformational B-cell epitopes might be a better choice for developing an effective multi-epitope vaccine against S. aureus.

A candidate triple-negative breast cancer vaccine design by targeting clinically relevant cell surface markers: an integrated immuno and bio-informatics approach

Triple-negative breast cancer (TNBC) is an aggressive, metastatic/invasive sub-class of breast cancer (BCa). Cell surface protein-derived multi-epitope vaccine-mediated targeting of TNBC cells could be a better strategy against the disease. Literature-based identified potential cell surface markers for TNBC cells were subjected to expression pattern and survival analysis in BCa patient sample using TCGA database. The cytotoxic and helper T-lymphocytes antigenic epitopes in the test proteins were identified, selected and fused together with the appropriate linkers and an adjuvant, to construct the multi-epitope vaccine (MEV). The immune profile, physiochemical property (PP) and world population coverage of the MEV was studied. Immune simulation, cloning in a suitable vector, molecular docking (against Toll-like receptors, MHC (I/II) molecules), and molecular dynamics simulations of the MEV was performed. Cell surface markers were differentially expressed in TNBC samples and showed poor survival in TNBC patients. Satisfactory PP and WPC (up to 89 and 99%) was observed. MEV significant stable binding with the immune molecules and induced the immune cells in silico. The designed vaccine has capability to elicit immune response which could be utilized to target TNBC alone/combination with other therapy. The experimental studies are required to check the efficacy of the vaccine.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-022-03140-3.

Immunoinformatic Approaches for Vaccine Designing for Pathogens with Unclear Pathogenesis

Designing a vaccine against a pathogen has been the toughest challenge to fight against any infectious diseases. To overcome this problem, use of artificial neural network with immuno-informatics is emerging as a front runner solution. For a successful designing of a potent vaccine, prediction of T-cell/B-cell epitopes, antigen processing and presentation analysis, antigenic potential analysis of epitopes, usages of linkers, population coverage, codon optimization, allergenicity assessment, toxicity prediction of construct, and finally protein-peptide docking for stability of vaccine are important steps. To achieve this, several bioinformatics software, tools and online web servers have been developed for each application, which have their own advantages and limitations. Scientists must evaluate these parameters and should take the decision to apply more suitable and precise servers for each analysis and prediction based on their accuracy, suitability, and robustness.

In Silico Designing of a Multitope Vaccine against Rhizopus microsporus with Potential Activity against Other Mucormycosis Causing Fungi

During the current era of the COVID-19 pandemic, the dissemination of Mucorales has been reported globally, with elevated rates of infection in India, and because of the high rate of mortality and morbidity, designing an effective vaccine against mucormycosis is a major health priority, especially for immunocompromised patients. In the current study, we studied shared Mucorales proteins, which have been reported as virulence factors, and after analysis of several virulent proteins for their antigenicity and subcellular localization, we selected spore coat (CotH) and serine protease (SP) proteins as the targets of epitope mapping. The current study proposes a vaccine constructed based on top-ranking cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B cell lymphocyte (BCL) epitopes from filtered proteins. In addition to the selected epitopes, β-defensins adjuvant and PADRE peptide were included in the constructed vaccine to improve the stimulated immune response. Computational tools were used to estimate the physicochemical and immunological features of the proposed vaccine and validate its binding with TLR-2, where the output data of these assessments potentiate the probability of the constructed vaccine to stimulate a specific immune response against mucormycosis. Here, we demonstrate the approach of potential vaccine construction and assessment through computational tools, and to the best of our knowledge, this is the first study of a proposed vaccine against mucormycosis based on the immunoinformatics approach.

Development of synthetic antigen vaccines for COVID-19

The current pandemic called COVID-19 caused by the SARS-CoV-2 virus brought the need for the search for fast alternatives to both control and fight the SARS-CoV-2 infection. Therefore, a race for a vaccine against COVID-19 took place, and some vaccines have been approved for emergency use in several countries in a record time. Ongoing prophylactic research has sought faster, safer, and precise alternatives by redirecting knowledge of other vaccines, and/or the development of new strategies using available tools, mainly in the areas of genomics and bioinformatics. The current review highlights the development of synthetic antigen vaccines, focusing on the usage of bioinformatics tools for the selection and construction of antigens on the different vaccine constructions under development, as well as strategies to optimize vaccines for COVID-19.

