Identification of vaccine targets in pathogens and design of a vaccine using computational approaches

Trypanosoma cruzi Tc24 Antigen Expressed and Orally Delivered by Schizochytrium sp. Microalga is Immunogenic in Mice

Chagas disease-caused by the parasite Trypanosoma cruzi-is a neglected tropical disease for which available drugs are not fully effective in the chronic stage and a vaccine is not available yet. Microalgae represent a promising platform for the production and oral delivery of low-cost vaccines. Herein, we report a vaccine prototype against T. cruzi produced in a microalgae platform, based on the candidate antigen Tc24 with a C terminus fusion with the Co1 peptide (Tc24:Co1 vaccine prototype). After modeling the tertiary structure, in silico studies suggested that the chimeric protein is antigenic, not allergenic, and molecular docking indicated binding with Toll-like receptors 2 and 4. Thus, Tc24:Co1 was expressed in the marine microalga Schizochytrium sp., and Western blot confirmed the expression at 48 h after induction, with a yield of 632 µg/L of algal culture (300 μg/g of lyophilized algal cells) as measured by the enzyme-linked immunosorbent assay (ELISA). Upon oral administration of whole-cell Schizochytrium sp. expressing Tc24:Co1 (7.5 µg or 15 µg of Tc24:Co1 doses) in mice, specific serum IgG and intestinal mucosa IgA responses were detected in addition to an increase in serum Th1/Th2 cytokines. In conclusion, Schizochytrium sp.-expressing Tc24:Co1 is a promising oral vaccine prototype to be evaluated in an animal model of Trypanosoma cruzi infection.

A comprehensive comparison of DNA and RNA vaccines

Nucleic acid technology has revolutionized vaccine development, enabling rapid design and production of RNA and DNA vaccines for prevention and treatment of diseases. The successful deployment of mRNA and plasmid DNA vaccines against COVID-19 has further validated the technology. At present, mRNA platform is prevailing due to its higher efficacy, while DNA platform is undergoing rapid evolution because it possesses unique advantages that can potentially overcome the problems associated with the mRNA platform. To help understand the recent performances of the two vaccine platforms and recognize their clinical potentials in the future, this review compares the advantages and drawbacks of mRNA and DNA vaccines that are currently known in the literature, in terms of development timeline, financial cost, ease of distribution, efficacy, safety, and regulatory approval of products. Additionally, the review discusses the ongoing clinical trials, strategies for improvement, and alternative designs of RNA and DNA platforms for vaccination.

Designing a conjugate vaccine targeting Klebsiella pneumoniae ST258 and ST11

Klebsiella pneumoniae (K. pneumoniae) is a common bacterium that can cause iatrogenic infection. Recently, the rise of antibiotic resistance among K. pneumoniae strains is one key factor associated with antibiotic treatment failure. Hencefore, there is an urgent need for effective K. pneumoniae vaccines. This study aimed to design a multi-epitope vaccine (MEV) candidate against K. pneumonia by utilizing an immunoinformatics method. In this study, we obtained 15 cytotoxic T lymphocyte epitopes, 10 helper T lymphocyte epitopes, 6 linear B-cell epitopes, and 2 conformational B-cell epitopes for further research. Then, we designed a multi-epitope vaccine composed of a total of 743 amino acids, containing the epitopes linked by GPGPG flexible links and an EAAAK linker to the Cholera Toxin Subunit B coadjuvant. The observed properties of the MEV, including non-allergenicity, high antigenicity, and hydrophilicity, are noteworthy. The improvements in the tertiary structure through structural refinement and disulfide bonding, coupled with promising molecular interactions revealed by molecular dynamics simulations with TLR4, position the MEV as a strong candidate for further investigation against K. pneumoniae.

mtx-COBRA: Subcellular localization prediction for bacterial proteins

BACKGROUND

Bacteria can have beneficial effects on our health and environment; however, many are responsible for serious infectious diseases, warranting the need for vaccines against such pathogens. Bioinformatic and experimental technologies are crucial for the development of vaccines. The vaccine design pipeline requires identification of bacteria-specific antigens that can be recognized and can induce a response by the immune system upon infection. Immune system recognition is influenced by the location of a protein. Methods have been developed to determine the subcellular localization (SCL) of proteins in prokaryotes and eukaryotes. Bioinformatic tools such as PSORTb can be employed to determine SCL of proteins, which would be tedious to perform experimentally. Unfortunately, PSORTb often predicts many proteins as having an "Unknown" SCL, reducing the number of antigens to evaluate as potential vaccine targets.

METHOD

We present a new pipeline called subCellular lOcalization prediction for BacteRiAl Proteins (mtx-COBRA). mtx-COBRA uses Meta's protein language model, Evolutionary Scale Modeling, combined with an Extreme Gradient Boosting machine learning model to identify SCL of bacterial proteins based on amino acid sequence. This pipeline is trained on a curated dataset that combines data from UniProt and the publicly available ePSORTdb dataset.

RESULTS

Using benchmarking analyses, nested 5-fold cross-validation, and leave-one-pathogen-out methods, followed by testing on the held-out dataset, we show that our pipeline predicts the SCL of bacterial proteins more accurately than PSORTb.

CONCLUSIONS

mtx-COBRA provides an accessible pipeline that can more efficiently classify bacterial proteins with currently "Unknown" SCLs than existing bioinformatic and experimental methods.

Multi-epitopes vaccine design for surface glycoprotein against SARS-CoV-2 using immunoinformatic approach

Background

The recent COVID vaccinations have successfully reduced death and severity but did not stop the transmission of viruses by the emerging SARS-CoV-2 strain. There is a need for better and long-lasting dynamic vaccines for numerous prevailing strains and the evolving SARS-CoV-2 virus, necessitating the development of broad-spectrum strains being used to stop infection by reducing the spread rate and re-infection. The spike (S) glycoprotein is one of the proteins expressed commonly in the early phases of SARS-CoV-2 infection. It has been identified as the most immunogenic protein of SARS-CoV-2.

Methods

In this study, advanced bioinformatics techniques have been exploited to design the novel multi-epitope vaccine using conserved S protein portions from widespread strains of SARS-CoV-2 to predict B cell and T cell epitopes. These epitopes were selected based on toxicity, antigenicity score and immunogenicity. Epitope combinations were used to construct the maximum potent multi-epitope construct with potential immunogenic features. EAAAK, AAY, and GPGPG were used as linkers to construct epitopes.

Results

The developed vaccine has shown positive results. After the chimeric vaccine construct was cloned into the PET28a (+) vector for expression screening in Escherichia coli, the potential expression of the construct was identified.

