Proteome-wide screening for designing a multi-epitope vaccine against emerging pathogen Elizabethkingia anophelis using immunoinformatic approaches

Development of a novel multi-epitope vaccine based on capsid and envelope protein against Chikungunya virus

Chikungunya virus (CHIKV), a type A virus borne by mosquitoes that can cause major clinical manifestations including rash, fever and debilitating arthritis, grown into a reemerging serious public health issue. Currently, there is no licensed therapy or vaccine available for CHIKV, although the most promising form of treatment appears to be immunotherapy. Neutralizing antibodies for CHIKV can provide high protection for all CHIKV strains, as well as other alphaviruses. Development of a protective vaccine may be an effective strategy to prevent the outbreak of CHIKV and provide protection for travelers. In this study, we designed a multi-epitope vaccine with a 543-amino-acid structure based on the E1, E2 and capsid proteins of CHIKV, including 6 CTL epitopes, 6 HTL epitopes, 12 linear B epitopes, along with the adjuvant β-defensin III. All T-cell epitopes were docked with their corresponding MHC alleles to validate their effect on inducing immune responses, and the vaccine's sequence was proven to have acceptable physicochemical properties. Further, the developed vaccine was docked with TLR3 and TLR8, both of which play an important role in recognizing RNA viruses. Basic analyses of the docked complexes and molecular dynamic simulations revealed that the vaccine interacted strongly with TLRs. Immunological simulations indicated that the vaccine could induce both cellular and humoral immunity. Hopefully, this proposed vaccine structure can serve as a viable candidate against CHIKV infection.Communicated by Ramaswamy H. Sarma.

Immunoinformatic-guided novel mRNA vaccine designing to elicit immunogenic responses against the endemic Monkeypox virus

Monkeypox virus (MPXV) is an orthopoxvirus, causing zoonotic infections in humans with smallpox-like symptoms. The WHO reported MPXV cases in May 2022 and the outbreak caused significant morbidity threats to immunocompromised individuals and children. Currently, no clinically validated therapies are available against MPXV infections. The present study is based on immunoinformatics approaches to design mRNA-based novel vaccine models against MPXV. Three proteins were prioritized based on high antigenicity, low allergenicity, and toxicity values to predict T- and B-cell epitopes. Lead T- and B-cell epitopes were used to design vaccine constructs, linked with epitope-specific linkers and adjuvant to enhance immune responses. Additional sequences, including Kozak sequence, MITD sequence, tPA sequence, Goblin 5', 3' UTRs, and a poly(A) tail were added to design stable and highly immunogenic mRNA vaccine construct. High-quality structures were predicted by molecular modeling and 3D-structural validation of the vaccine construct. Population coverage and epitope-conservancy speculated broader protection of designed vaccine model against multiple MPXV infectious strains. MPXV-V4 was eventually prioritized based on its physicochemical and immunological parameters and docking scores. Molecular dynamics and immune simulations analyses predicted significant structural stability and binding affinity of the top-ranked vaccine model with immune receptors to elicit cellular and humoral immunogenic responses against the MPXV. The pursuance of experimental and clinical follow-up of these prioritized constructs may lay the groundwork to develop safe and effective vaccine against MPXV.Communicated by Ramaswamy H. Sarma.

An Immunoinformatic-Based In Silico Identification on the Creation of a Multiepitope-Based Vaccination Against the Nipah Virus

The zoonotic viruses pose significant threats to public health. Nipah virus (NiV) is an emerging virus transmitted from bats to humans. The NiV causes severe encephalitis and acute respiratory distress syndrome, leading to high mortality rates, with fatality rates ranging from 40% to 75%. The first emergence of the disease was found in Malaysia in 1998-1999 and later in Bangladesh, Cambodia, Timor-Leste, Indonesia, Singapore, Papua New Guinea, Vietnam, Thailand, India, and other South and Southeast Asian nations. Currently, no specific vaccines or antiviral drugs are available. The potential advantages of epitope-based vaccines include their ability to elicit specific immune responses while minimizing potential side effects. The epitopes have been identified from the conserved region of viral proteins obtained from the UniProt database. The selection of conserved epitopes involves analyzing the genetic sequences of various viral strains. The present study identified two B cell epitopes, seven cytotoxic T lymphocyte (CTL) epitopes, and seven helper T lymphocyte (HTL) epitope interactions from the NiV proteomic inventory. The antigenic and physiological properties of retrieved protein were analyzed using online servers ToxinPred, VaxiJen v2.0, and AllerTOP. The final vaccine candidate has a total combined coverage range of 80.53%. The tertiary structure of the constructed vaccine was optimized, and its stability was confirmed with the help of molecular simulation. Molecular docking was performed to check the binding affinity and binding energy of the constructed vaccine with TLR-3 and TLR-5. Codon optimization was performed in the constructed vaccine within the Escherichia coli K12 strain, to eliminate the danger of codon bias. However, these findings must require further validation to assess their effectiveness and safety. The development of vaccines and therapeutic approaches for virus infection is an ongoing area of research, and it may take time before effective interventions are available for clinical use.

Subtractive proteomics-based vaccine targets annotation and reverse vaccinology approaches to identify multiepitope vaccine against Plesiomonas shigelloides

Plesiomonas shigelloides, an aquatic bacterium belonging to the Enterobacteriaceae family, is a frequent cause of gastroenteritis with diarrhea and gastrointestinal severe disease. Despite decades of research, discovering a licensed and globally accessible vaccine is still years away. Developing a putative vaccine that can combat the Plesiomonas shigelloides infection by boosting population immunity against P. shigelloides is direly needed. In the framework of the current study, the entire proteome of P. shigelloides was explored using subtractive genomics integrated with the immunoinformatics approach for designing an effective vaccine construct against P. shigelloides. The overall stability of the vaccine construct was evaluated using molecular docking, which demonstrated that MEV showed higher binding affinities with toll-like receptors (TLR4: 51.5 ± 10.3, TLR2: 60.5 ± 9.2) and MHC receptors(MHCI: 79.7 ± 11.2 kcal/mol, MHCII: 70.4 ± 23.7). Further, the therapeutic efficacy of the vaccine construct for generating an efficient immune response was evaluated by computational immunological simulation. Finally, computer-based cloning and improvement in codon composition without altering amino acid sequence led to the development of a proposed vaccine. In a nutshell, the findings of this study add to the existing knowledge about the pathogenesis of this infection. The schemed MEV can be a possible prophylactic agent for individuals infected with P. shigelloides. Nevertheless, further authentication is required to guarantee its safeness and immunogenic potential.

