Immunoinformatics-Aided Design and Evaluation of a Potential Multi-Epitope Vaccine against Klebsiella Pneumoniae

In-silico development of a novel TLR2-mediating multi-epitope vaccine against Mycobacterium tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), still remains one of the leading causes of mortality worldwide. The elusive nature of this pathogen and its ability to develop drug resistance makes it a serious threat to global health. BCG, the only preventive vaccine for TB, has a limited efficacy and provides partial protection against the disease. A new effective recombinant vaccine capable of producing a stronger and more comprehensive immune response is required to address this global threat. In the present study, we adopted an in-silico approach to develop a multi-epitope vaccine by screening 198 "regulatory proteins" of Mtb H37Rv strain. Epitopes generated from these proteins were screened on the basis of antigenicity, cytokine profile, allergenicity, toxicity, conservancy and population coverage. Selected epitopes were docked with predominant MHC alleles that were used to develop a vaccine construct using suitable linkers and adjuvant. The construct was subjected to homology modelling, tertiary structure validation and refinement and was eventually docked with Toll-like receptor 2 receptor. Molecular dynamic simulation studies revealed stable interactions between the vaccine construct and TLR-2 receptor. The construct also displayed a high probability to elicit a protective immune response involving both humoral and cell-mediated components. In conclusion, the findings suggest that the constructed vaccine has the potential to induce a robust immune response against Mtb. However, further in-vitro and in-vivo studies are required to assess the safety, efficacy, and long-term protective effects of the vaccine construct.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-025-00322-8.

Clinical Characteristics, Risk Factors, and Outcomes of Patients With Myocardial Injury due to Klebsiella pneumoniae Bloodstream Infections

Background: Very few studies have characterized patients with myocardial injury due to Klebsiella pneumoniae bloodstream infections (KP-BSI). Our study aimed to investigate the clinical characteristics, risk factors and outcomes of patients with myocardial injury due to KP-BSI. Methods: A double-center retrospective cohort study of patients with KP-BSI was conducted from January 1, 2013 to December 31, 2022. The clinical data was collected by reviewing electronic medical records. Classification of patients with KP-BSI into myocardial injury and nonmyocardial injury groups based on the levels of high-sensitivity cardiac troponin I (hs-cTnI) after 48 h onset of KP-BSI. Results: Patients with myocardial injury due to KP-BSI were generally younger than those without such injuries, with the former presenting a median age of 60 versus 67 in the latter (p < 0.001). Conditions like chronic cardiac insufficiency and chronic pulmonary disease were more prevalent in the myocardial injury cohort (10.0% and 7.1%, respectively) compared to those without myocardial injury (4.7% and 2.6%, respectively; p values 0.002 and 0.001). However, the nonmyocardial injury group had a higher incidence of solid tumors (15.3% vs. 10.4%, p=0.038). Severity assessments like the acute physiology and chronic health evaluation (APACHE) II, the sequential organ failure assessment (SOFA), and the Charlson Comorbidity Index (CCI) all registered higher for the myocardial injury group (all p < 0.001). Similarly, intensive care unit (ICU) admissions, use of mechanical ventilation, and central venous catheter (CVC) placement were notably more common in this group (all p < 0.001). Regarding infection sources, the myocardial injury group had a higher incidence of pneumonia as the cause for KP-BSI (29.8% vs. 15.9%, p < 0.001), whereas liver and biliary tract infections were less frequent compared to their counterparts. Mortality rates at 7, 14, and 28 days, along with in-hospital mortality, were significantly higher for those with myocardial injury (all p < 0.001). Multivariate analysis identified age > 67 [adjusted odds ratio (aOR), 2.32; 95% confidence interval (CI), 1.59-3.38], SOFA score > 6 (aOR, 3.04; 95% CI, 2.10-4.39), mechanical ventilation (aOR, 1.67; 95% CI, 1.15-2.39), and CVC in place (aOR, 1.50; 95% CI, 0.96-2.02) as independent prognostic factors for myocardial injury in KP-BSI. Conclusions: Older age (> 67 years), higher SOFA score (> 6), mechanical ventilation, and CVC in place were found to be significantly associated with an increased risk of myocardial injury. Clinical physicians should be alert to the potential for myocardial injury in elderly critically ill patients, especially those who are on mechanical ventilation and have indwelling CVC, in the event of KP-BSI.

Molecular dynamics simulation based prediction of T-cell epitopes for the production of effector molecules for liver cancer immunotherapy

Liver cancer is the sixth most frequent malignancy and the fourth major cause of deaths worldwide. The current treatments are only effective in early stages of cancer. To overcome the therapeutic challenges and exploration of immunotherapeutic options, broad spectral therapeutic vaccines could have significant impact. Based on immunoinformatic and integrated machine learning tools, we predicted the potential therapeutic vaccine candidates of liver cancer. In this study, machine learning and MD simulation-based approach are effectively used to design T-cell epitopes that aid the immune system against liver cancer. Antigenicity, molecular weight, subcellular localization and expression site predictions were used to shortlist liver cancer associated proteins including AMBP, CFB, CDHR5, VTN, APOBR, AFP, SERPINA1 and APOE. We predicted CD8+ T-cell epitopes of these proteins containing LGEGATEAE, LLYIGKDRK, EDIGTEADV, QVDAAMAGR, HLEARKKSK, HLCIRHEMT, LKLSKAVHK, EQGRVRAAT and CD4+ T-cell epitopes of VLGEGATEA, WVTKQLNEI, VEEDTKVNS, FTRINCQGK, WGILGREEA, LQDGEKIMS, VKFNKPFVF, VRAATVGSL. We observed the substantial physicochemical properties of these epitopes with a significant binding affinity with MHC molecules. A polyvalent construct of these epitopes was designed using suitable linkers and adjuvant indicated significant binding energy (>-10.5 kcal/mol) with MHC class-I and II molecule. Based on in silico cloning, we found the considerable compatibility of this polyvalent construct with the E. coli expression system and the efficiency of its translation in host. The system-level and machine learning based cross validations showed the possible effect of these T-cell epitopes as potential vaccine candidates for the treatment of liver cancer.

In silico design and assessment of a multi-epitope peptide vaccine against multidrug-resistant Acinetobacter baumannii

Acinetobacter baumannii, an opportunistic and notorious nosocomial pathogen, is responsible for many infections affecting soft tissues, skin, lungs, bloodstream, and urinary tract, accounting for more than 722,000 cases annually. Despite the numerous advancements in therapeutic options, no approved vaccine is currently available for this particular bacterium. Consequently, this study focused on creating a rational vaccine design using bioinformatics tools. Three outer membrane proteins with immunogenic potential and properties of good vaccine candidates were used to select epitopes based on good antigenic properties, non-allergenicity, high binding scores, and a low IC50 value. A multi-epitope peptide (MEP) construct was created by sequentially linking the epitopes using suitable linkers. ClusPro 2.0 and C-ImmSim web servers were used for docking analysis with TLR2/TLR4 and immune response respectively. The Ramachandran plot showed an accurate model of the MEP with 100% residue in the most favored and allowed regions. The construct was highly antigenic, stable, non-allergenic, non-toxic, and soluble, and showed maximum population coverage. Additionally, molecular docking demonstrated strong binding between the designed MEP vaccine and TLR2/TLR4. In silico immunological simulations showed significant increases in T-cell and B-cell populations. Finally, codon optimization and in silico cloning were conducted using the pET-28a (+) plasmid vector to evaluate the efficiency of the expression of vaccine peptide in the host organism (Escherichia coli). This designed MEP vaccine would support and accelerate the laboratory work to develop a potent vaccine targeting MDR Acinetobacter baumannii.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00292-3.

Computational strategies in Klebsiella pneumoniae vaccine design: navigating the landscape of in silico insights

The emergence of multidrug-resistant Klebsiella pneumoniae poses a grave threat to global public health, necessitating urgent strategies for vaccine development. In this context, computational tools have emerged as indispensable assets, offering unprecedented insights into klebsiellal biology and facilitating the design of effective vaccines. Here, a review of the application of computational methods in the development of K. pneumoniae vaccines is presented, elucidating the transformative impact of in silico approaches. Through a systematic exploration of bioinformatics, structural biology, and immunoinformatics techniques, the complex landscape of K. pneumoniae pathogenesis and antigenicity was unravelled. Key insights into virulence factors, antigen discovery, and immune response mechanisms are discussed, highlighting the pivotal role of computational tools in accelerating vaccine development efforts. Advancements in epitope prediction, antigen selection, and vaccine design optimisation are examined, highlighting the potential of in silico approaches to update vaccine development pipelines. Furthermore, challenges and future directions in leveraging computational tools to combat K. pneumoniae are discussed, emphasizing the importance of multidisciplinary collaboration and data integration. This review provides a comprehensive overview of the current state of computational contributions to K. pneumoniae vaccine development, offering insights into innovative strategies for addressing this urgent global health challenge.