Toxoplasma gondii Tyrosine-Rich Oocyst Wall Protein: A Closer Look through an In Silico Prism

Toxoplasmosis is a global threat with significant zoonotic concern. The present in silico study was aimed at determination of bioinformatics features and immunogenic epitopes of a tyrosine-rich oocyst wall protein (TrOWP) of Toxoplasma gondii. After retrieving the amino acid sequence from UniProt database, several parameters were predicted including antigenicity, allergenicity, solubility and physico-chemical features, signal peptide, transmembrane domain, and posttranslational modifications. Following secondary and tertiary structure prediction, the 3D model was refined, and immunogenic epitopes were forecasted. It was a 25.57 kDa hydrophilic molecule with 236 residues, a signal peptide, and significant antigenicity scores. Moreover, several linear and conformational B-cell epitopes were present. Also, potential mouse and human cytotoxic T-lymphocyte (CTL) and helper T-lymphocyte (HTL) epitopes were predicted in the sequence. The findings of the present in silico study are promising as they render beneficial characteristics of TrOWP to be included in future vaccination experiments.

Proteome Based Approach Defines Candidates for Designing a Multitope Vaccine against the Nipah Virus

Nipah virus is one of the most harmful emerging viruses with deadly effects on both humans and animals. Because of the severe outbreaks, in 2018, the World Health Organization focused on the urgent need for the development of effective solutions against the virus. However, up to date, there is no effective vaccine against the Nipah virus in the market. In the current study, the complete proteome of the Nipah virus (nine proteins) was analyzed for the antigenicity score and the virulence role of each protein, where we came up with fusion glycoprotein (F), glycoprotein (G), protein (V), and protein (W) as the candidates for epitope prediction. Following that, the multitope vaccine was designed based on top-ranking CTL, HTL, and BCL epitopes from the selected proteins. We used suitable linkers, adjuvant, and PADRE peptides to finalize the constructed vaccine, which was analyzed for its physicochemical features, antigenicity, toxicity, allergenicity, and solubility. The designed vaccine passed these assessments through computational analysis and, as a final step, we ran a docking analysis between the designed vaccine and TLR-³ and validated the docked complex through molecular dynamics simulation, which estimated a strong binding and supported the nomination of the designed vaccine as a putative solution for Nipah virus. Here, we describe the computational approach for design and analysis of this vaccine.

The next generation of HCV vaccines: a focus on novel adjuvant development

INTRODUCTION

Considerable efforts have been made to treat and prevent acute and chronic infections caused by the hepatitis C virus (HCV). Current treatments are unable to protect people from reinfection. Hence, there is a need for development of both preventive and therapeutic HCV vaccines. Many vaccine candidates are in development to fight against HCV, but their efficacy has so far proven limited partly due to low immunogenicity.

AREAS COVERED

We explore development of novel and powerful adjuvants to achieve an effective HCV vaccine. The basis for developing strong adjuvants is to understand the innate immunity pathway, which subsequently stimulates humoral and cellular immune responses. We have also investigated immunogenicity of developed adjuvants that have been used in recent studies available in online databases such as PubMed, PMC, ScienceDirect, Google Scholar, etc.

EXPERT OPINION

Adjuvants are used as a part of vaccine formulation to boost vaccine immunogenicity and antigen delivery. Several FDA-approved adjuvants are used in licensed human vaccines. Unfortunately, no adjuvant has yet been proven to boost HCV immune responses to the extent needed for an effective vaccine. One of the promising approaches for developing an effective adjuvant is the combination of various adjuvants to trigger several innate immune responses, leading to activation of adaptive immunity.[Figure: see text].

In silico design and in vitro expression of novel multiepitope DNA constructs based on HIV-1 proteins and Hsp70 T-cell epitopes

Objectives

Epitope-driven vaccines carrying highly conserved and immunodominant epitopes have emerged as promising approaches to overcome human immunodeficiency virus-1 (HIV-1) infection.

Methods

Two multiepitope DNA constructs encoding T cell epitopes from HIV-1 Gag, Pol, Env, Nef and Rev proteins alone and/or linked to the immunogenic epitopes derived from heat shock protein 70 (Hsp70) as an immunostimulatory agent were designed. In silico analyses were applied including MHC-I and MHC-II binding, MHC-I immunogenicity and antigen processing, population coverage, conservancy, allergenicity, toxicity and hemotoxicity. The peptide-MHC-I/MHC-II molecular docking and cytokine production analyses were carried out for predicted epitopes. The selected highly immunogenic T-cell epitopes were then used to design two multiepitope fusion constructs. Next, prediction of the physicochemical and structural properties, B cell epitopes, and constructs-toll-like receptors (TLRs) molecular docking were performed for each construct. Finally, the eukaryotic expression plasmids harboring totally 12 cytotoxic T Lymphocyte (CTL) and 10 helper T lymphocytes (HTL) epitopes from HIV-1 proteins (i.e., pEGFP-N1-gag-pol-env-nef-rev), and linked to 2 CTL and 2 HTL epitopes from Hsp70 (i.e., pEGFP-N1-hsp70-gag-pol-env-nef-rev) were generated and transfected into HEK-293 T cells for evaluating the percentage of multiepitope peptides expression using flow cytometry and western blotting.