Structure-guided design and cloning of peptide inhibitors targeting CDK9/cyclin T1 protein-protein interaction

CDK9 (cyclin-dependent kinase 9) plays a significant role in numerous pathological conditions, such as HIV-1 infection and cancer. The interaction between CDK9 and cyclin T1 is crucial for maintaining the kinase's active state. Therefore, targeting this protein-protein interaction offers a promising strategy for inhibiting CDK9. In this study, we aimed to design and characterize a library of mutant peptides based on the binding region of cyclin T1 to CDK9. Using Osprey software, a total of 7,776 mutant peptides were generated. After conducting a comprehensive analysis, three peptides, namely, mp3 (RAADVEGQRKRRE), mp20 (RAATVEGQRKRRE), and mp29 (RAADVEGQDKRRE), were identified as promising inhibitors that possess the ability to bind to CDK9 with high affinity and exhibit low free binding energy. These peptides exhibited favorable safety profiles and displayed promising dynamic behaviors. Notably, our findings revealed that the mp3 and mp29 peptides interacted with a conserved sequence in CDK9 (residues 60-66). In addition, by designing the structure of potential peptides in the plasmid vector pET28a (+), we have been able to pave the way for facilitating the process of their recombinant production in an Escherichia coli expression system in future studies. Predictions indicated good solubility upon overexpression, further supporting their potential for downstream applications. While these results demonstrate the promise of the designed peptides as blockers of CDK9 with high affinity, additional experimental studies are required to validate their biological activity and assess their selectivity. Such investigations will provide valuable insights into their therapeutic potential and pave the way for the future development of peptide-based inhibitors targeting the CDK9-cyclin T1 complex.

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.

Development of a novel multi‑epitope vaccine against the pathogenic human polyomavirus V6/7 using reverse vaccinology

BACKGROUND

Human polyomaviruses contribute to human oncogenesis through persistent infections, but currently there is no effective preventive measure against the malignancies caused by this virus. Therefore, the development of a safe and effective vaccine against HPyV is of high priority.

METHODS

First, the proteomes of 2 polyomavirus species (HPyV6 and HPyV7) were downloaded from the NCBI database for the selection of the target proteins. The epitope identification process focused on selecting proteins that were crucial, associated with virulence, present on the surface, antigenic, non-toxic, and non-homologous with the human proteome. Then, the immunoinformatic methods were used to identify cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and B-cell epitopes from the target antigens, which could be used to create epitope-based vaccine. The physicochemical features of the designed vaccine were predicted through various online servers. The binding pattern and stability between the vaccine candidate and Toll-like receptors were analyzed through molecular docking and molecular dynamics (MD) simulation, while the immunogenicity of the designed vaccines was assessed using immune simulation.

RESULTS

Online tools were utilized to forecast the most optimal epitope from the immunogenic targets, including LTAg, VP1, and VP1 antigens of HPyV6 and HPyV7. A multi-epitope vaccine was developed by combining 10 CTL, 7 HTL, and 6 LBL epitopes with suitable linkers and adjuvant. The vaccine displayed 98.35% of the world's population coverage. The 3D model of the vaccine structure revealed that the majority of residues (87.7%) were located in favored regions of the Ramachandran plot. The evaluation of molecular docking and MD simulation revealed that the constructed vaccine exhibits a strong binding (-1414.0 kcal/mol) towards the host's TLR4. Moreover, the vaccine-TLR complexes remained stable throughout the dynamic conditions present in the natural environment. The immune simulation results demonstrated that the vaccine design had the capacity to elicit robust immune responses in the host.

CONCLUSION

The multi-parametric analysis revealed that the designed vaccine is capable of inducing sustained immunity against the selected polyomaviruses, although further in-vivo investigations are needed to verify its effectiveness.

Immunoinformatics, molecular docking and dynamics simulation approaches unveil a multi epitope-based potent peptide vaccine candidate against avian leukosis virus

Lymphoid leukosis is a poultry neoplastic disease caused by avian leukosis virus (ALV) and is characterized by high morbidity and variable mortality rates in chicks. Currently, no effective treatment and vaccination is the only means to control it. This study exploited the immunoinformatics approaches to construct multi-epitope vaccine against ALV. ABCpred and IEDB servers were used to predict B and T lymphocytes epitopes from the viral proteins, respectively. Antigenicity, allergenicity and toxicity of the epitopes were assessed and used to construct the vaccine with suitable adjuvant and linkers. Secondary and tertiary structures of the vaccine were predicted, refined and validated. Structural errors, solubility, stability, immune simulation, dynamic simulation, docking and in silico cloning were also evaluated.The constructed vaccine was hydrophilic, antigenic and non-allergenic. Ramchandran plot showed most of the residues in the favored and additional allowed regions. ProsA server showed no errors in the vaccine structure. Immune simulation showed significant immunoglobulins and cytokines levels. Stability was enhanced by disulfide engineering and molecular dynamic simulation. Docking of the vaccine with chicken's TLR7 revealed competent binding energies.The vaccine was cloned in pET-30a(+) vector and efficiently expressed in Escherichia coli. This study provided a potent peptide vaccine that could assist in tailoring a rapid and cost-effective vaccine that helps to combat ALV. However, experimental validation is required to assess the vaccine efficiency.