Exploring the journey: A comprehensive review of vaccine development against Klebsiella pneumoniae

Klebsiella pneumoniae, a prominent nosocomial pathogen, poses a critical global health threat due to its multidrug-resistant (MDR) and hypervirulent strains. This comprehensive review focuses into the complex approaches undertaken in the development of vaccines against K. pneumoniae. Traditional methods, such as whole-cell and ribosomal-based vaccines, are compared with modern strategies, including DNA and mRNA vaccines, and extracellular vesicles (EVs), among others. Each method presents unique advantages and challenges, emphasising the complexity of developing an effective vaccine against this pathogen. Significant advancements in computational tools and artificial intelligence (AI) have revolutionised antigen identification and vaccine design, enhancing the precision and efficiency of developing multiepitope-based vaccines. The review also highlights the potential of glycomics and immunoinformatics in identifying key antigenic components and elucidating immune evasion mechanisms employed by K. pneumoniae. Despite progress, challenges remain in ensuring the safety, efficacy, and manufacturability of these vaccines. Notably, EVs demonstrate promise due to their intrinsic adjuvant properties and ability to elicit robust immune responses, although concerns regarding inflammation and antigen variability persist. This review provides a critical overview of the current landscape of K. pneumoniae vaccine development, stressing the need for continued innovation and interdisciplinary collaboration to address this pressing public health issue. The integration of advanced computational methods and AI holds the potential to accelerate the development of effective immunotherapies, paving the way for novel vaccines against MDR K. pneumoniae.

Deep Intraclonal Analysis for the Development of Vaccines against Drug-Resistant Klebsiella pneumoniae Lineages

Despite its medical relevance, there is no commercial vaccine that protects the population at risk from multidrug-resistant (MDR) Klebsiella pneumoniae infections. The availability of massive omic data and novel algorithms may improve antigen selection to develop effective prophylactic strategies. Up to 133 exposed proteins in the core proteomes, between 516 and 8666 genome samples, of the six most relevant MDR clonal groups (CGs) carried conserved B-cell epitopes, suggesting minimized future evasion if utilized for vaccination. Antigens showed a range of epitopicity, functional constraints, and potential side effects. Eleven antigens, including three sugar porins, were represented in all MDR-CGs, constitutively expressed, and showed limited reactivity with gut microbiota. Some of these antigens had important interactomic interactions and may elicit adhesion-neutralizing antibodies. Synergistic bivalent to pentavalent combinations that address expression conditions, interactome location, virulence activities, and clone-specific proteins may overcome the limiting protection of univalent vaccines. The combination of five central antigens accounted for 41% of all non-redundant interacting partners of the antigen dataset. Specific antigen mixtures represented in a few or just one MDR-CG further reduced the chance of microbiota interference. Rational antigen selection schemes facilitate the design of high-coverage and "magic bullet" multivalent vaccines against recalcitrant K. pneumoniae lineages.

Molecular dynamics simulation and purification of chimeric L1/L2 protein from human papillomavirus type 52 expressed in Escherichia coli BL21 (DE3)

The available prophylactic vaccines for human papillomavirus (HPV) in the market are only effective against specific types of HPV, rendering them ineffective for other types of HPV infections. The objective of this research is to investigate the stability of the recombinant protein constructed, namely chimeric L1/L2 protein from HPV type 52, with improved cross-neutralization ability. The 3D model, predicted using Alphafold, Robetta, I-Tasser, and refined with Galaxy Refinement, is validated using Ramachandran plot analysis. The stability is verified through molecular dynamics simulations, considering parameters such as RMSD, RMSF, Rg, and SASA, where stable conditions are observed. The chimeric L1/L2 protein from HPV type 52 is purified using affinity chromatography, and the His-tag is cleaved using SUMO protease to obtain pure chimeric protein with the size of ~ 55 kDa. Western blot analysis confirms binding to anti-L1 HPV type 52 polyclonal antibody. The obtained vaccine candidate can be utilized as an effective prophylactic vaccine against HPV.

Respiratory tract infections: an update on the complexity of bacterial diversity, therapeutic interventions and breakthroughs

Respiratory tract infections (RTIs) have a significant impact on global health, especially among children and the elderly. The key bacterial pathogens Streptococcus pneumoniae, Haemophilus influenzae, Klebsiella pneumoniae, Staphylococcus aureus and non-fermenting Gram Negative bacteria such as Acinetobacter baumannii and Pseudomonas aeruginosa are most commonly associated with RTIs. These bacterial pathogens have evolved a diverse array of resistance mechanisms through horizontal gene transfer, often mediated by mobile genetic elements and environmental acquisition. Treatment failures are primarily due to antimicrobial resistance and inadequate bacterial engagement, which necessitates the development of alternative treatment strategies. To overcome this, our review mainly focuses on different virulence mechanisms and their resulting pathogenicity, highlighting different therapeutic interventions to combat resistance. To prevent the antimicrobial resistance crisis, we also focused on leveraging the application of artificial intelligence and machine learning to manage RTIs. Integrative approaches combining mechanistic insights are crucial for addressing the global challenge of antimicrobial resistance in respiratory infections.

Comprehensive bioinformatics-based annotation and functional characterization of bovine chymosin protein revealed novel biological insights

Chymosin, an aspartic protease present in the stomachs of young ruminants like cows (bovine), causes milk coagulation and cheese production through the breakdown of κ-casein peptide bonds at the Met105-Phe106 site. Bovine chymosin is first synthesized as a pre-prochymosin that is cleaved to produce the mature chymosin protein. Despite significant strides in research, our understanding of this crucial enzyme remains incomplete. The purpose of this work was to perform in silico evolutionary and functional analysis and to gain unique insights into the structure of this protein. For this, the sequence of Bos taurus chymosin from UniProt database was subjected to various bioinformatics analyses. We found that bovine chymosin is a low molecular weight and hydrophilic protein that has homologs in other Bovidae species. Two active sites of aspartic peptidases, along with a functional domain, were identified. Gene Ontology analysis further confirmed chymosin's involvement in proteolysis and aspartic endopeptidase activity. Potential disordered residues and post-translational modification sites were also uncovered. It was revealed that the secondary structure of bovine chymosin is comprised of beta strands (44.27%), coils (43.65%), and alpha helices (12.07%). A highly optimized 3D structure was also obtained. Moreover, crucial protein-protein interactions were unveiled. Altogether, these findings provide valuable insights that could guide future research on bovine chymosin and its biological roles.

In silico and in vivo Investigations of the Immunoreactivity of Klebsiella pneumoniae OmpA Protein as a Vaccine Candidate

Background

The growing threat of antibiotic resistance and Klebsiella pneumoniae infection in healthcare settings highlights the urgent need for innovative solutions, such as vaccines, to address these challenges. This study sought to assess the potential of using K. pneumoniae outer membrane protein A (OmpA) as a vaccine candidate through both in silico and in vivo analyses.

Methods

The study examined the OmpA protein sequence for subcellular localization, antigenicity, allergenicity, similarity to the human proteome, physicochemical properties, B-cell epitopes, MHC binding sites, tertiary structure predictions, molecular docking, and immune response simulations. The ompA gene was cloned into the pET-28a (+) vector, expressed, purified and confirmed using Western blotting analysis. IgG levels in the serum of the immunized mice were measured using ELISA with dilutions ranging from 1:100 to 1:6400, targeting recombinant outer membrane protein A (rOmpA) and K. pneumoniae ATCC 13883. The sensitivity and specificity of the ELISA method were also assessed.

Results

The bioinformatics analysis identified rOmpA as a promising vaccine candidate. The immunized group demonstrated significant production of specific total IgG antibodies against rOmpA and K. pneumoniae ATCC1 13883, as compared to the control group (p < 0.0001). The titers of antibodies produced in response to bacterial exposure did not show any significant difference when compared to the anti-rOmpA antibodies (p > 0.05). The ELISA test sensitivity was 1:3200, and the antibodies in the serum could accurately recognize K. pneumoniae cells.

Conclusion

This study is a significant advancement in the development of a potential vaccine against K. pneumoniae that relies on OmpA. Nevertheless, additional experimental analyses are required.

Immunoinformatics design of a structural proteins driven multi-epitope candidate vaccine against different SARS-CoV-2 variants based on fynomer

The ideal vaccines for combating diseases that may emerge in the future require more than simply inactivating a few pathogenic strains. This study aims to provide a peptide-based multi-epitope vaccine effective against various severe acute respiratory syndrome coronavirus 2 strains. To design the vaccine, a library of peptides from the spike, nucleocapsid, membrane, and envelope structural proteins of various strains was prepared. Then, the final vaccine structure was optimized using the fully protected epitopes and the fynomer scaffold. Using bioinformatics tools, the antigenicity, allergenicity, toxicity, physicochemical properties, population coverage, and secondary and three-dimensional structures of the vaccine candidate were evaluated. The bioinformatic analyses confirmed the high quality of the vaccine. According to further investigations, this structure is similar to native protein and there is a stable and strong interaction between vaccine and receptors. Based on molecular dynamics simulation, structural compactness and stability in binding were also observed. In addition, the immune simulation showed that the vaccine can stimulate immune responses similar to real conditions. Finally, codon optimization and in silico cloning confirmed efficient expression in Escherichia coli. In conclusion, the fynomer-based vaccine can be considered as a new style in designing and updating vaccines to protect against coronavirus disease.