Results

The designed DNA constructs could be successfully expressed in mammalian cells. The expression rates of Gag-Pol-Env-Nef-Rev-GFP and Hsp70-Gag-Pol-Env-Nef-Rev-GFP were about 56–60% as the bands of ~ 63 and ~ 72 kDa confirmed in western blotting, respectively.

Conclusion

The combined in silico/in vitro methods indicated two multiepitope constructs can be produced and used as probable effective immunogens for HIV-1 vaccine development.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10529-021-03143-9.

Anticipation of Antigenic Sites for the Goal of Vaccine Designing Against Nipah Virus: An Immunoinformatics Inquisitive Quest

With time, the Nipah virus has been proved as a fatal and dangerous pathogen for humanity. Nipah virus has its origin from bats and severely affects the respiratory as well as neurological organs. Regular outbreaks and unavailability of proper treatment for Nipah virus infection, demands the designing of vaccine for this disease. This prediction study was conducted to explore B cell epitopes from the Nipah virus’s proteome using the immunoinformatics approach. In this curious quest of anticipation of antigenic sites for the Insilico peptide vaccine for the Nipah virus, nine NV-B strain proteins were retrieved for further series of investigations. After sequential refining through immunoinformatics approaches, a total of 26 epitopes was selected to perform molecular modeling and docking. PEPstrMOD and Swiss model, respectively performed 3D modeling of epitopes with their respective alleles. Based on minimum binding energy, four epitopes viz. LHLGNFVRR, LNLSPLIQR, YHNMSPINR and FRRNNAIAF were predicted as promiscuous B cell epitopes. Based on low binding affinity and high population coverage worldwide, epitope LHLGNFVRR was finally selected. Increased Stability of the LHLGNFVRR- HLA DRB_1301 complex during simulation studies exhibit it as the most promising vaccine bidder. So complex of LHLGNFVRR- HLA DRB_1301 has shown most significance result for vaccine and for further validation and confirmation, wet lab and clinical trials can provide the potential of predicted peptides for the subunit vaccine.

Computational evaluation of anticipated PE_PGRS39 protein involvement in host-pathogen interplay and its integration into vaccine development

Mycobacterium tuberculosis causes more than 1 million deaths every year, which is higher than any other bacterial pathogen. Its success depends on its interaction with the host and its ability to regulate the host's immune system for its own survival. Mycobacterium tuberculosis H37Rv (Mtb) proteome consists of unique PE_PGRS family proteins, which present a significant role in bacterial pathogenesis over the past years. Earlier evidence suggests that some PE_PGRS proteins display fibronectin-binding activity. In this manuscript, computational characterization of the PE_PGRS39 protein has indicated something peculiar about this protein. Investigation showed that PE_PGRS39 is an extracellular protein that, instead of acting as fibronectin-binding protein, might mimic fibronectin which binds to alpha-5 beta-1 (α5β1) integrin. PE_PGRS39 protein additionally turned into proven pieces of evidence to have motifs such as DXXG and GGXGXD and PXXP that bind with guanosine triphosphate (GTP), calcium, and host Src homology 3 (SH3) domains, respectively, in conjunction with RGD-integrin binding. These interactions designate the direct role of PE_PGRS39 in bacterial pathogenesis via cell adhesion and signaling. Additionally, the analysis showed that PE_PGRS39 is an antigenic protein and epitope prediction provided functional regions of the protein that trigger a cellular immune response facilitated by T or B cells. Further, an experimental analysis could also open up new avenues for developing novel drugs by targeting signaling motifs or novel vaccines using functional epitopes that could evoke an immune response in the host.

