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

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.

Multi-epitopevaccines, from design to expression; an in silico approach

The development of vaccines against a wide range of infectious diseases and pathogens often relies on multi-epitope strategies that can effectively stimulate both humoral and cellular immunity. Immunoinformatics tools play a pivotal role in designing such vaccines, enhancing immune response potential, and minimizing the risk of failure. This review presents a comprehensive overview of practical tools for epitope prediction and the associated immune responses. These immunoinformatics tools facilitate the selection of epitopes based on parameters such as antigenicity, absence of toxic and allergenic sequences, secondary and tertiary structures, sequence conservation, and population coverage. The chosen epitopes can be tailored for B-cells or T-cells, both of which require further assessments covered in this study. We offer a range of suitable linkers that effectively separate cytotoxic T lymphocyte and helper T lymphocyte epitopes while preserving their functionality. Additionally, we identify various adjuvants for specific purposes. We delve into the evaluation of MHC-epitope interactions, MHC clusters, and the simulation of final constructs through molecular docking techniques. We provide diverse linkers and adjuvants optimized for epitope functions to bolster immune responses through epitope attachment. By leveraging these comprehensive tools, the development of multi-epitope vaccines holds the promise of robust immunity and a significant reduction in experimental costs.

In-silico analysis of potent Mosquirix vaccine adjuvant leads

BACKGROUND

World Health Organization recommend the use of malaria vaccine, Mosquirix, as a malaria prevention strategy. However, Mosquirix has failed to reduce the global burden of malaria because of its inefficacy. The Mosquirix vaccine's modest effectiveness against malaria, 36% among kids aged 5 to 17 months who need at least four doses, fails to aid malaria eradication. Therefore, highly effective and efficacious malaria vaccines are required. The well-characterized P. falciparum circumsporozoite surface protein can be used to discover adjuvants that can increase the efficacy of Mosquirix. Therefore, the study sought to undertake an in-silico discovery of Plasmodium falciparum circumsporozoite surface protein inhibitors with pharmacological properties on Mosquirix using hierarchical virtual screening and molecular dynamics simulation.

RESULTS

Monoclonal antibody L9, an anti-Plasmodium falciparum circumsporozoite surface protein molecule, was used to identify Plasmodium falciparum circumsporozoite surface protein inhibitors with pharmacological properties on Mosquirix during a virtual screening process in ZINCPHARMER that yielded 23 hits. After drug-likeness and absorption, distribution, metabolism, excretion, and toxicity property analysis in the SwissADME web server, only 9 of the 23 hits satisfied the requirements. The 9 compounds were docked with Plasmodium falciparum circumsporozoite surface protein using the PyRx software to understand their interactions. ZINC25374360 (-8.1 kcal/mol), ZINC40144754 (-8.3 kcal/mol), and ZINC71996727 (-8.9 kcal/mol) bound strongly to Plasmodium falciparum circumsporozoite surface protein with binding affinities of less than -8.0 kcal/mol. The stability of these molecularly docked Plasmodium falciparum circumsporozoite surface protein-inhibitor complexes were assessed through molecular dynamics simulation using GROMACS 2022. ZINC25374360 and ZINC71996727 formed stable complexes with Plasmodium falciparum circumsporozoite surface protein. They were subjected to in vitro validation for their inhibitory potential. The IC50 values ranging between 250 and 350 ng/ml suggest inhibition of parasite development.

CONCLUSION

Therefore, the two Plasmodium falciparum circumsporozoite surface protein inhibitors can be used as vaccine adjuvants to increase the efficacy of the existing Mosquirix vaccine. Nevertheless, additional in vivo tests, structural optimization studies, and homogenization analysis are essential to determine the anti-plasmodial action of these adjuvants in humans.

In silico designing of an epitope-based peptide vaccine cocktail against Nipah virus: an Indian population-based epidemiological study

Nipah virus, a zoonotic virus from the family Paramyxoviridae has led to significant loss of lives till date with the most recent outbreak in India reported in Kerala. The virus has a considerably high mortality rate along with lack of characteristic symptoms which results in the delay of the virus detection. No specific vaccine is available for the virus although monoclonal antibody treatment has been seen to be effective along with favipiravir. The high mortality and complications caused by the virus underscores the necessity to develop alternative modes of vaccination. One such method has been designed in this study using peptide cocktail consisting of the immunologically important epitopes for use as vaccine. The human leucocytic antigens that are used for the study were analyzed for their presence in various ethnic Indian populations. This study may serve as a new avenue for development of more efficient peptide cocktail vaccines in recent future based on the population genetics and ethnicity.