Al-Abbasi F, M. Alghamdi A, Al-Regaiey K, Ul-Haq A, Kaleem I, Bashir S, Waheed Y. Computational design of experimentally validated multi-epitopes vaccine against hepatitis E virus: An immunological approach

Hepatitis E virus (HEV) is one of the leading acute liver infections triggered by viral hepatitis. Patients infected with HEV usually recover and the annual death rate is negligible. Currently, there is no HEV licensed vaccine available globally. This study was carried out to design a multi-epitope HEV peptide-based vaccine by retrieving already experimentally validated epitopes from ViPR database leading to epitope prioritization. Epitopes selected as potential vaccine candidates were non-allergen, immunogenic, soluble, non-toxic and IFN gamma positive. The epitopes were linked together by AAY linkers and the linker EAAAK was used to join adjuvant with epitopes. Toll-like receptor (TLR)-4 agonist was used as an adjuvant to boost efficacy of the vaccine. Furthermore, codon optimization followed by disulfide engineering was performed to analyse the designed vaccine's structural stability. Computational modeling of the immune simulation was done to examine the immune response against the vaccine. The designed vaccine construct was docked with TLR-3 receptor for their interactions and then subjected to molecular dynamic simulations. The vaccine model was examined computationally towards the capability of inducing immune responses which showed the induction of both humoral and cell mediated immunity. Taken together, our study suggests an In-silico designed HEV based multi-epitope peptide-based vaccine (MEPV) that needs to be examined in the wet lab-based data that can help to develop a potential vaccine against HEV.

Immunoinformatics aided designing of a next generation poly-epitope vaccine against uropathogenic Escherichia coli to combat urinary tract infections

Urinary tract infections (UTIs) are the second most prevalent bacterial infections and uropathogenic Escherichia coli (UPEC) stands among the primary causative agents of UTIs. The usage of antibiotics is the routine therapy being used in various countries to treat UTIs but becoming ineffective because of increasing antibiotic resistance among UPEC strains. Thus, there must be the development of some alternative treatment strategies such as vaccine development against UPEC. In the following study, pan-genomics along with reverse vaccinology approaches is used under the framework of bioinformatics for the identification of core putative vaccine candidates, employing 307 UPEC genomes (complete and draft), available publicly. A total of nine T-cell epitopes (derived from B-cells) of both MHC classes (I and II), were prioritized among three potential protein candidates. These epitopes were then docked together by using linkers (GPGPG and AAY) and an adjuvant (Cholera Toxin B) to form a poly-valent vaccine construct. The chimeric vaccine construct was undergone by molecular modelling, further refinement and energy minimization. We predicted positive results of the vaccine construct in immune simulations with significantly high levels of immune cells. The protein-protein docking analysis of vaccine construct with toll-like receptors predicted efficient binding, which was further validated by molecular dynamics simulation of vaccine construct with TLR-2 and TLR-4 at 120 ns, resulting in stable complexes' conformation throughout the simulation run. Overall, the vaccine construct demonstrated positive antigenic response. In future, this chimeric vaccine construct or the identified epitopes could be experimentally validated for the development of UPEC vaccines against UTIs.Communicated by Ramaswamy H. Sarma.

Design and Assessment of a Novel In Silico Approach for Developing a Next-Generation Multi-Epitope Universal Vaccine Targeting Coronaviruses

In the past two decades, there have been three coronavirus outbreaks that have caused significant economic and health crises. Biologists predict that more coronaviruses may emerge in the near future. Therefore, it is crucial to develop preventive vaccines that can effectively combat multiple coronaviruses. In this study, we employed computational approaches to analyze genetically related coronaviruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants, focusing on the spike glycoprotein as a potential vaccine candidate. By predicting common epitopes, we identified the top epitopes and combined them to create a multi-epitope candidate vaccine. The overall quality of the candidate vaccine was validated through in silico analyses, confirming its antigenicity, immunogenicity, and stability. In silico docking and simulation studies suggested a stable interaction between the multi-epitope candidate vaccine and human toll-like receptor 2 (TLR2). In silico codon optimization and cloning were used to further explore the successful expression of the designed candidate vaccine in a prokaryotic expression system. Based on computational analysis, the designed candidate vaccine was found to be stable and non-allergenic in the human body. The efficiency of the multi-epitope vaccine in triggering effective cellular and humoral immune responses was assessed through immune stimulation, demonstrating that the designed candidate vaccine can elicit specific immune responses against multiple coronaviruses. Therefore, it holds promise as a potential candidate vaccine against existing and future coronaviruses.

Immunoinformatics for Novel Multi-Epitope Vaccine Development in Canine Parvovirus Infections

Canine parvovirus (CPV-2) is one of the most important pathogens of dogs of all ages, causing pandemic infections that are characterized by fatal hemorrhagic enteritis. The CPV-2 vaccine is recommended as a core vaccine for pet animals. Despite the intensive practice of active immunization, CPV-2 remains a global threat. In this study, a multi-epitope vaccine against CPV-2 was designed, targeting the highly conserved capsid protein (VP2) via in silico approaches. Several immunoinformatics methods, such as epitope screening, molecular docking, and simulation were used to design a potential vaccine construct. The partial protein sequences of the VP2 gene of CPV-2 and protein sequences retrieved from the NCBI were screened to predict highly antigenic proteins through antigenicity, trans-membrane-topology screening, an allergenicity assessment, and a toxicity analysis. Homologous VP2 protein sequences typically linked to the disease were identified using NCBI BLAST, in which four conserved regions were preferred. Overall, 10 epitopes, DPIGGKTGI, KEFDTDLKP, GTDPDDVQ, GGTNFGYIG, GTFYFDCKP, NRALGLPP, SGTPTN, LGLPPFLNSL, IGGKTG, and VPPVYPN, were selected from the conserved regions to design the vaccine construct. The molecular docking demonstrated the higher binding affinity of these epitopes with dog leukocyte antigen (DLA) molecules. The selected epitopes were linked with Salmonella enterica flagellin FliC adjuvants, along with the PADRE sequence, by GGS linkers to construct a vaccine candidate with 272 nucleotides. The codon adaptation and in silico cloning showed that the generated vaccine can be expressed by the E. coli strain, K12, and the sequence of the vaccine construct showed no similarities with dog protein. Our results suggest that the vaccine construct might be useful in preventing canine parvoviral enteritis (CPE) in dogs. Further in vitro and in vivo experiments are needed for the validation of the vaccine candidate.

Human T-cell lymphotropic virus type 1 (HTLV-1) proposed vaccines: a systematic review of preclinical and clinical studies

BACKGROUND

Numerous vaccination research experiments have been conducted on non-primate hosts to prevent or control HTLV-1 infection. Therefore, reviewing recent advancements for status assessment and strategic planning of future preventative actions to reduce HTLV-1 infection and its consequences would be essential.

METHODS

MEDLINE, Scopus, Web of Science, and Clinicaltrials.gov were searched from each database's inception through March 27, 2022. All original articles focusing on developing an HTLV-1 vaccine candidate were included.

RESULTS

A total of 47 studies were included. They used a variety of approaches to develop the HTLV-1 vaccine, including DNA-based, dendritic-cell-based, peptide/protein-based, and recombinant vaccinia virus approaches. The majority of the research that was included utilized Tax, Glycoprotein (GP), GAG, POL, REX, and HBZ as their main peptides in order to develop the vaccine. The immunization used in dendritic cell-based investigations, which were more recently published, was accomplished by an activated CD-8 T-cell response. Although there hasn't been much attention lately on this form of the vaccine, the initial attempts to develop an HTLV-1 immunization depended on recombinant vaccinia virus, and the majority of results seem positive and effective for this type of vaccine. Few studies were conducted on humans. Most of the studies were experimental studies using animal models. Adenovirus, Cytomegalovirus (CMV), vaccinia, baculovirus, hepatitis B, measles, and pox were the most commonly used vectors.

CONCLUSIONS

This systematic review reported recent progression in the development of HTLV-1 vaccines to identify candidates with the most promising preventive and therapeutic effects.

Bioinformatics analysis of Omp19 and Omp25 proteins for designing multi-epitope vaccines against Brucella

Brucellosis is a zoonotic disease caused by Brucella. There is no effective vaccine against human brucellosis. Omp19 and Omp25 are the outer membrane proteins of Brucella. They are widely expressed and highly conserved in Brucella and have high immunogenicity. Herein, we aim to identify multi-epitope vaccine candidates based on Omp19 and Omp25. We analyzed the physicochemical properties and protein structure of Omp19 and Omp25, and predicted the corresponding B cell and T cell epitopes using bioinformatics analysis. Omp19 and Omp25 were composed of 177 amino acids and 213 amino acids, respectively. They were both stable hydrophilic proteins. The instability indices were 44.8 and 23, respectively. The hydrophilicity was -0.1 and -0.317, respectively. In the secondary structure of Omp19 and Omp25 proteins, the α-helix accounted for 12.43% and 23.94%, the β-sheet was 18.64% and 23.47%, the β-turn was 6.78% and 4.23%, and the random coil was 62.15% and 48.36%. Finally, 5 B cell epitopes, 3 Th-cell epitopes and 5 CTL cell epitopes of Omp19 protein, and 4 B cell epitopes, 3 Th-cell epitopes, and 5 CTL cell epitopes of Omp25 protein were selected as vaccine candidates. In conclusion, we obtained potential B cell and T cell epitopes of the Brucella outer membrane Omp19 and Omp25 proteins. This lays the foundation for the further design of multi-epitope vaccine of Brucella.