Conclusion

The construct vaccine performed well in computer-based immune response simulation and covered a variety of allelic populations. These computational results are more helpful for further analysis of our contract vaccine, which can finally help control and prevent SARS-CoV-2 infections worldwide.

Identification and prioritisation of potential vaccine candidates using subtractive proteomics and designing of a multi-epitope vaccine against Wuchereria bancrofti

This study employed subtractive proteomics and immunoinformatics to analyze the Wuchereria bancrofti proteome and identify potential therapeutic targets, with a focus on designing a vaccine against the parasite species. A comprehensive bioinformatics analysis of the parasite's proteome identified 51 probable therapeutic targets, among which "Kunitz/bovine pancreatic trypsin inhibitor domain-containing protein" was identified as the most promising vaccine candidate. The candidate protein was used to design a multi-epitope vaccine, incorporating B-cell and T-cell epitopes identified through various tools. The vaccine construct underwent extensive analysis of its antigenic, physical, and chemical features, including the determination of secondary and tertiary structures. Docking and molecular dynamics simulations were performed with HLA alleles, Toll-like receptor 4 (TLR4), and TLR3 to assess its potential to elicit the human immune response. Immune simulation analysis confirmed the predicted vaccine's strong binding affinity with immunoglobulins, indicating its potential efficacy in generating an immune response. However, experimental validation and testing of this multi-epitope vaccine construct would be needed to assess its potential against W. bancrofti and even for a broader range of lymphatic filarial infections given the similarities between W. bancrofti and Brugia.

Single-residue linear and conformational B cell epitopes prediction using random and ESM-2 based projections

B cell epitope prediction methods are separated into linear sequence-based predictors and conformational epitope predictions that typically use the measured or predicted protein structure. Most linear predictions rely on the translation of the sequence to biologically based representations and the applications of machine learning on these representations. We here present CALIBER 'Conformational And LInear B cell Epitopes pRediction', and show that a bidirectional long short-term memory with random projection produces a more accurate prediction (test set AUC=0.789) than all current linear methods. The same predictor when combined with an Evolutionary Scale Modeling-2 projection also improves on the state of the art in conformational epitopes (AUC = 0.776). The inclusion of the graph of the 3D distances between residues did not increase the prediction accuracy. However, the long-range sequence information was essential for high accuracy. While the same model structure was applicable for linear and conformational epitopes, separate training was required for each. Combining the two slightly increased the linear accuracy (AUC 0.775 versus 0.768) and reduced the conformational accuracy (AUC = 0.769).

Unveiling promising immunogenic targets in Coxiella burnetii through in silico analysis: paving the way for novel vaccine strategies

BACKGROUND

Coxiella burnetii, an intracellular pathogen, serves as the causative agent of zoonotic Q fever. This pathogen presents a significant threat due to its potential for airborne transmission, environmental persistence, and pathogenicity. The current whole-cell vaccine (WCV) utilized in Australia to combat Q fever exhibits notable limitations, including severe adverse reactions and limited regulatory approval for human use. This research employed the reverse vaccinology (RV) approach to uncover antigenic proteins and epitopes of C. burnetii, facilitating the development of more potent vaccine candidates.

METHODS

The potential immunogenic proteins derived from C. burnetii RSA493/Nine Mile phase I (NMI) were extracted through manual, automated RV, and virulence factor database (VFDB) methods. Web tools and bioinformatics were used to evaluate physiochemical attributes, subcellular localization, antigenicity, allergenicity, human homology, B-cell epitopes, MHC I and II binding ratios, functional class scores, adhesion probabilities, protein-protein interactions, and molecular docking.

RESULTS

Out of the 1850 proteins encoded by RSA493/NMI, a subset of 178 demonstrated the potential for surface or membrane localization. Following a series of analytical iterations, 14 putative immunogenic proteins emerged. This collection included nine proteins (57.1%) intricately involved in cell wall/membrane/envelope biogenesis processes (CBU_0197 (Q83EW1), CBU_0311 (Q83EK8), CBU_0489 (Q83E43), CBU_0939 (Q83D08), CBU_1190 (P39917), CBU_1829 (Q83AQ2), CBU_1412 (Q83BU0), CBU_1414 (Q83BT8), and CBU_1600 (Q83BB2)). The CBU_1627 (Q83B86 ) (7.1%) implicated in intracellular trafficking, secretion, and vesicular transport, and CBU_0092 (Q83F57) (7.1%) contributing to cell division. Additionally, three proteins (21.4%) displayed uncharacterized functions (CBU_0736 (Q83DJ4), CBU_1095 (Q83CL9), and CBU_2079 (Q83A32)). The congruent results obtained from molecular docking and immune response stimulation lend support to the inclusion of all 14 putative proteins as potential vaccine candidates. Notably, seven proteins with well-defined functions stand out among these candidates.

CONCLUSIONS

The outcomes of this study introduce promising proteins and epitopes for the forthcoming formulation of subunit vaccines against Q fever, with a primary emphasis on cellular processes and the virulence factors of C. burnetii.

In-silico development of multi-epitope subunit vaccine against lymphatic filariasis

The World Health Organization in 2022 reported that more than 863 million people in 50 countries are at risk of developing lymphatic filariasis (LF), a disease caused by parasitic infection. Immune responses to parasites suggest that the development of a prophylactic vaccine against LF is possible. Using a reverse vaccinology approach, the current study identified Trehalose-6-phosphatase (TPP) as a potential vaccine candidate among 15 reported vaccine antigens for B. malayi. High-ranking B and T-cell epitopes in the Trehalose-6-phosphatase (TPP) were shortlisted using online servers for subsequent analysis. We selected these peptides to construct a vaccine model using I-TASSER and GalaxyRefine server. The vaccine construct showed favorable physicochemical properties, high antigenicity, no allergenicity, no toxicity, and high stability. Structural validation using the Ramachandran plot showed that 98% of the residues were in favorable or mostly allowed regions. Molecular docking and simulation showed a strong binding affinity and stability of the subunit vaccine with toll-like receptor 4 (TLR4). Furthermore, the subunit vaccine showed a strong IgG/IgM response, with the disappearance of the antigen. We propose that our vaccine construct should be further evaluated using cellular and animal models to develop a vaccine that is safe and effective against LF.Communicated by Ramaswamy H. Sarma.

Exploring structural antigens of yellow fever virus to design multi-epitope subunit vaccine candidate by utilizing an immuno-informatics approach

BACKGROUND

Yellow fever is a mosquito-borne viral hemorrhagic disease transmitted by several species of virus-infected mosquitoes endemic to tropical regions of Central and South America and Africa. Earlier in the twentieth century, mass vaccination integrated with mosquito control was implemented to eradicate the yellow fever virus. However, regular outbreaks occur in these regions which pose a threat to travelers and residents of Africa and South America. There is no specific antiviral therapy, but there can be an effective peptide-based vaccine candidate to combat infection caused by the virus. Therefore, the study aims to design a multi-epitope-based subunit vaccine (MESV) construct against the yellow fever virus to reduce the time and cost using reverse vaccinology (RV) approach.