Core-genome-mediated promising alternative drug and multi-epitope vaccine targets prioritization against infectious Clostridium difficile

Prevention of Clostridium difficile infection is challenging worldwide owing to its high morbidity and mortality rates. C. difficile is currently being classified as an urgent threat by the CDC. Devising a new therapeutic strategy become indispensable against C. difficile infection due to its high rates of reinfection and increasing antimicrobial resistance. The current study is based on core proteome data of C. difficile to identify promising vaccine and drug candidates. Immunoinformatics and vaccinomics approaches were employed to construct multi-epitope-based chimeric vaccine constructs from top-ranked T- and B-cell epitopes. The efficacy of the designed vaccine was assessed by immunological analysis, immune receptor binding potential and immune simulation analyses. Additionally, subtractive proteomics and druggability analyses prioritized several promising and alternative drug targets against C. difficile. These include FMN-dependent nitroreductase which was prioritized for pharmacophore-based virtual screening of druggable molecule databases to predict potent inhibitors. A MolPort-001-785-965 druggable molecule was found to exhibit significant binding affinity with the conserved residues of FMN-dependent nitroreductase. The experimental validation of the therapeutic targets prioritized in the current study may worthy to identify new strategies to combat the drug-resistant C. difficile infection.

Leveraging immunoinformatics for developing a multi-epitope subunit vaccine against Helicobacter pylori and Fusobacterium nucleatum

Gastric ulcers caused by Helicobacter pylori and Fusobacterium nucleatum remain a significant global health concern without an established vaccine. In this study, we utilized immunoinformatics methods to design a multi-epitope vaccine targeting these pathogens. Outer membrane proteins from H. pylori and F. nucleatum were scrutinized to identify high antigenic T-cell and B-cell epitopes. The resulting vaccine comprised carefully analyzed and evaluated epitopes, including cytotoxic T-lymphocytes, helper T-lymphocytes, and linear B-lymphocytes epitopes. This vaccine exhibited notable antigenicity, suitable immunogenicity, and demonstrated non-allergenicity and non-toxicity. It displayed favorable physiochemical characteristics and high solubility. In interaction studies, the vaccine exhibited robust binding to toll-like receptor 4 (TLR4). Molecular dynamic simulations revealed cohesive structural integrity and stable attachment. Codon adaptation utilizing Escherichia coli K12 host yielded a vaccine with elevated Codon Adaptation Index (CAI) and optimal GC content. In silico cloning into the pET28+(a) vector demonstrated efficient expression. Immune simulations indicated the vaccine's ability to initiate immune responses in humans, mirroring real-life scenarios. Based on these comprehensive findings, we propose that our developed vaccine has the potential to confer robust immunity against H. pylori and F. nucleatum infections.Communicated by Ramaswamy H. Sarma.

Development of a novel circular mRNA vaccine of six protein combinations against Staphylococcus aureus

Staphylococcus aureus is an extraordinarily versatile pathogen, which is currently the most common cause of nosocomial and community infections. Considering that increased antibiotic resistance may hasten the spread of S. aureus, developing an effective vaccine can possibly aid in its control. The RNA vaccine coding immunodominance epitopes from bacteria provide a potential method to induce T and B cell immune responses by translating them into cells. Furthermore, using bioinformatics to create circular RNA vaccines can ensure that the translation of the vaccine is potent and durable. In this study, 7 cytotoxic T lymphocyte (CTL) epitopes, 4 helper T lymphocyte (HTL) epitopes, and 15 B cell epitopes from 6 proteins that are closely associated with the S. aureus virulence and invasion and critical to natural immune responses were mapped. To verify their interactions, all epitopes were docked with the corresponding MHC alleles. The final vaccine was composed of 26 epitopes and the adjuvant β-defencin, and a disulfide bond was also introduced to improve its stability. After the prediction of structure and characteristics, the developed vaccine was docked with TLR2 and TLR4, which induce immunological responses in S. aureus infection. According to the molecular dynamic simulation, the vaccine might interact strongly with TLRs. Meanwhile, it performed well in immunological simulation and population coverage prediction. Finally, the vaccine was converted into a circular RNA using a series of helper sequences to aid in vaccine circulation translation. Hopefully, this proposed structure will be proven to serve a viable vaccine against S. aureus.Communicated by Ramaswamy H. Sarma.

Genomic annotation for vaccine target identification and immunoinformatics-guided multi-epitope-based vaccine design against Songling virus through screening its whole genome encoded proteins

Songling virus (SGLV), a newly discovered tick-borne orthonairovirus, was recently identified in human spleen tissue. It exhibits cytopathic effects in human hepatoma cells and is associated with clinical symptoms including headache, fever, depression, fatigue, and dizziness, but no treatments or vaccines exist for this pathogenic virus. In the current study, immunoinformatics techniques were employed to identify potential vaccine targets within SGLV by comprehensively analyzing SGLV proteins. Four proteins were chosen based on specific thresholds to identify B-cell and T-cell epitopes, validated through IFN-γ epitopes. Six overlap MHC-I, MHC-II, and B cell epitopes were chosen to design a comprehensive vaccine candidate, ensuring 100% global coverage. These structures were paired with different adjuvants for broader protection against international strains. Vaccine constructions' 3D models were high-quality and validated by structural analysis. After molecular docking, SGLV-V4 was selected for further research due to its lowest binding energy (-66.26 kcal/mol) and its suitable immunological and physiochemical properties. The vaccine gene is expressed significantly in E. coli bacteria through in silico cloning. Immunological research and MD simulations supported its molecular stability and robust immune response within the host cell. These findings can potentially be used in designing safer and more effective experimental SGLV-V4 vaccines.

Vaccinomics-aided next-generation novel multi-epitope-based vaccine engineering against multidrug resistant Shigella Sonnei: Immunoinformatics and chemoinformatics approaches

Shigella sonnei is a gram-negative bacterium and is the primary cause of shigellosis in advanced countries. An exceptional rise in the prevalence of the disease has been reported in Asia, the Middle East, and Latin America. To date, no preventive vaccine is available against S. sonnei infections. This pathogen has shown resistances towards both first- and second-line antibiotics. Therefore, an effective broad spectrum vaccine development against shigellosis is indispensable. In the present study, vaccinomics-aided immunoinformatics strategies were pursued to identify potential vaccine candidates from the S. sonnei whole proteome data. Pathogen essential proteins that are non-homologous to human and human gut microbiome proteome set, are feasible candidates for this purpose. Three antigenic outer membrane proteins were prioritized to predict lead epitopes based on reverse vaccinology approach. Multi-epitope-based chimeric vaccines was designed using lead B- and T-cell epitopes combined with suitable linker and adjuvant peptide sequences to enhance immune responses against the designed vaccine. The SS-MEVC construct was prioritized based on multiple physicochemical, immunological properties, and immune-receptors docking scores. Immune simulation analysis predicted strong immunogenic response capability of the designed vaccine construct. The Molecular dynamic simulations analysis ensured stable molecular interactions of lead vaccine construct with the host receptors. In silico restriction and cloning analysis predicted feasible cloning capability of the SS-MEVC construct within the E. coli expression system. The proposed vaccine construct is predicted to be more safe, effective and capable of inducing robust immune responses against S. sonnei infections and may be worthy of examination via in vitro/in vivo assays.