Vaccine development for bacterial pathogens: Advances, challenges and prospects

The advent and use of antimicrobials have played a key role in treating potentially life-threatening infectious diseases, improving health, and saving the lives of millions of people worldwide. However, the emergence of multidrug resistant (MDR) pathogens has been a significant health challenge that has compromised the ability to prevent and treat a wide range of infectious diseases that were once treatable. Vaccines offer potential as a promising alternative to fight against antimicrobial resistance (AMR) infectious diseases. Vaccine technologies include reverse vaccinology, structural biology methods, nucleic acid (DNA and mRNA) vaccines, generalised modules for membrane antigens, bioconjugates/glycoconjugates, nanomaterials and several other emerging technological advances that are offering a potential breakthrough in the development of efficient vaccines against pathogens. This review covers the opportunities and advancements in vaccine discovery and development targeting bacterial pathogens. We reflect on the impact of the already-developed vaccines targeting bacterial pathogens and the potential of those currently under different stages of preclinical and clinical trials. More importantly, we critically and comprehensively analyse the challenges while highlighting the key indices for future vaccine prospects. Finally, the issues and concerns of AMR for low-income countries (sub-Saharan Africa) and the challenges with vaccine integration, discovery and development in this region are critically evaluated.

Computational design of candidate multi-epitope vaccine against SARS-CoV-2 targeting structural (S and N) and non-structural (NSP3 and NSP12) proteins

The COVID-19 pandemic caused by SARS-CoV-2 virus has created a global damage and has exposed the vulnerable side of scientific research towards novel diseases. The intensity of the pandemic is huge, with mortality rates of more than 6 million people worldwide in a span of 2 years. Considering the gravity of the situation, scientists all across the world are continuously attempting to create successful therapeutic solutions to combat the virus. Various vaccination strategies are being devised to ensure effective immunization against SARS-CoV-2 infection. SARS-CoV-2 spreads very rapidly, and the infection rate is remarkably high than other respiratory tract viruses. The viral entry and recognition of the host cell is facilitated by S protein of the virus. N protein along with NSP3 is majorly responsible for viral genome assembly and NSP12 performs polymerase activity for RNA synthesis. In this study, we have designed a multi-epitope, chimeric vaccine considering the two structural (S and N protein) and two non-structural proteins (NSP3 and NSP12) of SARS-CoV-2 virus. The aim is to induce immune response by generating antibodies against these proteins to target the viral entry and viral replication in the host cell. In this study, computational tools were used, and the reliability of the vaccine was verified using molecular docking, molecular dynamics simulation and immune simulation studies in silico. These studies demonstrate that the vaccine designed shows steady interaction with Toll like receptors with good stability and will be effective in inducing a strong and specific immune response in the body.Communicated by Ramaswamy H. Sarma.

Evaluation of biosynthesized silver nanoparticles effects on expression levels of virulence and biofilm-related genes of multidrug-resistant Klebsiella pneumoniae isolates

The emergence of multidrug-resistant (MDR) strains of Klebsiella pneumoniae is associated with high morbidity and mortality due to limited treatment options. This study attempts to biologically synthesize silver nanoparticles (AgNPs) and investigate their effect on expression levels of virulence and biofilm-related genes in clinically isolated K. pneumoniae. In this study, biofilm formation ability, antibiotic resistance pattern, extended-spectrum β-lactamases (ESBLs), and carbapenemases production were investigated for 200 clinical isolates of K. pneumoniae using phenotypic methods. Polymerase chain reaction (PCR) was used to detect virulence and biofilm-related genes, ESBL-encoding genes, and carbapenem resistance genes. AgNPs were synthesized using the bio-reduction method. The antibacterial effects of AgNPs were investigated by microdilution broth. In addition, the cytotoxic effect of AgNPs on L929 fibroblast cell lines was determined. The effects of AgNPs on K. pneumoniae virulence and biofilm-related genes (fimH, rmpA, and mrkA) were determined using quantitative real-time PCR. Thirty percent of the isolates produced a strong biofilm. The highest and lowest levels of resistance were observed against amoxicillin/clavulanic acid (95.4%) and tigecycline (96%), respectively. About 31% of isolates were considered positive for carbapenemases, and 75% of the isolates produced an ESBLs enzyme. Different frequencies of mentioned genes were observed. The synthesized AgNPs had a spherical morphology and varied in size. AgNPs inhibited the growth of MDR K. pneumoniae at 128 µg/ml. In addition, AgNPs downregulated the expression of fimH, rmpA, and mrkA genes by 10, 7, and 14-fold, respectively (p < 0.05), also exerted no cytotoxic effect on L929 fibroblast cell lines. It was revealed that AgNPs lead to a decrease in expression levels of virulence and biofilm-related genes; therefore, it was concluded that AgNPs had an excellent antibacterial effect on MDR K. pneumoniae.

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.

A subunit vaccine against pneumonia: targeting Streptococcus pneumoniae and Klebsiella pneumoniae

Community-acquired pneumonia is primarily caused by Streptococcus pneumoniae and Klebsiella pneumoniae, two pathogens that have high morbidity and mortality rates. This is largely due to bacterial resistance development against current antibiotics and the lack of effective vaccines. The objective of this work was to develop an immunogenic multi-epitope subunit vaccine capable of eliciting a robust immune response against S. pneumoniae and K. pneumoniae. The targeted proteins were the pneumococcal surface proteins (PspA and PspC) and choline-binding protein (CbpA) of S. pneumoniae and the outer membrane proteins (OmpA and OmpW) of K. pneumoniae. Different computational approaches and various immune filters were employed for designing a vaccine. The immunogenicity and safety of the vaccine were evaluated by utilizing many physicochemical and antigenic profiles. To improve structural stability, disulfide engineering was applied to a portion of the vaccine structure with high mobility. Molecular docking was performed to examine the binding affinities and biological interactions at the atomic level between the vaccine and Toll-like receptors (TLR2 and 4). Further, the dynamic stabilities of the vaccine and TLRs complexes were investigated by molecular dynamics simulations. While the immune response induction capability of the vaccine was assessed by the immune simulation study. Vaccine translation and expression efficiency was determined through an in silico cloning experiment utilizing the pET28a(+) plasmid vector. The obtained results revealed that the designed vaccine is structurally stable and able to generate an effective immune response to combat pneumococcal infection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13721-023-00416-3.

In-Silico Designing of a Multi-Epitope Vaccine against SARS-CoV2 and Studying the Interaction of the Vaccine with Alpha, Beta, Delta and Omicron Variants of Concern

BACKGROUND

The sudden appearance of the SARS-CoV2 virus has almost changed the future of vaccine development. There have been many different approaches to vaccination; among them, computational vaccinology in the form of multi-epitope vaccines with excellent immunological properties and minimal contamination or other adverse reactions has emerged as a promising strategy with a lot of room for further study in this area.

OBJECTIVE

Designing a multi-epitope vaccine from the spike protein of SARS-CoV2 based on immunoinformatics and in-silico techniques. Evaluating the binding affinity of the constructed vaccine against the major variants of concern (alpha, beta, delta, and omicron) using docking studies.

METHODS

The potential antigenic, immunogenic, and non-allergic T-cell epitopes were thoroughly explored using IEDB, NetCTL1.2, and NetMHCII pan 3.2 servers. The best suitable linker was identified using the ExPASy Protparam tool and VERIFY 3D. The 3D model of the vaccine was developed by RaptorX and the model was validated using ERRAT, Z-score, and Ramachandran Plot. Docking studies of the vaccine with TLR-2, 3, 4, and 7 and alpha, beta, delta, and omicron variants were performed using HADDOCK 2.4.

RESULTS

The vaccine construct showed good antigenic and immunogenic scores and was non-allergic as well. The model was capable of binding to all four selected Toll-like receptors. Docking scores with variants were also promising.

CONCLUSION

All the variants showed good binding ability with the vaccine construct. Interaction with the alpha variant was found to be the most intense, followed by delta, beta, and omicron.