METHODS

Yellow fever virus contains 10,233 nucleotides that encode for 10 proteins (C, prM, E, NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5) including 3 structural and 7 non-structural proteins. Structural proteins-precursor membrane protein (prM) and envelope protein (E)-were taken as a target for B cell and T cell epitope screening. Further, various immunoinformatics approaches were employed to FASTA sequences of structural proteins to retrieve B cell and T cell epitopes. MESV was constructed from these epitopes based on allergenicity, antigenicity and immunogenicity, toxicity, conservancy, and population coverage followed by structure prediction. The efficacy of the MESV construct to bind with human TLR-3, TLR-4, and TLR-8 were evaluated using molecular docking and simulation studies. Finally, in-silico cloning of vaccine construct was performed withpBR322 Escherichia coli expression system using codon optimization.

RESULTS

Predicted epitopes evaluated and selected for MESV construction were found stable, non-allergenic, highly antigenic, and global population coverage of 68.03% according to in-silico analysis. However, this can be further tested in in-vitro and in-vivo investigations. Epitopes were sequentially merged to construct a MESV consisting of 393 amino acids using adjuvant and linkers. Molecular docking and simulation studies revealed stable and high-affinity interactions. Furthermore, in-silico immune response graphs showed effective immune response generation. Finally, higher CAI value ensured high gene expression of vaccine in the host cell.

CONCLUSION

The designed MESV construct in the present in-silico study can be effective in generating an immune response against the yellow fever virus. Therefore, to prevent yellow fever, it can be an effective vaccine candidate. However, further downstream, in-vitro study is required.

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 based analysis of circulating SARS-CoV-2 variants: approach to a universal vaccine candidate

The discovery of the first infectious variant in Wuhan, China, in December 2019, has posed concerns over global health due to the spread of COVID-19 and subsequent variants. While the majority of patients experience flu-like symptoms such as cold and fever, a small percentage, particularly those with compromised immune systems, progress from mild illness to fatality. COVID-19 is caused by a RNA virus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Our approach involved utilizing immunoinformatic to identify vaccine candidates with multiple epitopes and ligand-binding regions in reported SARS-CoV-2 variants. Through analysis of the spike glycoprotein, we identified dominant epitopes for T-cells and B-cells, resulting in a vaccine construct containing two helper T-cell epitopes, six cytotoxic T-cell epitopes, and four linear B-cell epitopes. Prior to conjugation with adjuvants and linkers, all epitopes were evaluated for antigenicity, toxicity, and allergenicity. Additionally, we assessed the vaccine Toll-Like Receptors complex (2, 3, and 4). The vaccine construct demonstrated antigenicity, non-toxicity, and non-allergenicity, thereby enabling the host to generate antibodies with favorable physicochemical characteristics. Furthermore, the 3D structure of the B-cell construct exhibited a ProSA-web z-score plot with a value of -1.71, indicating the reliability of the designed structure. The Ramachandran plot analysis revealed that 99.6% of the amino acid residues in the vaccine subunit were located in the high favored observation region, further establishing its strong candidacy as a vaccination option.

Putative novel outer membrane antigens multi-epitope DNA vaccine candidates identified by Immunoinformatic approaches to control Acinetobacter baumannii

Multi-epitope polypeptide vaccines, a fusion protein, often have a string-of-beads system composed of various specific peptide epitopes, potential adjuvants, and linkers. When choosing the sequence of various segments and linkers, many alternatives are available. These variables can influence the vaccine's effectiveness through their effects on physicochemical properties and polypeptide tertiary structure.The most conserved antigens were discovered using BLASTn. To forecast the proteins' subcellular distribution, PSORTb 3.0.2 was used. Vaxign was used for the preliminary screening and antigenicity assessment. Protein solubility was also predicted using the ccSOL omics. Using PRED-TMBB, it was anticipated that the protein would localize across membranes. The IEDB and BepiPred-2.0 databases were used to predict the immunogenicity of B cell epitopes. A multi-epitope construct was developed and analyzed to evaluate. Twenty epitopes from A. baumannii's outer membrane protein (omp) were included in the vaccination. TLR4 agonist explosibility was investigated. The physicochemical characteristics, secondary and tertiary structures, and B-cell epitopes of vaccine constructs were assessed. Additionally, docking and MD experiments were used to examine the relationship between TLR4 and its agonist.Thirteen antigens were discovered, and eight of the 13 chosen proteins were predicted to be surface proteins. The 34 kDa outer membrane protein, Omp38, Omp W, CarO, putative porin, OmpA, were chosen as having the right antigenicity (≥0.5). FhuE and CdiA were eliminated from further study because of their low antigenicity. The vaccine design was developed by combining the most effective 10 B-cell and 10 MHC-I/MHCII combined coverage epitopes. The molecular formula of the vaccine was determined to be C1718H2615N507O630S17. The vaccine form has a molecular weight of 40,996.70 Da and 47 negatively charged residues (Asp + Glu), whereas 28 positively charged residues (Arg + Lys). The estimated half-life was 7.2 hours (mammalian reticulocytes, in vitro), > 20 hours (yeast, in vivo) and > 10 hours (Escherichia coli, in vivo) for the vaccine. The multi-epitope vaccine insertion is carried via the expression vector pcDNA3.1 (+).The multi-epitope vaccine may stimulate humoral and cellular immune responses, according to our findings, and it may be a candidate for an A. baumannii vaccine.