Probing the Rhipicephalusbursa Sialomes in Potential Anti-Tick Vaccine Candidates: A Reverse Vaccinology Approach

In the wake of the 'omics' explosion of data, reverse vaccinology approaches are being applied more readily as an alternative for the discovery of candidates for next generation diagnostics and vaccines. Promising protective antigens for the control of ticks and tick-borne diseases can be discovered by mining available omics data for immunogenic epitopes. The present study aims to explore the previously obtained Rhipicephalus bursa sialotranscriptome during both feeding and Babesia infection, to select antigenic targets that are either membrane-associated or a secreted protein, as well as unique to the ectoparasite and not present in the mammalian host. Further, they should be capable of stimulating T and B cells for a potential robust immune response, and be non-allergenic or toxic to the host. From the R. bursa transcriptome, 5706 and 3025 proteins were identified as belonging to the surfaceome and secretome, respectively. Following a reverse genetics immunoinformatics pipeline, nine preferred candidates, consisting of one transmembrane-related and eight secreted proteins, were identified. These candidates showed a higher predicted antigenicity than the Bm86 antigen, with no homology to mammalian hosts and exposed regions. Only four were functionally annotated and selected for further in silico analysis, which examined their protein structure, surface accessibility, flexibility, hydrophobicity, and putative linear B and T-cell epitopes. Regions with overlapping coincident epitopes groups (CEGs) were evaluated to select peptides that were further analyzed for their physicochemical characteristics, potential allergenicity, toxicity, solubility, and potential propensity for crystallization. Following these procedures, a set of three peptides from the three R. bursa proteins were selected. In silico results indicate that the designed epitopes could stimulate a protective and long-lasting immune response against those tick proteins, reflecting its potential as anti-tick vaccines. The immunogenicity of these peptides was evaluated in a pilot immunization study followed by tick feeding to evaluate its impact on tick behavior and pathogen transmission. Combining in silico methods with in vivo immunogenicity evaluation enabled the screening of vaccine candidates prior to expensive infestation studies on the definitive ovine host animals.

Immunoinformatics Approach for the Identification and Characterization of T Cell and B Cell Epitopes towards the Peptide-Based Vaccine against SARS-CoV-2

Presently, immunoinformatics is playing a significant role in epitope identification and vaccine designing for various critical diseases. Using immunoinformatics, several scientists are trying to identify and characterize T cell and B cell epitopes as well as design peptide-based vaccine against SARS-CoV-2. In this review article, we have tried to discuss the importance in adaptive immunity and its significance for designing the SARS-CoV-2 vaccine. Moreover, we have attempted to illustrate several significant key points for utilizing immunoinformatics for vaccine designing, such as the criteria for selection and identification of epitopes, T cell epitope, and B cell epitope prediction and different emerging tools/databases for immunoinformatics. In the current scenario, a few immunoinformatics studies have been performed for various infectious pathogens and related diseases. Thus, we have also summarized and included these current immunoinformatics studies in this review article. Finally, we have discussed about the probable T cell and B cell epitopes and their identification and characterization for vaccine designing against SARS-CoV-2.

In Silico and in Vivo Analysis of HIV-1 Rev Regulatory Protein for Evaluation of a Multiepitope-based Vaccine Candidate

In silico-designed multiepitope conserved regions of human immunodeficiency virus 1 (HIV-1) proteins would be a beneficial strategy for antigen design which induces effective anti-HIV-1 T-cell responses. The conserved multiple HLA-DR-binding epitopes of Rev protein were identified using IEDB MHC-I prediction tools and SYFPEITHI webserver to screen potential T-cell epitopes. We analyzed toxicity, allergenicity, immunogenicity, hemolytic activity, cross-reactivity, cell-penetrating peptide (CPP) potency, and molecular docking of the candidate epitopes using several immune-informatics tools. Afterward, we designed a novel multiepitope construct based on non-toxic and non-allergenic Rev, Nef, Gp160 and P24-derived cytotoxic T cell (CTL) and T-helper cell (HTL) epitopes. Next, the designed construct (Nef-Rev-Gp160-P24) was subjected to three B-cell epitope prediction webservers, ProtParam and Protein-Sol to obtain the physicochemical features. Then, the recombinant multiepitope DNA and polypeptide constructs were complexed with different CPPs for nanoparticle formation and pass them via the cell membranes. Finally, the immunogenicity of multiepitope constructs in a variety of modalities was evaluated in mice. The results demonstrated that groups immunized with heterologous DNA+ MPG or HR9 CPP prime/rNef-Rev-Gp160-P24 polypeptide + LDP-NLS CPP boost regimens could significantly produce higher levels of IFN-γ and Granzyme B, and lower amounts of IL-10 than other groups. Moreover, higher levels of IgG2a and IgG2b were observed in all heterologous prime-boost regimens than homologous DNA or polypeptide regimens. Altogether, the present findings indicated that the Nef-Rev-Gp160-P24 polypeptide meets the criteria to be potentially useful as a multiepitope-based vaccine candidate against HIV-1 infection.