Identification of a Potential Vaccine against Treponema pallidum Using Subtractive Proteomics and Reverse-Vaccinology Approaches

Syphilis, a sexually transmitted infection, is a deadly disease caused by Treponema pallidum. It is a Gram-negative spirochete that can infect nearly every organ of the human body. It can be transmitted both sexually and perinatally. Since syphilis is the second most fatal sexually transmitted disease after AIDS, an efficient vaccine candidate is needed to establish long-term protection against infections by T. pallidum. This study used reverse-vaccinology-based immunoinformatic pathway subtractive proteomics to find the best antigenic proteins for multi-epitope vaccine production. Six essential virulent and antigenic proteins were identified, including the membrane lipoprotein TpN32 (UniProt ID: O07950), DNA translocase FtsK (UniProt ID: O83964), Protein Soj homolog (UniProt ID: O83296), site-determining protein (UniProt ID: F7IVD2), ABC transporter, ATP-binding protein (UniProt ID: O83930), and Sugar ABC superfamily ATP-binding cassette transporter, ABC protein (UniProt ID: O83782). We found that the multiepitope subunit vaccine consisting of 4 CTL, 4 HTL, and 11 B-cell epitopes mixed with the adjuvant TLR-2 agonist ESAT6 has potent antigenic characteristics and does not induce an allergic response. Before being docked at Toll-like receptors 2 and 4, the developed vaccine was modeled, improved, and validated. Docking studies revealed significant binding interactions, whereas molecular dynamics simulations demonstrated its stability. Furthermore, the immune system simulation indicated significant and long-lasting immunological responses. The vaccine was then reverse-transcribed into a DNA sequence and cloned into the pET28a (+) vector to validate translational activity as well as the microbial production process. The vaccine developed in this study requires further scientific consensus before it can be used against T. pallidum to confirm its safety and efficacy.

Immunoinformatic design of a putative multi-epitope vaccine candidate against Trypanosoma brucei gambiense

Human African trypanosomiasis (HAT) is a neglected tropical disease that is caused by flagellated parasites of the genus Trypanosoma. HAT imposes a significant socio-economic burden on many countries in sub-Saharan Africa and its control is hampered by several drawbacks ranging from the ineffectiveness of drugs, complex dosing regimens, drug resistance, and lack of a vaccine. Despite more than a century of research and investigations, the development of a vaccine to tackle HAT is still challenging due to the complex biology of the pathogens. Advancements in computational modeling coupled with the availability of an unprecedented amount of omics data from different organisms have allowed the design of new generation vaccines that offer better antigenicity and safety profile. One of such new generation approaches is a multi-epitope vaccine (MEV) designed from a collection of antigenic peptides. A MEV can stimulate both cellular and humoral immune responses as well as avoiding possible allergenic reactions. Herein, we take advantage of this approach to design a MEV from conserved hypothetical plasma membrane proteins of Trypanosoma brucei gambiense, the trypanosome subspecies that is responsible for the west and central African forms of HAT. The designed MEV is 402 amino acids long (41.5 kDa). It is predicted to be antigenic, non-toxic, to assume a stable 3D conformation, and to interact with a key immune receptor. In addition, immune simulation foresaw adequate immune stimulation by the putative antigen and a lasting memory. Therefore, the designed chimeric vaccine represents a potential candidate that could be used to target HAT.

Immune epitopes identification and designing of a multi-epitope vaccine against bovine leukemia virus: a molecular dynamics and immune simulation approaches

Background

Bovine leukemia virus (BLV) is an oncogenic delta-retrovirus causing bovine leucosis. Studies on BLV have shown the association with human breast cancer. However, the exact molecular mechanism is neither known nor their appropriate preventative measure to halt the disease initiation and progression. In this study, we designed a multi-epitope vaccine against BLV using a computational analyses.

Methods

Following a rigorous assessment, the vaccine was constructed using the T-cell epitopes from each BLV-derived protein with suitable adjuvant and linkers. Both physicochemistry and immunogenic potency as well as the safeness of the vaccine candidate were assessed. Population coverage was done to evaluate the vaccine probable efficiency in eliciting the immune response worldwide. After homology modeling, the three-dimensional structure was refined and validated to determine the quality of the designed vaccine. The vaccine protein was then subjected to molecular docking with Toll-like receptor 3 (TLR3) to evaluate the binding efficiency followed by dynamic simulation for stable interaction.

Results

Our vaccine construct has the potential immune response and good physicochemical properties. The vaccine is antigenic and immunogenic, and has no allergenic or toxic effect on the human body. This novel vaccine contains a significant interactions and binding affinity with the TLR3 receptor.

Conclusions

The proposed vaccine candidate would be structurally stable and capable of generating an effective immune response to combat BLV infections. However, experimental evaluations are essential to validate the exact safety and immunogenic profiling of this vaccine.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00262-022-03181-w.

A novel strategy for developing vaccine candidate against Jaagsiekte sheep retrovirus from the envelope and gag proteins: an in-silico approach

BACKGROUND

Sheep pulmonary adenocarcinoma (OPA) is a contagious lung cancer of sheep caused by the Jaagsiekte retrovirus (JSRV). OPA typically has a serious economic impact worldwide. A vaccine has yet to be developed, even though the disease has been globally spread, along with its complications. This study aimed to construct an effective multi-epitopes vaccine against JSRV eliciting B and T lymphocytes using immunoinformatics tools.

RESULTS

The designed vaccine was composed of 499 amino acids. Before the vaccine was computationally validated, all critical parameters were taken into consideration; including antigenicity, allergenicity, toxicity, and stability. The physiochemical properties of the vaccine displayed an isoelectric point of 9.88. According to the Instability Index (II), the vaccine was stable at 28.28. The vaccine scored 56.51 on the aliphatic index and -0.731 on the GRAVY, indicating that the vaccine was hydrophilic. The RaptorX server was used to predict the vaccine's tertiary structure, the GalaxyWEB server refined the structure, and the Ramachandran plot and the ProSA-web server validated the vaccine's tertiary structure. Protein-sol and the SOLPro servers showed the solubility of the vaccine. Moreover, the high mobile regions in the vaccine's structure were reduced and the vaccine's stability was improved by disulfide engineering. Also, the vaccine construct was docked with an ovine MHC-1 allele and showed efficient binding energy. Immune simulation remarkably showed high levels of immunoglobulins, T lymphocytes, and INF-γ secretions. The molecular dynamic simulation provided the stability of the constructed vaccine. Finally, the vaccine was back-transcribed into a DNA sequence and cloned into a pET-30a ( +) vector to affirm the potency of translation and microbial expression.

CONCLUSION

A novel multi-epitopes vaccine construct against JSRV, was formed from B and T lymphocytes epitopes, and was produced with potential protection. This study might help in controlling and eradicating OPA.

Immunoinformatics-Aided Analysis of RSV Fusion and Attachment Glycoproteins to Design a Potent Multi-Epitope Vaccine

Respiratory syncytial virus (RSV) usually causes respiratory tract infections of upper airways in infants and young children. Despite recent medical advances, no approved vaccine is available to control RSV infections. Therefore, we conducted an immunoinformatics study to design and evaluate a potential multi-epitope vaccine against RSV. Sequence-based analyses of the glycoproteins F and G revealed a total of eight CD8 T-cell and three CD4 T-cell epitopes after considering antigenicity, binding affinity and other parameters. Molecular docking analysis confirmed that these T-cell epitopes developed strong structural associations with HLA allele(s). By integrating these prioritized epitopes with linkers and a cholera toxin-derived adjuvant, a multi-epitope vaccine was designed. The developed vaccine was found to be stable, non-allergenic, flexible and antigenic. Molecular docking analysis revealed a striking mean HADDOCK score (-143.3) of top-ranked vaccine-TLR cluster and a Gibbs free energy change (ΔG) value of -11.3 kcal mol-1. As per computational immune simulation results, the vaccine generated a high titer of antibodies (especially IgM) and effector T-cells. Also, codon optimization and in silico cloning ensured the increased expression of vaccine in Escherichia coli. Altogether, we anticipate that the multi-epitope vaccine reported in this study will stimulate humoral and cellular responses against RSV infection, subject to follow-up experimental validation.

Identification and construction of a multi-epitopes vaccine design against Klebsiella aerogenes: molecular modeling study

A rapid rise in antibiotic resistance by bacterial pathogens is due to these pathogens adaptation to the changing environmental conditions. Antibiotic resistance infections can be reduced by a number of ways such as development of safe and effective vaccine. Klebsiella aerogene is a gram-negative, rod-shaped bacterium resistant to a variety of antibiotics and no commercial vaccine is available against the pathogen. Identifying antigens that can be easily evaluated experimentally would be crucial to successfully vaccine development. Reverse vaccinology (RV) was used to identify vaccine candidates based on complete pathogen proteomic information. The fully sequenced proteomes include 44,115 total proteins of which 43,316 are redundant and 799 are non-redundant. Subcellular localization showed that only 1 protein in extracellular matrix, 7 were found in outer-membrane proteins, and 27 in the periplasm space. A total of 3 proteins were found virulent. Next in the B-cell-derived T-cell epitopes mapping phase, the 3 proteins (Fe2^+- enterobactin, ABC transporter substrate-binding protein, and fimbriae biogenesis outer membrane usher protein) were tested positive for antigenicity, toxicity, and solubility. GPGPG linkers were used to prepare a vaccine construct composed of 7 epitopes and an adjuvant of toxin B subunit (CTBS). Molecular docking of vaccine construct with major histocompatibility-I (MHC-I), major histocompatibility-II (MHC-II), and Toll-like receptor 4 (TLR4) revealed vaccine robust interactions and stable binding pose to the receptors. By using molecular dynamics simulations, the vaccine-receptors complexes unveiled stable dynamics and uniform root mean square deviation (rmsd). Further, binding energies of complex were computed that again depicted strong intermolecular bindings and formation of stable conformation.