Development of a tetravalent subunit vaccine against dengue virus through a vaccinomics approach

Dengue virus infection (DVI) is a mosquito-borne disease that can lead to serious morbidity and mortality. Dengue fever (DF) is a major public health concern that affects approximately 3.9 billion people each year globally. However, there is no vaccine or drug available to deal with DVI. Dengue virus consists of four distinct serotypes (DENV1-4), each raising a different immunological response. In the present study, we designed a tetravalent subunit multi-epitope vaccine, targeting proteins including the structural protein envelope domain III (EDIII), precursor membrane proteins (prM), and a non-structural protein (NS1) from each serotype by employing an immunoinformatic approach. Only conserved sequences obtained through a multiple sequence alignment were used for epitope mapping to ensure efficacy against all serotypes. The epitopes were shortlisted based on an IC50 value <50, antigenicity, allergenicity, and a toxicity analysis. In the final vaccine construct, overall, 11 B-cell epitopes, 10 HTL epitopes, and 10 CTL epitopes from EDIII, prM, and NS1 proteins targeting all serotypes were selected and joined via KK, AAY, and GGGS linkers, respectively. We incorporated a 45-amino-acid-long B-defensins adjuvant in the final vaccine construct for a better immunogenic response. The vaccine construct has an antigenic score of 0.79 via VaxiJen and is non-toxic and non-allergenic. Our refined vaccine structure has a Ramachandran score of 96.4%. The vaccine has shown stable interaction with TLR3, which has been validated by 50 ns of molecular dynamics (MD) simulation. Our findings propose that a designed multi-epitope vaccine has substantial potential to elicit a strong immune response against all dengue serotypes without causing any adverse effects. Furthermore, the proposed vaccine can be experimentally validated as a probable vaccine, suggesting it may serve as an effective preventative measure against dengue virus infection.

Identification of potential novel therapeutic drug target against Elizabethkingia anophelis by integrative pan and subtractive genomic analysis: An in silico approach

Elizabethkingia anophelis is a human pathogen responsible for severe nosocomial infections in neonates and immunocompromised patients. The significantly higher mortality rate from E. anophelis infections and the lack of available regimens highlight the critical need to explore novel drug targets. The current study investigated effective novel drug targets by employing a comprehensive in silico subtractive genomic approach integrated with pangenomic analysis of E. anophelis strains. A total of 2809 core genomic proteins were found by pangenomic analysis of non-paralogous proteins. Subsequently, 156 pathogen-specific, 442 choke point, 202 virulence factor, 53 antibiotic resistant and 119 host-pathogen interacting proteins were identified in E. anophelis. By subtractive genomic approach, at first 791 proteins were found to be indispensable for the survival of E. anophelis. 558 and 315 proteins were detected as non-homologous to human and gut microflora respectively. Following that 245 cytoplasmic, 245 novel, and 23 broad-spectrum targets were selected and finally four proteins were considered as potential therapeutic targets of E. anophelis based on highest degree score in PPI network. Among those, three proteins were subjected to molecular docking and subsequent MD simulation as one protein did not contain a plausible binding pocket with sufficient surface area and volume. All the complexes were found to be stable and compact in 100 ns molecular dynamics simulation studies as measured by RMSD, RMSF, and Rg. These three short-listed targets identified in this study may lead to the development of novel antimicrobials capable of curing infections and pave the way to prevent and control the disease progression caused by the deadly agent E. anophelis.

Design of a novel multi-epitope vaccine candidate against endometrial cancer using immunoinformatics and bioinformatics approaches

Endometrial cancer (EC) is one of the most common cancers of the female reproductive system. Multi-epitope vaccine may be a promising and effective strategy against EC. In this study, we designed a novel multi-epitope vaccine based on the antigenic proteins PRAME and TMPRSS4 using immunoinformatics and bioinformatics approaches. After a rigorous selection process, 14 cytotoxic T lymphocyte (CTL) epitopes, 6 helper T lymphocyte (HTL) epitopes, and 8 B cell epitopes (BCEs) were finally selected for vaccine construction. To enhance the immunogenicity of the vaccine candidate, the pan HLA DR-binding epitope was included in the vaccine design as an adjuvant. The final vaccine construct had 455 amino acids and a molecular weight of 49.8 kDa, and was predicted to cover 95.03% of the total world population. Docking analysis showed that there were 10 hydrogen bonds and 19 hydrogen bonds in the vaccine-HLA-A*02:01 and vaccine-HLA-DRB1*01:01 complexes, respectively, indicating that the vaccine has a good affinity to MHC molecules. This was further supported by molecular dynamics (MD) simulation. Immune simulation showed that the designed vaccine was able to induce higher levels of immune cell activity, with the secretion of numerous cytokines. The codon adaptation index (CAI) value and GC content of the optimised codon sequences of the vaccine were 0.986 and 54.43%, respectively, indicating that the vaccine has the potential to be highly expressed. The in silico analysis suggested that the designed vaccine may provide a novel therapeutic option for the individualised treatment of EC patients in the future.Communicated by Ramaswamy H. Sarma.