A Comprehensive review on Pharmacokinetic Studies of Vaccines: Impact of delivery route, carrier-and its modulation on immune response

The lack of knowledge about the absorption, distribution, metabolism, and excretion (ADME) of vaccines makes former biopharmaceutical optimization difficult. This was shown during the COVID-19 immunization campaign, where gradual booster doses were introduced.. Thus, understanding vaccine ADME and its effects on immunization effectiveness could result in a more logical vaccine design in terms of formulation, method of administration, and dosing regimens. Herein, we will cover the information available on vaccine pharmacokinetics, impacts of delivery routes and carriers on ADME, utilization and efficiency of nanoparticulate delivery vehicles, impact of dose level and dosing schedule on the therapeutic efficacy of vaccines, intracellular and endosomal trafficking and in vivo fate, perspective on DNA and mRNA vaccines, new generation sequencing and mathematical models to improve cancer vaccination and pharmacology, and the reported toxicological study of COVID-19 vaccines. Altogether, this review will enhance the reader's understanding of the pharmacokinetics of vaccines and methods that can be implied in delivery vehicle design to improve the absorption and distribution of immunizing agents and estimate the appropriate dose to achieve better immunogenic responses and prevent toxicities.

Two peptides derivate from Acinetobacter baumannii outer membrane protein K as vaccine candidates: a comprehensive in silico study

BACKGROUND

The lack of appropriate vaccines is an obstacle to the effective management of A. baumannii infections. Peptide vaccines offer an attractive and promising preventive strategy against A. baumannii.

OBJECTIVE

In this study, we identified specific T cell epitopes of A. baumannii outer membrane protein K (OMPK) using comprehensive bioinformatics and detailed molecular docking analysis.

METHODS

Both class-I and class-II T cell epitopes of A. baumannii OMPK were predicted by three tools namely IEDB, SYFPEITHI, and ProPred. The predicted epitopes were shortlisted based on several analyses including prediction scoring, clustering, exclusion of human similarity, considering immunogenicity and cytokine production, and removal of toxic and/or allergen epitopes. The epitopic peptides with high prediction scores and appropriate properties containing both class-I and class-II T cell epitopes were selected. Two of these class I/II epitopic peptides were chosen for molecular docking studies and assessing their physicochemical properties as vaccine candidates.

RESULTS

The results showed many T-cell epitopes of OMPK that could be evaluated for possible immunogenicity. Two of these epitopes (containing both class-I and II epitopes) had high prediction scores, were predicted by several tools, attached to several HLAs, and had the best docking score. They had different physicochemical properties and were conserved among Acinetobacter species.

DISCUSSION

We identified the A. baumannii OMPK high immunogenic class-I and class-II T cell epitopes and introduced two promising high immunogenic peptides as vaccine candidates. It is recommended to perform in vitro/in vivo investigation of these peptides to determine their true efficacy and efficiency.

Immunoinformatics Approaches for Vaccine Design: A Fast and Secure Strategy for Successful Vaccine Development

Vaccines are major contributors to the cost-effective interventions in major infectious diseases in the global public health space [...].

Vaccinomics-Aided Development of a Next-Generation Chimeric Vaccine against an Emerging Threat: Mycoplasma genitalium

Mycoplasma genitalium, besides urethritis, causes a number of other sexually transmitted diseases, posing a significant health threat to both men and women, particularly in developing countries. In light of the rapid appearance of multidrug-resistant strains, M. genitalium is regarded as an emerging threat and has been placed on the CDC's "watch list". Hence, a protective vaccine is essential for combating this pathogen. In this study, we utilized reverse vaccinology to develop a chimeric vaccine against M. genitalium by identifying vaccine targets from the reference proteome (Strain G-37) of this pathogen. A multiepitope vaccine was developed using proteins that are non-toxic, non-allergic, and non-homologous to human proteins. Several bioinformatic tools identified linear and non-linear B-cell epitopes, as well as MHC epitopes belonging to classes I and II, from the putative vaccine target proteins. The epitopes that showed promiscuity among the various servers were shortlisted and subsequently selected for further investigation based on an immunoinformatic analysis. Using GPGPG, AAY, and KK linkers, the shortlisted epitope sequences were assembled to create a chimeric construct. A GPI anchor protein immunomodulating adjuvant was adjoined to the vaccine construct's N-terminus through the EAAK linker so as to improve the overall immunogenicity. For further investigations of the designed construct, various bioinformatic tools were employed to study the physicochemical properties, immune profile, solubility, and allergenicity profile. A tertiary chimeric design was computationally modeled using I-TASSER and Robetta and was subsequently refined through GalaxyRefine. ProSA-Web was exploited to corroborate the quality of the construct by detecting errors and the Ramachandran plot was used to identify possible quality issues. Simulation studies of the molecular dynamics demonstrated the robustness and flexibility of the designed construct. Following the successful docking of the designed model to the immune receptors, the construct was computationally cloned into Escherichia coli plasmids to affirm the efficient expression of the designed construct in a biological system.