Exploring whole proteome to contrive multi-epitope-based vaccine for NeoCoV: An immunoinformtics and in-silico approach

Neo-Coronavirus (NeoCoV) is a novel Betacoronavirus (β-CoVs or Beta-CoVs) discovered in bat specimens in South Africa during 2011. The viral sequence is highly similar to Middle East Respiratory Syndrome, particularly that of structural proteins. Thus, scientists have emphasized the threat posed by NeoCoV associated with human angiotensin-converting enzyme 2 (ACE2) usage, which could lead to a high death rate and faster transmission rate in humans. The development of a NeoCoV vaccine could provide a promising option for the future control of the virus in case of human infection. In silico predictions can decrease the number of experiments required, making the immunoinformatics approaches cost-effective and convenient. Herein, with the aid of immunoinformatics and reverse vaccinology, we aimed to formulate a multi-epitope vaccine that may be used to prevent and treat NeoCoV infection. Based on the NeoCoV proteins, B-cell, cytotoxic T lymphocyte (CTL), and helper T lymphocyte (HTL) epitopes were shortlisted. Four vaccines (Neo-1-4) were devised by fusing shortlisted epitopes with appropriate adjuvants and linkers. The secondary and three-dimensional structures of final vaccines were then predicted. The binding interactions of these potential vaccines with toll-like immune receptors (TLR-2, TLR-3, and TLR-4) and major histocompatibility complex molecules (MHC-I and II) reveal that they properly fit into the receptors' binding domains. Besides, Neo-1 and Neo-4 vaccines exhibited better docking energies of -101.08 kcal/mol and -114.47 kcal/mol, respectively, with TLR-3 as compared to other vaccine constructs. The constructed vaccines are highly antigenic, non-allergenic, soluble, non-toxic, and topologically assessable with good physiochemical characteristics. Codon optimization and in-silico cloning confirmed efficient expression of the designed vaccines in Escherichia coli strain K12. In-silico immune simulation indicated that Neo-1 and Neo-4 vaccines could induce a strong immune response against NeoCoV. Lastly, the binding stability and strong binding affinity of Neo-1 and Neo-4 with TLR-3 receptor were validated using molecular dynamics simulations and free energy calculations (Molecular Mechanics/Generalized Born Surface Area method). The final vaccines require experimental validation to establish their safety and effectiveness in preventing NeoCoV infections.

In silico design of a multi-epitope vaccine against HPV16/18

BACKGROUND

Cervical cancer is the fourth most common cancer affecting women and is caused by human Papillomavirus (HPV) infections that are sexually transmitted. There are currently commercially available prophylactic vaccines that have been shown to protect vaccinated individuals against HPV infections, however, these vaccines have no therapeutic effects for those who are previously infected with the virus. The current study's aim was to use immunoinformatics to develop a multi-epitope vaccine with therapeutic potential against cervical cancer.

RESULTS

In this study, T-cell epitopes from E5 and E7 proteins of HPV16/18 were predicted. These epitopes were evaluated and chosen based on their antigenicity, allergenicity, toxicity, and induction of IFN-γ production (only in helper T lymphocytes). Then, the selected epitopes were sequentially linked by appropriate linkers. In addition, a C-terminal fragment of Mycobacterium tuberculosis heat shock protein 70 (HSP70) was used as an adjuvant for the vaccine construct. The physicochemical parameters of the vaccine construct were acceptable. Furthermore, the vaccine was soluble, highly antigenic, and non-allergenic. The vaccine's 3D model was predicted, and the structural improvement after refinement was confirmed using the Ramachandran plot and ProSA-web. The vaccine's B-cell epitopes were predicted. Molecular docking analysis showed that the vaccine's refined 3D model had a strong interaction with the Toll-like receptor 4. The structural stability of the vaccine construct was confirmed by molecular dynamics simulation. Codon adaptation was performed in order to achieve efficient vaccine expression in Escherichia coli strain K12 (E. coli). Subsequently, in silico cloning of the multi-epitope vaccine was conducted into pET-28a ( +) expression vector.

CONCLUSIONS

According to the results of bioinformatics analyses, the multi-epitope vaccine is structurally stable, as well as a non-allergic and non-toxic antigen. However, in vitro and in vivo studies are needed to validate the vaccine's efficacy and safety. If satisfactory results are obtained from in vitro and in vivo studies, the vaccine designed in this study may be effective as a therapeutic vaccine against cervical cancer.

Modern vaccine development via reverse vaccinology to combat antimicrobial resistance

With the continuous evolution of bacteria, the global antimicrobial resistance health threat is causing millions of deaths yearly. While depending on antibiotics as a primary treatment has its merits, there are no effective alternatives thus far in the pharmaceutical market against some drug-resistant bacteria. In recent years, vaccinology has become a key topic in scientific research. Combining with the growth of technology, vaccine research is seeing a new light where the process is made faster and more efficient. Although less discussed, bacterial vaccine is a feasible strategy to combat antimicrobial resistance. Some vaccines have shown promising results with good efficacy against numerous multidrug-resistant strains of bacteria. In this review, we aim to discuss the findings from studies utilizing reverse vaccinology for vaccine development against some multidrug-resistant bacteria, as well as provide a summary of multi-year bacterial vaccine studies in clinical trials. The advantages of reverse vaccinology in the generation of new bacterial vaccines are also highlighted. Meanwhile, the limitations and future prospects of bacterial vaccine concludes this review.

Development of a Multi-Epitope Vaccine for Mycoplasma hyopneumoniae and Evaluation of Its Immune Responses in Mice and Piglets

Mycoplasma hyopneumoniae (Mhp), the primary pathogen causing Mycoplasma pneumonia of swine (MPS), brings massive economic losses worldwide. Genomic variability and post-translational protein modification can enhance the immune evasion of Mhp, which makes MPS prone to recurrent outbreaks on farms, even with vaccination or other treatments. The reverse vaccinology pipeline has been developed as an attractive potential method for vaccine development due to its high efficiency and applicability. In this study, a multi-epitope vaccine for Mhp was developed, and its immune responses were evaluated in mice and piglets. Genomic core proteins of Mhp were retrieved through pan-genome analysis, and four immunodominant antigens were screened by host homologous protein removal, membrane protein screening, and virulence factor identification. One immunodominant antigen, AAV27984.1 (membrane nuclease), was expressed by E. coli and named rMhp597. For epitope prioritization, 35 B-cell-derived epitopes were identified from the four immunodominant antigens, and 10 MHC-I and 6 MHC-II binding epitopes were further identified. The MHC-I/II binding epitopes were merged and combined to produce recombinant proteins MhpMEV and MhpMEVC6His, which were used for animal immunization and structural analysis, respectively. Immunization of mice and piglets demonstrated that MhpMEV could induce humoral and cellular immune responses. The mouse serum antibodies could detect all 11 synthetic epitopes, and the piglet antiserum suppressed the nuclease activity of rMhp597. Moreover, piglet serum antibodies could also detect cultured Mhp strain 168. In summary, this study provides immunoassay results for a multi-epitope vaccine derived from the reverse vaccinology pipeline, and offers an alternative vaccine for MPS.

Immunoinformatic Approach to Contrive a Next Generation Multi-Epitope Vaccine Against Achromobacter xylosoxidans Infections

Achromobacter xylosoxidans, previously identified as Alcaligenes xylosoxidans, is a rod-shaped, flagellated, non-fermenting Gram-negative bacterium that has the ability to cause diverse infections in humans. As a part of its intrinsic resistance to different antibiotics, Achromobacter spp. is also increasingly becoming resistant to Carbapenems. Lack of knowledge regarding the pathogen’s clinical features has led to limited efforts to develop countermeasures against infection. The current study utilized an immunoinformatic method to map antigenic epitopes (Helper T cells, B-cell and Cytotoxic-T cells) to design a vaccine construct. We found that 20 different epitopes contribute significantly to immune response instigation that was further supported by physicochemical analysis and experimental viability. The safety profile of our vaccine was tested for antigenicity, allergenicity, and toxicity against all the identified epitopes before they were used as vaccine candidates. The disulfide engineering was carried out in an area of high mobility to increase the stability of vaccine proteins. In order to determine if the constructed vaccine is compatible with toll-like receptor, the binding affinity of vaccine was investigated via molecular docking approach. With the in silico expression in host cells and subsequent immune simulations, we were able to detect the induction of both arms of the immune response, i.e., humoral response and cytokine induced response. To demonstrate its safety and efficacy, further experimental research is necessary.