Vaccinomics-based next-generation multi-epitope chimeric vaccine models prediction against Leishmania tropica - a hierarchical subtractive proteomics and immunoinformatics approach

Leishmania tropica is a vector-borne parasitic protozoa that is the leading cause of leishmaniasis throughout the global tropics and subtropics. L. tropica is a multidrug-resistant parasite with a diverse set of serological, biochemical, and genomic features. There are currently no particular vaccines available to combat leishmaniasis. The present study prioritized potential vaccine candidate proteins of L. tropica using subtractive proteomics and vaccinomics approaches. These vaccine candidate proteins were downstream analyzed to predict B- and T-cell epitopes based on high antigenicity, non-allergenic, and non-toxic characteristics. The top-ranked overlapping MHC-I, MHC-II, and linear B-cell epitopes were prioritized for model vaccine designing. The lead epitopes were linked together by suitable linker sequences to design multi-epitope constructs. Immunogenic adjuvant sequences were incorporated at the N-terminus of the model vaccine constructs to enhance their immunological potential. Among different combinations of constructs, four vaccine designs were selected based on their physicochemical and immunological features. The tertiary structure models of the designed vaccine constructs were predicted and verified. The molecular docking and molecular dynamic (MD) simulation analyses indicated that the vaccine design V1 demonstrated robust and stable molecular interactions with toll-like receptor 4 (TLR4). The top-ranked vaccine construct model-IV demonstrated significant expressive capability in the E. coli expression system during in-silico restriction cloning analysis. The results of the present study are intriguing; nevertheless, experimental bioassays are required to validate the efficacy of the predicted model chimeric vaccine.

In silico and immunoinformatics based multiepitope subunit vaccine design for protection against visceral leishmaniasis

Visceral leishmaniasis (VL) is a vector-borne neglected tropical protozoan disease with high fatality and no certified vaccine. Conventional vaccine preparation is challenging and tedious. Here in this work, we created a global multiepitope subunit vaccination against VL utilizing innovative immunoinformatics technique based on the extensively conserved epitopic regions of the PrimPol protein of Leishmania donovani consisting of four subunits which were analyzed and studied, out of which DNA primase large subunit and DNA polymerase α subunit B were evaluated as antigens by Vaxijen 2.0. The multiepitope vaccine design includes a single adjuvant β-defensins, eight CTL epitopes, eight HTL epitopes, seven linear BCL epitopes and one discontinuous BCL epitope to induce innate, cellular and humoral immune responses against VL. The Expasy ProtParam tool characterized the physiochemical parameters of the vaccine. At the same time, SOLpro evaluated our vaccine constructs to be soluble upon expression. We also modeled the stable tertiary structure of our vaccine construct through Robetta modeling for molecular docking studies with toll-like receptor proteins through HADDOCK 2.4. Simulations based on molecular dynamics revealed an intact vaccine and TLR8 complex, supporting our vaccine design's immunogenicity. Also, the immune simulation of our vaccine by the C-ImmSim server demonstrated the potency of the multiepitope vaccine construct to induce proper immune response for host defense. Codon optimization and in silico cloning of our vaccine further assured high expression. The outcomes of our study on multiepitope vaccine design significantly produced a potential candidate against VL and can potentially eradicate the disease in the future after clinical investigations.Communicated by Ramaswamy H. Sarma.

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.

Elucidation of novel compounds and epitope-based peptide vaccine design against C30 endopeptidase regions of SARS-CoV-2 using immunoinformatics approaches

There has been progressive improvement in immunoinformatics approaches for epitope-based peptide design. Computational-based immune-informatics approaches were applied to identify the epitopes of SARS-CoV-2 to develop vaccines. The accessibility of the SARS-CoV-2 protein surface was analyzed, and hexa-peptide sequences (KTPKYK) were observed having a maximum score of 8.254, located between amino acids 97 and 102, whereas the FSVLAC at amino acids 112 to 117 showed the lowest score of 0.114. The surface flexibility of the target protein ranged from 0.864 to 1.099 having amino acid ranges of 159 to 165 and 118 to 124, respectively, harboring the FCYMHHM and YNGSPSG hepta-peptide sequences. The surface flexibility was predicted, and a 0.864 score was observed from amino acids 159 to 165 with the hepta-peptide (FCYMHHM) sequence. Moreover, the highest score of 1.099 was observed between amino acids 118 and 124 against YNGSPSG. B-cell epitopes and cytotoxic T-lymphocyte (CTL) epitopes were also identified against SARS-CoV-2. In molecular docking analyses, -0.54 to -26.21 kcal/mol global energy was observed against the selected CTL epitopes, exhibiting binding solid energies of -3.33 to -26.36 kcal/mol. Based on optimization, eight epitopes (SEDMLNPNY, GSVGFNIDY, LLEDEFTPF, DYDCVSFCY, GTDLEGNFY, QTFSVLACY, TVNVLAWLY, and TANPKTPKY) showed reliable findings. The study calculated the associated HLA alleles with MHC-I and MHC-II and found that MHC-I epitopes had higher population coverage (0.9019% and 0.5639%) than MHC-II epitopes, which ranged from 58.49% to 34.71% in Italy and China, respectively. The CTL epitopes were docked with antigenic sites and analyzed with MHC-I HLA protein. In addition, virtual screening was conducted using the ZINC database library, which contained 3,447 compounds. The 10 top-ranked scrutinized molecules (ZINC222731806, ZINC077293241, ZINC014880001, ZINC003830427, ZINC030731133, ZINC003932831, ZINC003816514, ZINC004245650, ZINC000057255, and ZINC011592639) exhibited the least binding energy (-8.8 to -7.5 kcal/mol). The molecular dynamics (MD) and immune simulation data suggest that these epitopes could be used to design an effective SARS-CoV-2 vaccine in the form of a peptide-based vaccine. Our identified CTL epitopes have the potential to inhibit SARS-CoV-2 replication.