An In Silico Multi-epitopes Vaccine Ensemble and Characterization Against Nosocomial Proteus penneri

Proteus penneri (P. penneri) is a bacillus-shaped, gram-negative, facultative anaerobe bacterium that is primarily an invasive pathogen and the etiological agent of several hospital-associated infections. P. penneri strains are naturally resistant to macrolides, amoxicillin, oxacillin, penicillin G, and cephalosporins; in addition, no vaccines are available against these strains. This warrants efforts to propose a theoretical based multi-epitope vaccine construct to prevent pathogen infections. In this research, reverse vaccinology bioinformatics and immunoinformatics approaches were adopted for vaccine target identification and construction of a multi-epitope vaccine. In the first phase, a core proteome dataset of the targeted pathogen was obtained using the NCBI database and subjected to bacterial pan-genome analysis using bacterial pan-genome analysis (BPGA) to predict core protein sequences which were then used to find good vaccine target candidates. This identified two proteins, Hcp family type VI secretion system effector and superoxide dismutase family protein, as promising vaccine targets. Afterward using the IEDB database, different B-cell and T-cell epitopes were predicted. A set of four epitopes "KGSVNVQDRE, NTGKLTGTR, IIHSDSWNER, and KDGKPVPALK" were chosen for the development of a multi-epitope vaccine construct. A 183 amino acid long vaccine design was built along with "EAAAK" and "GPGPG" linkers and a cholera toxin B-subunit adjuvant. The designed vaccine model comprised immunodominant, non-toxic, non-allergenic, and physicochemical stable epitopes. The model vaccine was docked with MHC-I, MHC-II, and TLR-4 immune cell receptors using the Cluspro2.0 web server. The binding energy score of the vaccine was - 654.7 kcal/mol for MHC-I, - 738.4 kcal/mol for MHC-II, and - 695.0 kcal/mol for TLR-4. A molecular dynamic simulation was done using AMBER v20 package for dynamic behavior in nanoseconds. Additionally, MM-PBSA binding free energy analysis was done to test intermolecular binding interactions between docked molecules. The MM-GBSA net binding energy score was - 148.00 kcal/mol, - 118.00 kcal/mol, and - 127.00 kcal/mol for vaccine with TLR-4, MHC-I, and MHC-II, respectively. Overall, these in silico-based predictions indicated that the vaccine is highly promising in terms of developing protective immunity against P. penneri. However, additional experimental validation is required to unveil the real immune response to the designed vaccine.

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.

Assessment of the Immunoprotective Efficacy of Recombinant 14-3-3 Protein and Dense Granule Protein 10 (GRA10) as Candidate Antigens for Rabbit Vaccines against Eimeria intestinalis

Eimeria intestinalis infects rabbits, causing severe intestinal coccidiosis. Prolonged anticoccidial drug use might lead to coccidia resistance and drug residues in food. Thus, vaccines are required to control rabbit coccidiosis. In this study, recombinant E. intestinalis 14-3-3 and GRA10 proteins (rEi-14-3-3 and rEi-GRA10) were obtained via prokaryotic expression and used as recombinant subunit vaccines. Fifty 30-day-old rabbits were randomly grouped as follows: PBS-uninfected group, PBS-infected group, Trx-His-S control group, and rEi-14-3-3 and rEi-GRA10 immunized groups. The rabbits were subcutaneously immunized twice at 2-week intervals, challenged with 7 × 104 sporulated oocysts, and sacrificed 14 days later. The protective effects were assessed via clinical signs, relative weight gain, oocyst reduction, mean intestinal lesion score, ACI (anticoccidial index), cytokine, and specific antibody levels in sera. The rEi-14-3-3 and rEi-GRA10 groups had higher relative weight gain rates of 81.94% and 73.61% (p < 0.05), and higher oocyst reduction rates of 86.13% and 84.87% (p < 0.05), respectively. The two immunized groups had fewer intestinal lesions (p < 0.05) and higher IgG levels (p < 0.05). Higher levels of IL-2, IL-4, and IFN-γ cytokines in the rEi-14-3-3 group (p < 0.05) and a higher level of IFN-γ in the rEi-GRA10 group (p < 0.05) were observed. The ACI values of the rEi-14-3-3 and rEi-GRA10 groups were 168.24 and 159.91, with good and moderate protective effects, respectively. Both rEi-14-3-3 and rEi-GRA10 induced humoral immunity in the rabbits. In addition, rEi-14-3-3 induced Th1- and Th2-type immune responses. Both recombinant proteins were protective against E. intestinalis infection in rabbits, with rEi-14-3-3 showing a better protective effect.

Designing a novel chimeric multi-epitope vaccine subunit against Staphylococcus argenteus through artificial intelligence approach integrating pan-genome analysis, in vitro identification, and immunogenicity profiling

Staphylococcus argenteus is a newly identified pathogen that causes respiratory tract infections, skin infections, such as cellulitis, abscesses, and impetigo, and currently, there is no licensed vaccine available against it. To develop a vaccine against S. argenteus, a bacterial pan-genome analysis was applied to identify potential vaccine candidates. A total of 4908 core proteins were retrieved and utilized for identifying four proteins, including SG38 Panton-Valentine leukocidin LukS-PV protein, SG62 staphylococcal enterotoxin type A protein, SG39 enterotoxin B protein, and SG43 enterotoxin type C3 protein as potential vaccine candidates. Epitopes were predicted for these proteins using different types of B and T-cell epitope prediction tools, and only those with a non-toxic profile, antigenic, non-allergenic, and immunogenic were selected. The selected epitopes were linked to each other to form a multi-epitope vaccine construct, which was further linked to the PADRE sequence (AKFVAAWTLKAAA) and 50s ribosomal L7/L12 protein to enhance the vaccine's antigenicity. The three-dimensional structure of the vaccine construct was assessed to determine its binding affinity with key Toll-like receptor 9 (TLR-9) and Toll-like receptor 5 (TLR-5) immune cell receptors. Our findings demonstrate that the vaccine exhibits favorable binding interactions with these immune cell receptors, indicating its potential efficacy. Molecular dynamic simulations further confirmed the accessibility of vaccine epitopes to the host immune system, substantiating its ability to elicit protective immune responses. Taken together, this study highlights the promising candidacy of the modeled vaccine construct for future in vivo and in vitro experimental investigations.Communicated by Ramaswamy H. Sarma.

Development of chimeric protein as a multivalent vaccine for human Kinetoplastid infections: Chagas disease and leishmaniasis

Leishmania spp. and Trypanosoma cruzi are parasitic kinetoplastids of great medical and epidemiological importance since they are responsible for thousands of deaths and disability-adjusted life-years annually, especially in low- and middle-income countries. Despite efforts to minimize their impact, current prevention measures have failed to fully control their spread. There are still no vaccines available. Taking into account the genetic similarity within the Class Kinetoplastida, we selected CD8+ T cell epitopes preserved among Leishmania spp. and T. cruzi to construct a multivalent and broad-spectrum chimeric polyprotein vaccine. In addition to inducing specific IgG production, immunization with the vaccine was able to significantly reduce parasite burden in the colon, liver and skin lesions from T. cruzi, L. infantum and L. mexicana challenged mice, respectively. These findings were supported by histopathological analysis, which revealed decreased inflammation in the colon, a reduced number of degenerated hepatocytes and an increased proliferation of connective tissue in the skin lesions of the corresponding T. cruzi, L. infantum and L. mexicana vaccinated and challenged mice. Collectively, our results support the protective effect of a polyprotein vaccine approach and further studies will elucidate the immune profile associated with this protection. Noteworthy, our results act as conceptual proof that a single multi-kinetoplastida vaccine can be used effectively to control different infectious etiologies, which in turn can have a profound impact on the development of a new generation of vaccines.