Identification of Antigenic Properties of Acinetobacter baumannii Proteins as Novel Putative Vaccine Candidates Using Reverse Vaccinology Approach

Multidrug-resistant Acinetobacter baumannii (A. baumannii) infections are becoming more prevalent all over the world. As a cost-effective and preventative method, vaccination seems to be required against this bacterium. In the present study, subtractive proteomics along with reverse vaccinology approaches was used to predict suitable therapeutics against A. baumannii. Using the Vaxign online tool, we studied over 35 genomes of A. baumannii strains and chose outer membrane and secreted proteins of A. baumannii 1656-2 as possible vaccine candidates. Then, investigations were performed on the immunogenicity, antigenic characteristics, physicochemical properties, B-cell and MHC class I, and MHC class II molecules epitope densities of proteins. After optimizing the codon of the proteins, the pcDNA3.1( +) expression construct was designed and the immunogenicity, allergenicity, and physicochemical properties of the vaccine construct were predicted. Hcp and OmpC proteins were predicted as extracellular and outer membrane proteins, respectively. These proteins interact with 10 other proteins to form a network of protein interactions with virulence properties. Immunoassays of Hcp and OmpC proteins showed antigenicity of 0.88 and 0.79, respectively. These proteins have 5 structural cell epitope points and 5 linear B epitope points. They are also able to bind to different HLA alleles of MCH class I/class II as selected immunogenic proteins and designed non-allergenic structures with solubility of 0.650 and immunogenicity score of 0.91. The results of this "in silico" study indicate high specificity and the development of a significant humoral and cellular immune response. It can be concluded that the Hcp and OmpC dual vaccine construct is one of the promising candidates against A. baumannii. The findings of this "in silico" study show excellent specificity and the emergence of a substantial humoral and cellular immune response. This is a computer-based study that needs to be tested in vitro and in vivo to corroborate the conclusions of the vaccine design procedures.

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

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

Reverse vaccinology-based prediction of a multi-epitope SARS-CoV-2 vaccine and its tailoring to new coronavirus variants

The genome feature of SARS-CoV-2 leads the virus to mutate and creates new variants of concern. Tackling viral mutations is also an important challenge for the development of a new vaccine. Accordingly, in the present study, we undertook to identify B- and T-cell epitopes with immunogenic potential for eliciting responses to SARS-CoV-2, using computational approaches and its tailoring to coronavirus variants. A total of 47 novel epitopes were identified as immunogenic triggering immune responses and no toxic after investigation with in silico tools. Furthermore, we found these peptide vaccine candidates showed a significant binding affinity for MHC I and MHC II alleles in molecular docking investigations. We consider them to be promising targets for developing peptide-based vaccines against SARS-CoV-2. Subsequently, we designed two efficient multi-epitopes vaccines against the SARS-CoV-2, the first one based on potent MHC class I and class II T-cell epitopes of S (FPNITNLCPF-NYNYLYRLFR-MFVFLVLLPLVSSQC), M (MWLSYFIASF-GLMWLSYFIASFRLF), E (LTALRLCAY-LLFLAFVVFLLVTLA), and N (SPRWYFYYL-AQFAPSASAFFGMSR). The second candidate is the result of the tailoring of the first designed vaccine according to three classes of SARS-CoV-2 variants. Molecular docking showed that the protein-protein binding interactions between the vaccines construct and TLR2-TLR4 immune receptors are stable complexes. These findings confirmed that the final multi-epitope vaccine could be easily adapted to new viral variants. Our study offers a shortlist of promising epitopes that can accelerate the development of an effective and safe vaccine against the virus and its adaptation to new variants.Communicated by Ramaswamy H. Sarma.

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 titers for the immunogen, and the antibody titers increased significantly following the second immunization. However, the generated antibodies did not protect the 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 the 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.

Designing of a Recombinant Multi-Epitopes Based Vaccine against Enterococcus mundtii Using Bioinformatics and Immunoinformatics Approaches

Enterococcus species are an emerging group of bacterial pathogens that have a significant role in hospital-associated infections and are associated with higher mortality and morbidity rates. Among these pathogens, Enterococcus mundtii is one of the causative agents of multiple hospital associated infections. Currently, no commercially available licensed vaccine is present, and multi-drug resistant strains of the pathogen are prominent. Due to several limitations of experimental vaccinology, computational vaccine designing proved to be helpful in vaccine designing against several bacterial pathogens. Herein, we designed a multi-epitope-based vaccine against E. mundtii using in silico approaches. After an in-depth analysis of the core genome, three probable antigenic proteins (lytic polysaccharide monooxygenase, siderophore ABC transporter substrate-binding protein, and lytic polysaccharide monooxygenase) were shortlisted for epitope prediction. Among predicted epitopes, ten epitopes-GPADGRIAS, TTINHGGAQA, SERTALSVTT, GDGGNGGGEV, GIKEPDLEK, KQADDRIEA, QAIGGDTSN, EPLDEQTASR, AQWEPQSIEA, QPLKFSDFEL-were selected for multi-epitope vaccine construct designing. The screened B- and T-cell epitopes were joined with each other via specific linkers and linked to the cholera toxin B subunit as an adjuvant to enhance vaccine immune protection efficacy. The designed vaccine construct induced cellular and humoral immune responses. Blind docking with immune cell receptors, followed by molecular dynamic simulation results confirms the good binding potency and stability of the vaccine in providing protection against the pathogen.

In silico Designing of an Epitope-Based Vaccine Against Common E. coli Pathotypes

Escherichia coli (E. coli) is a Gram-negative bacterium that belongs to the family Enterobacteriaceae. While E. coli can stay as an innocuous resident in the digestive tract, it can cause a group of symptoms ranging from diarrhea to live threatening complications. Due to the increased rate of antibiotic resistance worldwide, the development of an effective vaccine against E. coli pathotypes is a major health priority. In this study, a reverse vaccinology approach along with immunoinformatics has been applied for the detection of potential antigens to develop an effective vaccine. Based on our screening of 5,155 proteins, we identified lipopolysaccharide assembly protein (LptD) and outer membrane protein assembly factor (BamA) as vaccine candidates for the current study. The conservancy of these proteins in the main E. coli pathotypes was assessed through BLASTp to make sure that the designed vaccine will be protective against major E. coli pathotypes. The multitope vaccine was constructed using cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B cell lymphocyte (BCL) epitopes with suitable linkers and adjuvant. Following that, it was analyzed computationally where it was found to be antigenic, soluble, stable, and non-allergen. Additionally, the adopted docking study, as well as all-atom molecular dynamics simulation, illustrated the promising predicted affinity and free binding energy of this constructed vaccine against the human Toll-like receptor-4 (hTLR-4) dimeric state. In this regard, wet lab studies are required to prove the efficacy of the potential vaccine construct that demonstrated promising results through computational validation.

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

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

Exploring Klebsiella pneumoniae capsule polysaccharide proteins to design multiepitope subunit vaccine to fight against pneumonia

BACKGROUND

Klebsiella pneumoniae is an emerging human pathogen causing neonatal lung disease, catheter-associated infections, and nosocomial outbreaks with high fatality rates. Capsular polysaccharide (CPS) protein plays a major determinant in virulence and is considered as a promising target for vaccine development.

RESEARCH DESIGN AND METHODS

In this study, we used immunoinformatic approaches to design a multi-peptide vaccine against K. pneumonia. The epitopes were selected through several immune filters, such as antigenicity, conservancy, nontoxicity, non-allergenicity, binding affinity to HLA alleles, overlapping epitopes, and peptides having common epitopes.

RESULTS

Finally, a construct comprising 2 B-Cell, 8 CTL, 2 HTL epitopes, along with adjuvant, linkers was designed. Peptide-HLA interaction analysis showed strong binding of these epitopes with several common HLA molecules. The in silico immune simulation and population coverage analysis of the vaccine showed its potential to evoke strong immune responses.. Further, the interaction between vaccine and immune was evaluated by docking and simulation, revealing high affinity and complex stability. Codon adaptation and in silico cloning revealed higher expression of vaccine in E. coli K12 expression system.

CONCLUSIONS

Conclusively, the findings of the present study suggest that the designed novel multi-epitopic vaccine holds potential for further experimental validation against the pathogen.

Computational design and characterization of a multiepitope vaccine against carbapenemase-producing Klebsiella pneumoniae strains, derived from antigens identified through reverse vaccinology

Klebsiella pneumoniae is a Gram-negative pathogen of clinical relevance, which can provoke serious urinary and blood infections and pneumonia. This bacterium is a major public health threat due to its resistance to several antibiotic classes. Using a reverse vaccinology approach, 7 potential antigens were identified, of which 4 were present in most of the sequences of Italian carbapenem-resistant K. pneumoniae clinical isolates. Bioinformatics tools demonstrated the antigenic potential of these bacterial proteins and allowed for the identification of T and B cell epitopes. This led to a rational design and in silico characterization of a multiepitope vaccine against carbapenem-resistant K. pneumoniae strains. As adjuvant, the mycobacterial heparin-binding hemagglutinin adhesin (HBHA), which is a Toll-like receptor 4 (TLR-4) agonist, was included, to increase the immunogenicity of the construct. The multiepitope vaccine candidate was analyzed by bioinformatics tools to assess its antigenicity, solubility, allergenicity, toxicity, physical and chemical parameters, and secondary and tertiary structures. Molecular docking binding energies to TLR-2 and TLR-4, two important innate immunity receptors involved in the immune response against K. pneumoniae infections, and molecular dynamics simulations of such complexes supported active interactions. A codon optimized multiepitope sequence cloning strategy is proposed, for production of recombinant vaccine in classical bacterial vectors. Finally, a 3 dose-immunization simulation with the multiepitope construct induced both cellular and humoral immune responses. These results suggest that this multiepitope construct has potential as a vaccination strategy against carbapenem-resistant K. pneumoniae and deserves further validation.