Advances in Computational and Bioinformatics Tools and Databases for Designing and Developing a Multi-Epitope-Based Peptide Vaccine

A vaccine is defined as a biologic preparation that trains the immune system, boosts immunity, and protects against a deadly microbial infection. They have been used for centuries to combat a variety of contagious illnesses by means of subsiding the disease burden as well as eradicating the disease. Since infectious disease pandemics are a recurring global threat, vaccination has emerged as one of the most promising tools to save millions of lives and reduce infection rates. The World Health Organization reports that immunization protects three million individuals annually. Currently, multi-epitope-based peptide vaccines are a unique concept in vaccine formulation. Epitope-based peptide vaccines utilize small fragments of proteins or peptides (parts of the pathogen), called epitopes, that trigger an adequate immune response against a particular pathogen. However, conventional vaccine designing and development techniques are too cumbersome, expensive, and time-consuming. With the recent advancement in bioinformatics, immunoinformatics, and vaccinomics discipline, vaccine science has entered a new era accompanying a modern, impressive, and more realistic paradigm in designing and developing next-generation strong immunogens. In silico designing and developing a safe and novel vaccine construct involves knowledge of reverse vaccinology, various vaccine databases, and high throughput techniques. The computational tools and techniques directly associated with vaccine research are extremely effective, economical, precise, robust, and safe for human use. Many vaccine candidates have entered clinical trials instantly and are available prior to schedule. In light of this, the present article provides researchers with up-to-date information on various approaches, protocols, and databases regarding the computational designing and development of potent multi-epitope-based peptide vaccines that can assist researchers in tailoring vaccines more rapidly and cost-effectively.

In silico design and immunoinformatics analysis of a universal multi-epitope vaccine against monkeypox virus

Monkeypox virus (MPXV) outbreaks have been reported in various countries worldwide; however, there is no specific vaccine against MPXV. In this study, therefore, we employed computational approaches to design a multi-epitope vaccine against MPXV. Initially, cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), linear B lymphocytes (LBL) epitopes were predicted from the cell surface-binding protein and envelope protein A28 homolog, both of which play essential roles in MPXV pathogenesis. All of the predicted epitopes were evaluated using key parameters. A total of 7 CTL, 4 HTL, and 5 LBL epitopes were chosen and combined with appropriate linkers and adjuvant to construct a multi-epitope vaccine. The CTL and HTL epitopes of the vaccine construct cover 95.57% of the worldwide population. The designed vaccine construct was found to be highly antigenic, non-allergenic, soluble, and to have acceptable physicochemical properties. The 3D structure of the vaccine and its potential interaction with Toll-Like receptor-4 (TLR4) were predicted. Molecular dynamics (MD) simulation confirmed the vaccine's high stability in complex with TLR4. Finally, codon adaptation and in silico cloning confirmed the high expression rate of the vaccine constructs in strain K12 of Escherichia coli (E. coli). These findings are very encouraging; however, in vitro and animal studies are needed to ensure the potency and safety of this vaccine candidate.

Construction and validation of a multi-epitope in silico vaccine model for lymphatic filariasis by targeting Brugia malayi: a reverse vaccinology approach

BACKGROUND

Lymphatic filariasis (LF), often referred to as elephantiasis, has been identified as one of the 17 neglected tropical diseases by the World Health Organization. Currently, there are no vaccines available to treat this infection in humans. Therefore, with the objective of devising a novel preventive measure, we exploited an immunoinformatics approach to design a multi-epitope-based subunit vaccine for LF, that can elicit a variety of immune responses within the host. In this study, different B cell, T_C cell, and T_H cell-binding epitopes were screened from the antigenic proteins of Brugia malayi and they were passed through several immunological filters to determine the optimal epitopes.

RESULTS

As a result, 15 CD8+, 3 CD4+, and 3 B cell epitopes were found to be prominent, antigenic, non-toxic, immunogenic and non-allergenic. The presence of conformational B cell epitopes and cytokine-inducing epitopes confirmed the humoral and cell-mediated immune response that would be triggered by the constructed vaccine model. Following that, the selected epitopes and TLR-4-specific adjuvant were ligated by appropriate peptide linkers to finalize the vaccine construct. Protein-protein docking of the vaccine structure with the TLR4 receptor predicted strong binding affinity and hence putatively confirms its ability to elicit an immune response. Further, the efficiency of the vaccine candidate to provide a long-lasting protective immunity was assessed by in silico immune simulation. The reverse translated vaccine sequence was also virtually cloned in the pET28a (+) plasmid after the optimization of the gene sequence.

CONCLUSION

So taken together, by monitoring the overall in silico assessment, we hypothesize that our engineered peptide vaccine could be a viable prophylactic approach in the development of vaccines against the threat of human lymphatic filariasis.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s42269-023-01013-0.

In silico formulation of a next-generation multiepitope vaccine for use as a prophylactic candidate against Crimean-Congo hemorrhagic fever

BACKGROUND

Crimean-Congo hemorrhagic fever (CCHF) is a widespread disease transmitted to humans and livestock animals through the bite of infected ticks or close contact with infected persons' blood, organs, or other bodily fluids. The virus is responsible for severe viral hemorrhagic fever outbreaks, with a case fatality rate of up to 40%. Despite having the highest fatality rate of the virus, a suitable treatment option or vaccination has not been developed yet. Therefore, this study aimed to formulate a multiepitope vaccine against CCHF through computational vaccine design approaches.

METHODS

The glycoprotein, nucleoprotein, and RNA-dependent RNA polymerase of CCHF were utilized to determine immunodominant T- and B-cell epitopes. Subsequently, an integrative computational vaccinology approach was used to formulate a multi-epitopes vaccine candidate against the virus.

RESULTS

After rigorous assessment, a multiepitope vaccine was constructed, which was antigenic, immunogenic, and non-allergenic with desired physicochemical properties. Molecular dynamics (MD) simulations of the vaccine-receptor complex show strong stability of the vaccine candidates to the targeted immune receptor. Additionally, the immune simulation of the vaccine candidates found that the vaccine could trigger real-life-like immune responses upon administration to humans.

CONCLUSIONS

Finally, we concluded that the formulated multiepitope vaccine candidates would provide excellent prophylactic properties against CCHF.