Comparative evaluation of protective immunity against Francisella tularensis induced by subunit or adenovirus-vectored vaccines

Tularemia is a highly contagious disease caused by infection with Francisella tularensis (Ft), a pathogenic intracellular gram-negative bacterium that infects a wide range of animals and causes severe disease and death in people, making it a public health concern. Vaccines are the most effective way to prevent tularemia. However, there are no Food and Drug Administration (FDA)-approved Ft vaccines thus far due to safety concerns. Herein, three membrane proteins of Ft, Tul4, OmpA, and FopA, and a molecular chaperone, DnaK, were identified as potential protective antigens using a multifactor protective antigen platform. Moreover, the recombinant DnaK, FopA, and Tul4 protein vaccines elicited a high level of IgG antibodies but did not protect against challenge. In contrast, protective immunity was elicited by a replication-defective human type 5 adenovirus (Ad5) encoding the Tul4, OmpA, FopA, and DnaK proteins (Ad5-Tul4, Ad5-OmpA, Ad5-FopA, and Ad5-DnaK) after a single immunization, and all Ad5-based vaccines stimulated a Th1-biased immune response. Moreover, intramuscular and intranasal vaccination with Ad5-Tul4 using the prime-boost strategy effectively eliminated Ft lung, spleen and liver colonization and provided nearly 80% protection against intranasal challenge with the Ft live vaccine strain (LVS). Only intramuscular, not intranasal vaccination, with Ad5-Tul4 protected mice from intraperitoneal challenge. This study provides a comprehensive comparison of protective immunity against Ft provided by subunit or adenovirus-vectored vaccines and suggests that mucosal vaccination with Ad5-Tul4 may yield desirable protective efficacy against mucosal infection, while intramuscular vaccination offers greater overall protection against intraperitoneal tularemia.

A New Strategy for Mapping Epitopes of LACK and PEPCK Proteins of Leishmania amazonensis Specific for Major Histocompatibility Complex Class I

Leishmaniasis represents a complex of diseases with a broad clinical spectrum and epidemiological diversity, considered a major public health problem. Although there is treatment, there are still no vaccines for cutaneous leishmaniasis. Because Leishmania spp. is an intracellular protozoan with several escape mechanisms, a vaccine must provoke cellular and humoral immune responses. Previously, we identified the Leishmania homolog of receptors for activated C kinase (LACK) and phosphoenolpyruvate carboxykinase (PEPCK) proteins as strong immunogens and candidates for the development of a vaccine strategy. The present work focuses on the in silico prediction and characterization of antigenic epitopes that might interact with mice or human major histocompatibility complex class I. After immunogenicity prediction on the Immune Epitope Database (IEDB) and the Database of MHC Ligands and Peptide Motifs (SYFPEITHI), 26 peptides were selected for interaction assays with infected mouse lymphocytes by flow cytometry and ELISpot. This strategy identified nine antigenic peptides (pL1-H2, pPL3-H2, pL10-HLA, pP13-H2, pP14-H2, pP15-H2, pP16-H2, pP17-H2, pP18-H2, pP26-HLA), which are strong candidates for developing a peptide vaccine against leishmaniasis.

Immunoinformatics design of multi-epitope vaccine using OmpA, OmpD and enterotoxin against non-typhoidal salmonellosis

BACKGROUND

Non-typhoidal Salmonella (NTS) is one of the important bacteria that cause foodborne diseases and invasive infections in children and elderly people. Since NTS infection is difficult to control due to the emergence of antibiotic-resistant species and its adverse effect on immune response, the development of a vaccine against NTS would be necessary. This study aimed to develop a multi-epitope vaccine against the most prevalent serovars of NTS (Salmonella Typhimurium, Salmonella Enteritidis) using an immunoinformatics approach and targeting OmpA, OmpD, and enterotoxin (Stn).

RESULTS

Initially, the B cell and T cell epitopes were predicted. Then, epitopes and suitable adjuvant were assembled by molecular linkers to construct a multi-epitope vaccine. The computational tools predicted the tertiary structure, refined the tertiary structure and validated the final vaccine construct. The effectiveness of the vaccine was evaluated via molecular docking, molecular dynamics simulation, and in silico immune simulation. The vaccine model had good binding affinity and stability with MHC-I, MHC-II, and toll-like receptors (TLR-1, 2, 4) as well as activation of T cells, IgM, IgG, IFN-γ and IL-2 responses. Furthermore, after codon optimization of the vaccine sequence, this sequence was cloned in E. coli plasmid vector pET-30a (+) within restriction sites of HindIII and BamHI.

CONCLUSIONS

This study, for the first time, introduced a multi-epitope vaccine based on OmpA, OmpD and enterotoxin (Stn) of NTS that could stimulate T and B cell immune responses and produced in the prokaryotic system. This vaccine was validated in-silico phase which is an essential study to reduce challenges before in vitro and in vivo studies.

The Low Variability of Tc24 in Trypanosoma cruzi TcI as an Advantage for Chagas Disease Prophylaxis and Diagnosis in Mexico

(1) Background: Chagas disease is the main neglected tropical disease in America. It is estimated that around 6 million people are currently infected with the parasite in Latin America, and 25 million live in endemic areas with active transmission. The disease causes an estimated economic loss of USD 24 billion dollars annually, with a loss of 75,200 working years per year of life; it is responsible for around ~12,000 deaths annually. Although Mexico is an endemic country that recorded 10,186 new cases of Chagas disease during the period of 1990–2017, few studies have evaluated the genetic diversity of genes that could be involved in the prophylaxis and/or diagnosis of the parasite. One of the possible candidates proposed as a vaccine target is the 24 kDa trypomastigote excretory–secretory protein, Tc24, whose protection is linked to the stimulation of T. cruzi-specific CD8+ immune responses. (2) Methods: The aim of the present study was to evaluate the fine-scale genetic diversity and structure of Tc24 in T. cruzi isolates from Mexico, and to compare them with other populations reported in the Americas with the aim to reconsider the potential role of Tc24 as a key candidate for the prophylaxis and improvement of the diagnosis of Chagas disease in Mexico. (3) Results: Of the 25 Mexican isolates analysed, 48% (12) were recovered from humans and 24% (6) recovered from Triatoma barberi and Triatoma dimidiata. Phylogenetic inferences revealed a polytomy in the T. cruzi clade with two defined subgroups, one formed by all sequences of the DTU I and the other formed by DTU II–VI; both subgroups had high branch support. Genetic population analysis detected a single (monomorphic) haplotype of TcI throughout the entire distribution across both Mexico and South America. This information was supported by Nei’s pairwise distances, where the sequences of TcI showed no genetic differences. (4) Conclusions: Given that both previous studies and the findings of the present work confirmed that TcI is the only genotype detected from human isolates obtained from various states of Mexico, and that there is no significant genetic variability in any of them, it is possible to propose the development of in silico strategies for the production of antigens that optimise the diagnosis of Chagas disease, such as quantitative ELISA methods that use this region of Tc24.