Immunoinformatics approach for designing a universal multiepitope vaccine against Chandipura Virus

Chandipura vesiculovirus (CHPV) is a fast-emerging virus that causes acute encephalitis with a high death rate. Because of its extensive prevalence in African and Asian countries, this infection has become a global hazard, and there is an urgent need to create an effective and non-allergenic vaccine or appropriate treatment to combat it. A vaccine candidate is offered utilizing a computational technique in this study. To build a potential vaccine candidate, viral protein sequences were acquired from the National Center for Biotechnology Information database and evaluated with several bioinformatics techniques to identify B-cell and T-cell epitopes. V1 was shown to be superior in terms of various physicochemical qualities, as well as highly immunogenic and non-allergic. Molecular docking revealed that the CHPV vaccine construct had a greater binding affinity with human Toll-like receptors (TLR-3 and TLR-8) and that it was stable in molecular dynamics simulations. MEC-CHPV was in silico cloned in the pET28a (+) expression vector using codon optimization. The current research identifies potential antigenic epitopes that could be used as vaccine candidates to eradicate the CHPV. This in-silico development of a CHPV vaccine with multiple epitopes could open the path for future rapid laboratory tests.

In-Silico Vaccine Design Based on a Novel Vaccine Candidate Against Infections Caused by Acinetobacter baumannii

Acinetobacter baumannii is notorious for causing serious infections of the skin, lungs, soft tissues, bloodstream, and urinary tract. Despite the overwhelming information available so far, there has still been no approved vaccine in the market to prevent these infections. Therefore, this study focuses on developing a rational vaccine design using the technique of epitope mapping to curb the infections caused by A. baumannii. An outer membrane protein with immunogenic potential as well as all the properties of a good vaccine candidate was selected and used to calculate epitopes for selection on the basis of a low percentile rank, high binding scores, good immunological properties, and non-allergenicity. Thus, a 240 amino-acid vaccine sequence was obtained by manually joining all the epitopes in sequence-wise manner with the appropriate linkers, namely AAY, GPGPG, and EAAAK. Additionally, a 50S ribosomal protein L7/L12, agonist to the human innate immune receptors was attached to the N-terminus to increase the overall immune response towards the vaccine. As a result, enhanced overall protein stability, expression, immunostimulatory capabilities, and solubility of the designed construct were observed. Molecular dynamic simulations revealed the compactness and stability of the polypeptide construct. Moreover, molecular docking exhibited strong binding of the designed vaccine with TLR-4 and TLR-9. In-silico immune simulations indicated an immense increment in T-cell and B-cell populations. Bioinformatic tools also significantly assisted with optimizing codons which allowed for successful cloning of constructs into desired host vectors. Using in-silico tools to design a vaccine against A. baumannii demonstrated that this construct could pave the way for successfully combating infections caused by multidrug-resistant bacteria.

Designing of a Multi-epitope Vaccine against the Structural Proteins of Marburg Virus Exploiting the Immunoinformatics Approach

Marburg virus disease (MVD) caused by the Marburg virus (MARV) generally appears with flu-like symptoms and leads to severe hemorrhagic fever. It spreads via direct contact with infected individuals or animals. Despite being considered to be less threatening in terms of appearances and the number of infected patients, the high fatality rate of this pathogenic virus is a major concern. Until now, no vaccine has been developed to combat this deadly virus. Therefore, vaccination for this virus is necessary to reduce its mortality. Our current investigation focuses on the design and formulation of a multi-epitope vaccine based on the structural proteins of MARV employing immunoinformatics approaches. The screening of potential T-cell and B-cell epitopes from the seven structural proteins of MARV was carried out through specific selection parameters. Afterward, we compiled the shortlisted epitopes by attaching them to an appropriate adjuvant and linkers. Population coverage analysis, conservancy analysis, and MHC cluster analysis of the shortlisted epitopes were satisfactory. Importantly, physicochemical characteristics, human homology assessment, and structure validation of the vaccine construct delineated convenient outcomes. We implemented disulfide bond engineering to stabilize the tertiary or quaternary interactions. Furthermore, stability and physical movements of the vaccine protein were explored using normal-mode analysis. The immune simulation study of the vaccine complexes also exhibited significant results. Additionally, the protein-protein docking and molecular dynamics simulation of the final construct exhibited a higher affinity toward toll-like receptor-4 (TLR4). From simulation trajectories, multiple descriptors, namely, root mean square deviations (rmsd), radius of gyration (Rg), root mean square fluctuations (RMSF), solvent-accessible surface area (SASA), and hydrogen bonds, have been taken into account to demonstrate the inflexible and rigid nature of receptor molecules and the constructed vaccine. Inclusively, our findings suggested the vaccine constructs' ability to regulate promising immune responses against MARV pathogenesis.

Development of a Candidate Multi-Epitope Subunit Vaccine against Klebsiella aerogenes: Subtractive Proteomics and Immuno-Informatics Approach

Klebsiella aerogenes is a Gram-negative bacterium which has gained considerable importance in recent years. It is involved in 10% of nosocomial and community-acquired urinary tract infections and 12% of hospital-acquired pneumonia. This organism has an intrinsic ability to produce inducible chromosomal AmpC beta-lactamases, which confer high resistance. The drug resistance in K. aerogenes has been reported in China, Israel, Poland, Italy and the United States, with a high mortality rate (~50%). This study aims to combine immunological approaches with molecular docking approaches for three highly antigenic proteins to design vaccines against K. aerogenes. The synthesis of the B-cell, T-cell (CTL and HTL) and IFN-γ epitopes of the targeted proteins was performed and most conserved epitopes were chosen for future research studies. The vaccine was predicted by connecting the respective epitopes, i.e., B cells, CTL and HTL with KK, AAY and GPGPG linkers and all these were connected with N-terminal adjuvants with EAAAK linker. The humoral response of the constructed vaccine was measured through IFN-γ and B-cell epitopes. Before being used as vaccine candidate, all identified B-cell, HTL and CTL epitopes were tested for antigenicity, allergenicity and toxicity to check the safety profiles of our vaccine. To find out the compatibility of constructed vaccine with receptors, MHC-I, followed by MHC-II and TLR4 receptors, was docked with the vaccine. Lastly, in order to precisely certify the proper expression and integrity of our construct, in silico cloning was carried out. Further studies are needed to confirm the safety features and immunogenicity of the vaccine.

Development of an in silico multi-epitope vaccine against SARS-COV-2 by précised immune-informatics approaches

The coronavirus family has been infecting the human population for the past two decades, but the ongoing coronavirus called SARS-CoV-2 has posed an enigmatic challenge to global public health security. Since last year, the mutagenic quality of this virus is causing changes to its genetic material. To prevent those situations, the FDA approved some emergency vaccines but there is no assurance that these will function properly in the complex human body system. In point of view, a short but efficient effort has made in this study to develop an immune epitope-based therapy for the rapid exploitation of SARS-CoV-2 by applying in silico structural biology and advancing immune information strategies. The antigenic epitopes were screened from the Surface, Membrane, Envelope proteins of SARS-CoV-2 and passed through several immunological filters to determine the best possible one. According to this, 7CD4+, 10CD8+ and 5 B-cell epitopes were found to be prominent, antigenic, immunogenic, and most importantly, highly conserved among 128 Bangladeshi and 110 other infected countries SARS-CoV-2 variants. After that, the selected epitopes and adjuvant were linked to finalize the multi-epitope vaccine by appropriate linkers. The immune simulation disclosed that the engineered vaccine could activate both humoral and innate immune responses. For the prediction of an effective binding, molecular docking was carried out between the vaccine and immunological receptors (TLRs). Strong binding affinity and good docking scores clarified the stringency of the vaccines. Furthermore, MD simulation was performed within the highest binding affinity complex to observe the stability. Codon optimization and other physicochemical properties revealed that the vaccine would be suitable for a higher expression at cloning level. So, monitoring the overall in silico assessment, we anticipated that our engineered vaccine would be a plausible prevention against COVID-19.

Immunoinformatics based designing a multi-epitope vaccine against pathogenic Chandipura vesiculovirus

Chandipura vesiculovirus (CHPV) is a rapidly emerging pathogen responsible for causing acute encephalitis. Due to its widespread occurrence in Asian and African countries, this has become a global threat, and there is an urgent need to design an effective and nonallergenic vaccine against this pathogen. The present study aimed to develop a multi-epitope vaccine using an immunoinformatics approach. The conventional method of vaccine design involves large proteins or whole organism which leads to unnecessary antigenic load with increased chances of allergenic reactions. In addition, the process is also very time-consuming and labor-intensive. These limitations can be overcome by peptide-based vaccines comprising short immunogenic peptide fragments that can elicit highly targeted immune responses, avoiding the chances of allergenic reactions, in a relatively shorter time span. The multi-epitope vaccine constructed using CTL, HTL, and IFN-γ epitopes was able to elicit specific immune responses when exposed to the pathogen, in silico. Not only that, molecular docking and molecular dynamics simulation studies confirmed a stable interaction of the vaccine with the immune receptors. Several physicochemical analyses of the designed vaccine candidate confirmed it to be highly immunogenic and nonallergic. The computer-aided analysis performed in this study suggests that the designed multi-epitope vaccine can elicit specific immune responses and can be a potential candidate against CHPV.