In silico design of epitope-based peptide vaccine against non-typhoidal Salmonella through immunoinformatic approaches

Non-typhoidal Salmonella (NTS) is one of the leading bacterial causes of many invasive human infections with a high antibiotic resistance profile. With this concern, the current study aimed to design an effective epitope-based peptide vaccine against NTS species as a successive and substitutive protective measure of invasive NTS disease. To design rationally, the current study considered a comprehensive in silico workflow combination of both immunoinformatics and molecular modeling approaches, including molecular docking and molecular dynamics (MD) simulation. We identified the two most promising T cell epitopes KVLYGIFAI and YGIFAITAL, and three B cell epitopes AAPVQVGEAAGS, TGGGDGSNT, and TGGGDGSNTGTTTT, in the outer membrane of NTS. Using these epitopes, a multiepitope vaccine was subsequently constructed along with appropriate adjuvant and linkers, which showed a good binding affinity and stability with toll-like receptor 2 (TLR2) in both molecular docking and MD simulation. Furthermore, in silico immune simulation described a strong immune response with a high number of antibodies, interferon-γ, and activated B and T cells. This study collectively suggests that predicted vaccine constructs could be considered potential vaccine candidates against common NTS species.Communicated by Ramaswamy H. Sarma.

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.

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

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

Vaccinomics to Design a Multiepitope Vaccine against Legionella pneumophila

Legionella pneumophila is found in the natural aquatic environment and can resist a wide range of environmental conditions. There are around fifty species of Legionella, at least twenty-four of which are directly linked to infections in humans. L. pneumophila is the cause of Legionnaires' disease, a potentially lethal form of pneumonia. By blocking phagosome-lysosome fusion, L. pneumophila lives and proliferates inside macrophages. For this disease, there is presently no authorized multiepitope vaccine available. For the multi-epitope-based vaccine (MEBV), the best antigenic candidates were identified using immunoinformatics and subtractive proteomic techniques. Several immunoinformatics methods were utilized to predict B and T cell epitopes from vaccine candidate proteins. To construct an in silico vaccine, epitopes (07 CTL, 03 HTL, and 07 LBL) were carefully selected and docked with MHC molecules (MHC-I and MHC-II) and human TLR4 molecules. To increase the immunological response, the vaccine was combined with a 50S ribosomal adjuvant. To maximize vaccine protein expression, MEBV was cloned and reverse-translated in Escherichia coli. To prove the MEBV's efficacy, more experimental validation is required. After its development, the resulting vaccine is greatly hoped to aid in the prevention of L. pneumophila infections.

Not all T cell epitopes are equally desired: a review of in silico tools for the prediction of cytokine-inducing potential of T-cell epitopes

Assessment of protective or harmful T cell response induced by any antigenic epitope is important in designing any immunotherapeutic molecule. The understanding of cytokine induction potential also helps us to monitor antigen-specific cellular immune responses and rational vaccine design. The classical immunoinformatics tools served well for prediction of B cell and T cell epitopes. However, in the last decade, the prediction algorithms for T cell epitope inducing specific cytokines have also been developed and appreciated in the scientific community. This review summarizes the current status of such tools, their applications, background algorithms, their use in experimental setup and functionalities available in the tools/web servers.

Molecular modelling on multiepitope-based vaccine against SARS-CoV-2 using immunoinformatics, molecular docking, and molecular dynamics simulation

The pandemic of COVID-19 caused by SARS-CoV-2 has made a worldwide health emergency. Despite the fact that current vaccines are readily available, several SARSCoV-2 variants affecting the existing vaccine are to be less effective due to the mutations in the structural proteins. Furthermore, the appearance of the new variants cannot be easily predicted in the future. Therefore, the attempts to construct new vaccines or to modify the current vaccines are still pivotal works for preventing the spread of the virus. In the present investigation, the computational analysis through immunoinformatics, molecular docking, and molecular dynamics (MD) simulation is employed to construct an effective vaccine against SARS-CoV2. The structural proteins of SARS-CoV2 are utilized to create a multiepitope-based vaccine (MEV). According to our findings presented by systematic procedures in the current investigation, the MEV construct may be able to trigger a strong immunological response against the virus. Therefore, the designed MEV could be a potential vaccine candidate against SARS-CoV-2, and also it is expected to be effective for other variants.

Multi-epitope chimeric vaccine design against emerging Monkeypox virus via reverse vaccinology techniques- a bioinformatics and immunoinformatics approach

The emerging monkeypox virus (MPXV) is a zoonotic orthopoxvirus that causes infections in humans similar to smallpox. Since May 2022, cases of monkeypox (MPX) have been increasingly reported by the World Health Organization (WHO) worldwide. Currently, there are no clinically validated treatments for MPX infections. In this study, an immunoinformatics approach was used to identify potential vaccine targets against MPXV. A total of 190 MPXV-2022 proteins were retrieved from the ViPR database and subjected to various analyses including antigenicity, allergenicity, toxicity, solubility, IFN-γ, and virulence. Three outer membrane and extracellular proteins were selected based on their respective parameters to predict B-cell and T-cell epitopes. The epitopes are conserved among different strains of MPXV and the population coverage is 100% worldwide, which will provide broader protection against various strains of the virus globally. Nine overlapping MHC-I, MHC-II, and B-cell epitopes were selected to design multi-epitope vaccine constructs linked with suitable linkers in combination with different adjuvants to enhance the immune responses of the vaccine constructs. Molecular modeling and structural validation ensured high-quality 3D structures of vaccine constructs. Based on various immunological and physiochemical properties and docking scores, MPXV-V2 was selected for further investigation. In silico cloning revealed a high level of gene expression for the MPXV-V2 vaccine within the bacterial expression system. Immune and MD simulations confirmed the molecular stability of the MPXV-V2 construct, with high immune responses within the host cell. These results may aid in the development of experimental vaccines against MPXV with increased potency and improved safety.

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.

Application of reverse vaccinology to design a multi-epitope subunit vaccine against a new strain of Aeromonas veronii

BACKGROUND

Aeromonas veronii is one of the most common pathogens of freshwater fishes that cause sepsis and ulcers. There are increasing numbers of cases showing that it is a significant zoonotic and aquatic agent. Epidemiological studies have shown that A. veronii virulence and drug tolerance have both increased over the last few years as a result of epidemiological investigations. Cadaverine reverse transporter (CadB) and maltoporin (LamB protein) contribute to the virulence of A. veronii TH0426. TH0426 strain is currently showing severe cases on fish species, and its resistance against therapeutic has been increasing. Despite these devastating complications, there is still no effective cure or vaccine for this strain of A.veronii.