The Elusive Trypanosoma cruzi Disperse Gene Protein Family (DGF-1)

Chagas disease, caused by Trypanosoma cruzi infections, is included in the group of neglected diseases, and efforts to develop new therapeutic or immunoprevention approaches have not been successful. After the publication of the T. cruzi genome, the number of molecular and biochemical studies on this parasite has increased considerably, many of which are focused on families of variant surface proteins, especially trans-sialidases, mucins, and mucin-associated proteins. The disperse gene protein 1 family (DGF-1) is one of the most abundant families in the T. cruzi genome; however, the large gene size, high copy numbers, and low antibody titers detected in infected humans make it an unattractive study target. However, here we argue that given the ubiquitous presence in all T. cruzi species, and physicochemical characteristics, the DGF-1 gene family may play and important role in host-parasite interactions.

A Data-Driven Approach to Construct a Molecular Map of Trypanosoma cruzi to Identify Drugs and Vaccine Targets

Chagas disease (CD) is endemic in large parts of Central and South America, as well as in Texas and the southern regions of the United States. Successful parasites, such as the causative agent of CD, Trypanosoma cruzi have adapted to specific hosts during their phylogenesis. In this work, we have assembled an interactive network of the complex relations that occur between molecules within T. cruzi. An expert curation strategy was combined with a text-mining approach to screen 10,234 full-length research articles and over 200,000 abstracts relevant to T. cruzi. We obtained a scale-free network consisting of 1055 nodes and 874 edges, and composed of 838 proteins, 43 genes, 20 complexes, 9 RNAs, 36 simple molecules, 81 phenotypes, and 37 known pharmaceuticals. Further, we deployed an automated docking pipeline to conduct large-scale docking studies involving several thousand drugs and potential targets to identify network-based binding propensities. These experiments have revealed that the existing FDA-approved drugs benznidazole (Bz) and nifurtimox (Nf) show comparatively high binding energies to the T. cruzi network proteins (e.g., PIF1 helicase-like protein, trans-sialidase), when compared with control datasets consisting of proteins from other pathogens. We envisage this work to be of value to those interested in finding new vaccines for CD, as well as drugs against the T. cruzi parasite.

Vaxi-DL: An Artificial Intelligence-Enabled Platform for Vaccine Development

Vaccine development is a complex and long process. It involves several steps, including computational studies, experimental analyses, animal model system studies, and clinical trials. This process can be accelerated by using in silico antigen screening to identify potential vaccine candidates. In this chapter, we describe a deep learning-based technique which utilizes 18 biological and 9154 physicochemical properties of proteins for finding potential vaccine candidates. Using this technique, a new web-based system, named Vaxi-DL, was developed which helped in finding new vaccine candidates from bacteria, protozoa, viruses, and fungi. Vaxi-DL is available at: https://vac.kamalrawal.in/vaxidl/ .

COVID-19 Vaccines: Computational tools and Development

The 2019 coronavirus outbreak, also known as COVID-19, poses a serious threat to global health and has already had widespread, devastating effects around the world. Scientists have been working tirelessly to develop vaccines to stop the virus from spreading as much as possible, as its cure has not yet been found. As of December 2022, 651,918,402 cases and 6,656,601 deaths had been reported. Globally, over 13 billion doses of vaccine have been administered, representing 64.45% of the world's population that has received the vaccine. To expedite the vaccine development process, computational tools have been utilized. This paper aims to analyze some computational tools that aid vaccine development by presenting positive evidence for proving the efficacy of these vaccines to suppress the spread of the virus and for the use of computational tools in the development of vaccines for emerging diseases.

Design of a potential Sema4A-based multi-epitope vaccine to combat triple-negative breast cancer: an immunoinformatic approach

Immunotherapy is revamping the therapeutic strategies for TNBC owing to its higher mutational burden and tumour-associated antigens. One of the most intriguing developments in cancer immunotherapy is the focus on peptide-based cancer vaccines. Thus, the current work aims to develop an efficient peptide-based vaccine against TNBC that targets Sema4A, which has recently been identified as a major regulator of TNBC progression. Initially, the antigenic peptides derived from Sema4A were determined and evaluated based on their capability to provoke immunological responses. The assessed epitopes were then linked with a suitable adjuvant (RpfB and RpfE) and appropriate linkers (AAY, GPGPG, KK and EAAAK) to preclude junctional immunogenicity. Eventually, docking and dynamics simulations are performed against TLR-2, TLR-4, TLR-7 and TLR-9 to assess the interaction between the vaccine construct and TLR receptors, as the TLR signalling pathway is critical in the host immune response. The developed vaccine was then exposed to in silico cloning and immune simulation analysis. The findings suggest that the designed vaccine could potentially evoke significant humoral and cellular immune responses in the intended organism. Considering these outcomes, the final multi-epitope vaccine could be employed to serve as an effective choice for TNBC management and may open new avenues for further studies.

Contriving multi-epitope vaccine ensemble for monkeypox disease using an immunoinformatics approach

The current global outbreak of monkeypox (MPX) disease, caused by Monkeypox virus (MPXV), has resulted in 16 thousand infection cases, five deaths, and has been declared a global health emergency of international concern by the World Health Organization. Given current challenges in the safety of existing vaccines, a vaccine to prevent MPX infection and/or onset of symptoms would significantly advance disease management. In this context, a multi-epitope-based vaccine could be a well-suited approach. Herein, we searched a publicly accessible database (Virus Pathogen Database and Analysis Resource) for MPXV immune epitopes from various antigens. We prioritized a group of epitopes (10 CD8+ T cells and four B-cell epitopes) using a computer-aided technique based on desirable immunological and physicochemical properties, sequence conservation criteria, and non-human homology. Three multi-epitope vaccines were constructed (MPXV-1–3) by fusing finalized epitopes with the aid of appropriate linkers and adjuvant (beta-defensin 3, 50S ribosomal protein L7/L12, and Heparin-binding hemagglutinin). Codon optimization and in silico cloning in the pET28a (+) expression vector ensure the optimal expression of each construct in the Escherichia Coli system. Two and three-dimensional structures of the constructed vaccines were predicted and refined. The optimal binding mode of the construct with immune receptors [Toll-like receptors (TLR2, TLR3, and TLR4)] was explored by molecular docking, which revealed high docking energies of MPXV-1–TLR3 (–99.09 kcal/mol), MPXV-2–TLR3 (–98.68 kcal/mol), and MPXV-3–TLR2 (–85.22 kcal/mol). Conformational stability and energetically favourable binding of the vaccine-TLR2/3 complexes were assessed by performing molecular dynamics simulations and free energy calculations (Molecular Mechanics/Generalized Born Surface Area method). In silico immune simulation suggested that innate, adaptive, and humoral responses will be elicited upon administration of such potent multi-epitope vaccine constructs. The vaccine constructs are antigenic, non-allergen, non-toxic, soluble, topographically exposed, and possess favourable physicochemical characteristics. These results may help experimental vaccinologists design a potent MPX vaccine.