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

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

Immunoinformatics-Based Proteome Mining to Develop a Next-Generation Vaccine Design against Borrelia burgdorferi: The Cause of Lyme Borreliosis

The tick-borne bacterium, Borrelia burgdorferi has been implicated in Lyme disease-a deadly infection, formerly confined to North America, but currently widespread across Europe and Asia. Despite the severity of this disease, there is still no human Lyme disease vaccine available. A reliable immunoinformatic approach is urgently needed for designing a therapeutic vaccine against this Gram-negative pathogen. Through this research, we explored the immunodominant proteins of B. burgdorferi and developed a novel and reliable vaccine design with great immunological predictability as well as low contamination and autoimmunity risks. Our initial analysis involved proteome-wide analysis to filter out proteins on the basis of their redundancy, homology to humans, virulence, immunogenicity, and size. Following the selection of proteins, immunoinformatic tools were employed to identify MHC class I & II epitopes and B-cell epitopes, which were subsequently subjected to a rigorous screening procedure. In the final formulation, ten common MHC-I and II epitopes were used together with a suitable adjuvant. We predicted that the final chimeric multi-epitope vaccine could invoke B-cell responses and IFN-gamma-mediated immunity as well as being stable and non-allergenic. The dynamics simulations predicted the stable folding of the designed molecule, after which the molecular docking predicted the stability of the interaction between the potential antigenic epitopes and human immune receptors. Our studies have shown that the designed next-generation vaccine stimulates desirable immune responses, thus potentially providing a viable way to prevent Lyme disease. Nevertheless, further experimental studies in a wet lab are needed in order to validate the results.

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.

Immunoinformatic approach for the construction of multi-epitopes vaccine against omicron COVID-19 variant

The newly discovered SARS-CoV-2 Omicron variant B.1.1.529 is a Variant of Concern (VOC) announced by the World Health Organization (WHO). It's becoming increasingly difficult to keep these variants from spreading over the planet. The fifth wave has begun in several countries because of Omicron variant, and it is posing a threat to human civilization. As a result, we need effective vaccination that can tackle Omicron SARS-CoV-2 variants that are bound to emerge. Therefore, the current study is an initiative to design a peptide-based chimeric vaccine that may potentially battle SARS-CoV-2 Omicron variant. As a result, the most relevant epitopes present in the mutagenic areas of Omicron spike protein were identified using a set of computational tools and immunoinformatic techniques to uncover common MHC-1, MHC-II, and B cell epitopes that may have the ability to influence the host immune mechanism. A final of three epitopes from CD8⁺ T-cell, CD4⁺ T-cell epitopes, and B-cell were shortlisted from spike protein, and that are highly antigenic, IFN-γ inducer, as well as overlapping for the construction of twelve vaccine models. As a result, the antigenic epitopes were coupled with a flexible and stable peptide linker, and the adjuvant was added at the N-terminal end to create a unique vaccine candidate. The structure of a 3D vaccine candidate was refined, and its quality was assessed by using web servers. However, the applied immunoinformatic study along with the molecular docking and simulation of 12 modeled vaccines constructs against six distinct HLAs, and TLRs (TLR2, and TLR4) complexes revealed that the V1 construct was non-allergenic, non-toxic, highly immunogenic, antigenic, and most stable. The vaccine candidate's stability was confirmed by molecular dynamics investigations. Finally, we studied the expression of the suggested vaccination using codon optimization and in-silico cloning. The current study proposed V1 Multi-Epitope Vaccine (MEV) as a significant vaccine candidate that may help the scientific community to treat SARS-CoV-2 infections.

Promising Acinetobacter baumannii Vaccine Candidates and Drug Targets in Recent Years

In parallel to the uncontrolled use of antibiotics, the emergence of multidrug-resistant bacteria, like Acinetobacter baumannii, has posed a severe threat. A. baumannii predominates in the nosocomial setting due to its ability to persist in hospitals and survive antibiotic treatment, thereby eventually leading to an increasing prevalence and mortality due to its infection. With the increasing spectra of drug resistance and the incessant collapse of newly discovered antibiotics, new therapeutic countermeasures have been in high demand. Hence, recent research has shown favouritism towards the long-term solution of designing vaccines. Therefore, being a realistic alternative strategy to combat this pathogen, anti-A. Baumannii vaccines research has continued unearthing various antigens with variable results over the last decade. Again, other approaches, including pan-genomics, subtractive proteomics, and reverse vaccination strategies, have shown promise for identifying promiscuous core vaccine candidates that resulted in chimeric vaccine constructs. In addition, the integration of basic knowledge of the pathobiology of this drug-resistant bacteria has also facilitated the development of effective multiantigen vaccines. As opposed to the conventional trial-and-error approach, incorporating the in silico methods in recent studies, particularly network analysis, has manifested a great promise in unearthing novel vaccine candidates from the A. baumannii proteome. Some studies have used multiple A. baumannii data sources to build the co-functional networks and analyze them by k-shell decomposition. Additionally, Whole Genomic Protein Interactome (GPIN) analysis has utilized a rational approach for identifying essential proteins and presenting them as vaccines effective enough to combat the deadly pathogenic threats posed by A. baumannii. Others have identified multiple immune nodes using network-based centrality measurements for synergistic antigen combinations for different vaccination strategies. Protein-protein interactions have also been inferenced utilizing structural approaches, such as molecular docking and molecular dynamics simulation. Similar workflows and technologies were employed to unveil novel A. baumannii drug targets, with a similar trend in the increasing influx of in silico techniques. This review integrates the latest knowledge on the development of A. baumannii vaccines while highlighting the in silico methods as the future of such exploratory research. In parallel, we also briefly summarize recent advancements in A. baumannii drug target research.