Subtractive genomic analysis for computational identification of putative immunogenic targets against clinical Enterobacter cloacae complex

Background

Enterobacter is a major nosocomial genus of Enterobacteriaceae responsible for a variety of nosocomial infections, particularly in prolonged hospitalized patients in the intensive care units. Since current antibiotics have failed treating colistin- and carbapenem-resistant Enterobacteriaceae, efforts are underway to find suitable alternative strategies. Therefore, this study conducted a reverse vaccinology (RV) to identify novel and putative immunogenic targets using core proteome of 20 different sequence types (STs) of clinical Enterobacter spp. Moreover, we introduced a structural-based approach for exploration of potential vaccine candidates against the Enterobacteriaceae family using their conserved domain analysis.

Results

A number of 2616 core coding sequences (CDSs) were retrieved from 20 clinical strains of Enterobacter spp. with a similarity of ≥ 50%. Nine proteins with a score of ≥ 20 considered as the shortlisted proteins based on the quartile scoring method, including three TonB-dependent receptors, WP_008500981.1, WP_058690971.1 and WP_058679571.1; one YjbH domain-containing protein, WP_110108068.1; three flagellar proteins, WP_088207510.1, WP_033145204.1 and WP_058679632.1; one spore-coat U domain-containing protein, WP_039266612.1; and one DD-metalloendopeptidase family protein, WP_025912449.1. In this study, proteins WP_058690971.1 and WP_110108068.1 were detected as the top candidates with regard to immune stimulation and interactions with TLRs. However, their efficacy is remaining to be evaluated experimentally.

Conclusions

Our investigation introduced common ferrichrome porins with high sequence similarity as potential vaccine candidates against the Enterobacteriaceae family. These proteins belong to the iron acquisition system and possess all criteria of suitable vaccine targets. Therefore, they need to be specifically paid attention for vaccine development against clinically important members of Enterobacteriaceae family.

Towards identification and development of alternative vaccines against pregnancy-associated malaria based on naturally acquired immunity

Pregnant women are particularly susceptible to Plasmodium falciparum malaria, leading to substantial maternal and infant morbidity and mortality. While highly effective malaria vaccines are considered an essential component towards malaria elimination, strides towards development of vaccines for pregnant women have been minimal. The leading malaria vaccine, RTS,S/AS01, has modest efficacy in children suggesting that it needs to be strengthened and optimized if it is to be beneficial for pregnant women. Clinical trials against pregnancy-associated malaria (PAM) focused on the classical VAR2CSA antigen are ongoing. However, additional antigens have not been identified to supplement these initiatives despite the new evidence that VAR2CSA is not the only molecule involved in pregnancy-associated naturally acquired immunity. This is mainly due to a lack of understanding of the immune complexities in pregnancy coupled with difficulties associated with expression of malaria recombinant proteins, low antigen immunogenicity in humans, and the anticipated complications in conducting and implementing a vaccine to protect pregnant women. With the accelerated evolution of molecular technologies catapulted by the global pandemic, identification of novel alternative vaccine antigens is timely and feasible. In this review, we discuss approaches towards novel antigen discovery to support PAM vaccine studies.

The Correlation between Subolesin-Reactive Epitopes and Vaccine Efficacy

Vaccination is an environmentally-friendly alternative for tick control. The tick antigen Subolesin (SUB) has shown protection in vaccines for the control of multiple tick species in cattle. Additionally, recent approaches in quantum vaccinomics have predicted SUB-protective epitopes and the peptide sequences involved in protein−protein interactions in this tick antigen. Therefore, the identification of B-cell−reactive epitopes by epitope mapping using a SUB peptide array could be essential as a novel strategy for vaccine development. Subolesin can be used as a model to evaluate the effectiveness of these approaches for the identification of protective epitopes related to vaccine protection and efficacy. In this study, the mapping of B-cell linear epitopes of SUB from three different tick species common in Uganda (Rhipicephalus appendiculatus, R. decoloratus, and Amblyomma variegatum) was conducted using serum samples from two cattle breeds immunized with SUB-based vaccines. The results showed that in cattle immunized with SUB from R. appendiculatus (SUBra) all the reactive peptides (Z-score > 2) recognized by IgG were also significant (Z-ratio > 1.96) when compared to the control group. Additionally, some of the reactive peptides recognized by IgG from the control group were also recognized in SUB cocktail−immunized groups. As a significant result, cattle groups that showed the highest vaccine efficacy were Bos indicus immunized with a SUB cocktail (92%), and crossbred cattle were immunized with SUBra (90%) against R. appendiculatus ticks; the IgG from these groups recognized overlapping epitopes from the peptide SPTGLSPGLSPVRDQPLFTFRQVGLICERMMKERESQIRDEYDHVLSAKLAEQYDTFVKFTYDQKRFEGATPSYLS (Z-ratio > 1.96), which partially corresponded to a Q38 peptide and the SUB protein interaction domain. These identified epitopes could be related to the protection and efficacy of the SUB-based vaccines, and new chimeras containing these protective epitopes could be designed using this new approach.

In silico based multi-epitope vaccine design against norovirus

Norovirus (NoV) belongs to the Calciviridae family that causes diarrhoea, vomiting, and stomach pain in people who have acute gastroenteritis (AGE). Identifying multi-epitope dependent vaccines for single stranded positive sense viruses such as NoV has been a long due. Although efforts have been in place to look into the candidate epitopes, understanding molecular mimicry and finding new epitopes for inducing immune responses against the T/B-cells which play an important role for the cell-mediated and humoral immunity was not dealt with in great detail. The current study focuses on identifying new epitopes from various databases that were filtered for antigenicity, allergenicity, and toxicity. The adjuvant β-defensin along with different linkers were used for vaccine construction. Further, the binding relationship between the vaccine construct and toll-like immune receptor (TLR3) complex was determined using a molecular docking analysis, followed by molecular dynamics simulation of 100 ns. The vaccine candidate developed expresses good solubility with a score of 0.530, Z-score of -4.39 and molecular docking score of -140.4 ± 12.1. The MD trajectories reveal that there is a stability between TLR3 and the developed vaccine candidate with an average of 0.91 nm RMSD value and also the system highest occupancy H-bond formed between GLU127 of TLR3 and TYR10 of vaccine candidate (61.55%). Four more H-bonds exist with an occupancy of more than 32% between TLR3 and the vaccine candidates which makes it stable. Thus, the multi-epitope based vaccine developed in the present study forms the basis for further experimental investigations to develop a potentially good vaccine against NoV.Communicated by Ramaswamy H. Sarma.

Design of a multi-epitope vaccine candidate against Brucella melitensis

Brucella is a typical facultative intracellular bacterium that can cause zoonotic infections. For Brucella, it is difficult to eliminate with current medical treatment. Therefore, a multi-epitope vaccine (MEV) should be designed to prevent Brucella infection. For this purpose, we applied the reverse vaccinology approach from Omp10, Omp25, Omp31 and BtpB. Finally, we obtained 13 cytotoxic T lymphocyte (CTL) epitopes, 17 helper T lymphocyte (HTL) epitopes, 9 linear B cell epitopes, and 2 conformational B cell epitopes for further study. To keep the protein folded normally, we linked AAY, GPGPG, and KK to CTL epitopes, HTL epitopes, and B cell epitopes, respectively. The N-terminal of the vaccine peptide is supplemented with appropriate adjuvants to enhance immunogenicity. To evaluate its immunogenicity, stability, safety, and feasibility, a final MEV containing 806 amino acids was constructed by linking linkers and adjuvants. In addition, molecular docking and molecular dynamics simulations were performed to verify the affinity and stability of the MEV-TLR4. Then, codon adaptation and in silico cloning studies were carried out to identify the possible codons for expressing the MEV. In animal experiments, the results demonstrated that the MEV had high immunogenicity. Collectively, this study provided a theoretical basis for the development of a Brucella vaccine.

Identification of vaccine targets & design of vaccine against SARS-CoV-2 coronavirus using computational and deep learning-based approaches

An unusual pneumonia infection, named COVID-19, was reported on December 2019 in China. It was reported to be caused by a novel coronavirus which has infected approximately 220 million people worldwide with a death toll of 4.5 million as of September 2021. This study is focused on finding potential vaccine candidates and designing an in-silico subunit multi-epitope vaccine candidates using a unique computational pipeline, integrating reverse vaccinology, molecular docking and simulation methods. A protein named spike protein of SARS-CoV-2 with the GenBank ID QHD43416.1 was shortlisted as a potential vaccine candidate and was examined for presence of B-cell and T-cell epitopes. We also investigated antigenicity and interaction with distinct polymorphic alleles of the epitopes. High ranking epitopes such as DLCFTNVY (B cell epitope), KIADYNKL (MHC Class-I) and VKNKCVNFN (MHC class-II) were shortlisted for subsequent analysis. Digestion analysis verified the safety and stability of the shortlisted peptides. Docking study reported a strong binding of proposed peptides with HLA-A*02 and HLA-B7 alleles. We used standard methods to construct vaccine model and this construct was evaluated further for its antigenicity, physicochemical properties, 2D and 3D structure prediction and validation. Further, molecular docking followed by molecular dynamics simulation was performed to evaluate the binding affinity and stability of TLR-4 and vaccine complex. Finally, the vaccine construct was reverse transcribed and adapted for E. coli strain K 12 prior to the insertion within the pET-28-a (+) vector for determining translational and microbial expression followed by conservancy analysis. Also, six multi-epitope subunit vaccines were constructed using different strategies containing immunogenic epitopes, appropriate adjuvants and linker sequences. We propose that our vaccine constructs can be used for downstream investigations using in-vitro and in-vivo studies to design effective and safe vaccine against different strains of COVID-19.

Vaxi-DL: A web-based deep learning server to identify potential vaccine candidates

The development of a new vaccine is a challenging exercise involving several steps including computational studies, experimental work, and animal studies followed by clinical studies. To accelerate the process, in silico screening is frequently used for antigen identification. Here, we present Vaxi-DL, web-based deep learning (DL) software that evaluates the potential of protein sequences to serve as vaccine target antigens. Four different DL pathogen models were trained to predict target antigens in bacteria, protozoa, fungi, and viruses that cause infectious diseases in humans. Datasets containing antigenic and non-antigenic sequences were derived from known vaccine candidates and the Protegen database. Biological and physicochemical properties were computed for the datasets using publicly available bioinformatics tools. For each of the four pathogen models, the datasets were divided into training, validation, and testing subsets and then scaled and normalised. The models were constructed using Fully Connected Layers (FCLs), hyper-tuned, and trained using the training subset. Accuracy, sensitivity, specificity, precision, recall, and AUC (Area under the Curve) were used as metrics to assess the performance of these models. The models were benchmarked using independent datasets of known target antigens against other prediction tools such as VaxiJen and Vaxign-ML. We also tested Vaxi-DL on 219 known potential vaccine candidates (PVC) from 37 different pathogens. Our tool predicted 175 PVCs correctly out of 219 sequences. We also tested Vaxi-DL on different datasets obtained from multiple resources. Our tool has demonstrated an average sensitivity of 93% and will thus be a useful tool for prioritising PVCs for preclinical studies.

Whole Proteome-Based Therapeutic Targets Annotation and Designing of Multi-Epitope-Based Vaccines against the Gram-Negative XDR-Alcaligenes faecalis Bacterium

This study involved therapeutic targets mining for the extremely drug-resistant bacterial species called Alcaligenes faecalis, which is known to infect humans. The infections caused by this species in different parts of the human body have been linked with a higher degree of resistance to several classes of antibiotics. Meanwhile, alternate therapeutic options are needed to treat these bacterial infections in clinical settings. In the current study, a subtractive proteomics approach was adapted to annotate the whole proteome of Alcaligenes faecalis and prioritize target proteins for vaccine-related therapeutics design. This was followed by targeted protein-specific immune epitope prediction and prioritization. The shortlisted epitopes were further subjected to structural design and in silico validation of putative vaccines against Alcaligenes faecalis. The final vaccine designs were also evaluated for potential interaction analysis with human TLR-2 through molecular docking. Finally, the putative vaccines were subjected to in silico cloning and immune simulation approaches to ensure the feasibility of the target-specific vaccine constructs in further experimental designs.