RESULTS

In this regard, an immunoinformatic method was used to generate an epitope-based vaccine against this pathogen. The immunodominant epitopes were identified using the CadB and LamB protein of A. veronii. The final constructed vaccine sequence was developed to be immunogenic, non-allergenic as well as have better solubility. Molecular dynamic simulation revealed significant binding stability and structural compactness. Finally, using Escherichia coli K12 as a model, codon optimization yielded ideal GC content and a higher CAI value, which was then included in the cloning vector pET2+ (a).

CONCLUSION

Altogether, our outcomes imply that the proposed peptide vaccine might be a good option for A. veronii TH0426 prophylaxis.

Development of a Multiepitope Vaccine Against SARS-CoV-2: Immunoinformatics Study

Background

Since the first appearance of SARS-CoV-2 in China in December 2019, the world witnessed the emergence of the SARS-CoV-2 outbreak. Due to the high transmissibility rate of the virus, there is an urgent need to design and develop vaccines against SARS-CoV-2 to prevent more cases affected by the virus.

Objective

A computational approach is proposed for vaccine design against the SARS-CoV-2 spike (S) protein, as the key target for neutralizing antibodies, and envelope (E) protein, which contains a conserved sequence feature.

Methods

We used previously reported epitopes of S protein detected experimentally and further identified a collection of predicted B-cell and major histocompatibility (MHC) class II–restricted T-cell epitopes derived from E proteins with an identical match to SARS-CoV-2 E protein.

Results

The in silico design of our candidate vaccine against the S and E proteins of SARS-CoV-2 demonstrated a high affinity to MHC class II molecules and effective results in immune response simulations.

Conclusions

Based on the results of this study, the multiepitope vaccine designed against the S and E proteins of SARS-CoV-2 may be considered as a new, safe, and efficient approach to combatting the COVID-19 pandemic.

Pan-Genome Analysis of Oral Bacterial Pathogens to Predict a Potential Novel Multi-Epitopes Vaccine Candidate

Porphyromonas gingivalis is a Gram-negative anaerobic bacterium, mainly present in the oral cavity and causes periodontal infections. Currently, no licensed vaccine is available against P. gingivalis and other oral bacterial pathogens. To develop a vaccine against P. gingivalis, herein, we applied a bacterial pan-genome analysis (BPGA) on the bacterial genomes that retrieved a total number of 4908 core proteins, which were further utilized for the identification of good vaccine candidates. After several vaccine candidacy analyses, three proteins, namely lytic transglycosylase domain-containing protein, FKBP-type peptidyl-propyl cis-trans isomerase and superoxide dismutase, were shortlisted for epitopes prediction. In the epitopes prediction phase, different types of B and T-cell epitopes were predicted and only those with an antigenic, immunogenic, non-allergenic, and non-toxic profile were selected. Moreover, all the predicted epitopes were joined with each other to make a multi-epitopes vaccine construct, which was linked further to the cholera toxin B-subunit to enhance the antigenicity of the vaccine. For downward analysis, a three dimensional structure of the designed vaccine was modeled. The modeled structure was checked for binding potency with major histocompatibility complex I (MHC-I), major histocompatibility complex II (MHC-II), and Toll-like receptor 4 (TLR-4) immune cell receptors which revealed that the designed vaccine performed proper binding with respect to immune cell receptors. Additionally, the binding efficacy of the vaccine was validated through a molecular dynamic simulation that interpreted strong intermolecular vaccine-receptor binding and confirmed the exposed situation of vaccine epitopes to the host immune system. In conclusion, the study suggested that the model vaccine construct has the potency to generate protective host immune responses and that it might be a good vaccine candidate for experimental in vivo and in vitro studies.

Use of Integrated Core Proteomics, Immuno-Informatics, and In Silico Approaches to Design a Multiepitope Vaccine against Zoonotic Pathogen Edwardsiella tarda

Multidrug-resistant Edwardsiella tarda has been reported as the main causative agent for massive fish mortality. The pathogen is well-known for causing hemorrhagic septicemia in fish and has been linked to gastrointestinal infections in humans. Formalin-inactivated Edwardsiella vaccination has previously been found to be ineffective in aquaculture species. Therefore, based on E. tarda’s integrated core complete sequenced genomes, the study aimed to design a subunit vaccine based on T and B cell epitopes employing immunoinformatics approach. Initially, the top immunodominant and antigenic epitopes were predicted from the core complete sequenced genomes of the E. tarda genome and designed the vaccine by using linkers and adjuvant. In addition, vaccine 3D structure was predicted followed by refinement, and molecular docking was performed for the analysis of interacting residues between vaccines with TLR5, MHC-I, and MHC-II, respectively. The final vaccine constructs demonstrated strong hydrogen bond interactions. Molecular dynamic simulation of vaccine-TLR5 receptor complex showed a stable structural binding and compactness. Furthermore, E. coli used as a model organism for codon optimization proved optimal GC content and CAI value, which were subsequently cloned in vector pET2+ (a). Overall, the findings of the study imply that the designed epitope vaccine might be a good option for prophylaxis for E. tarda.

Designing a novel multi-epitope vaccine to evoke a robust immune response against pathogenic multidrug-resistant Enterococcus faecium bacterium

Enterococcus faecium is an emerging ESKAPE bacterium that is capable of causing severe public health complications in humans. There are currently no licensed treatments or vaccinations to combat the deadly pathogen. We aimed to design a potent and novel prophylactic chimeric vaccine against E. faecium through an immunoinformatics approach The antigenic Penicillin-binding protein 5 (PBP 5) protein was selected to identify B and T cell epitopes, followed by conservancy analysis, population coverage, physiochemical assessment, secondary and tertiary structural analysis. Using various immunoinformatics methods and tools, two linear B-cell epitopes, five CTL epitopes, and two HTL epitopes were finally selected for vaccine development. The constructed vaccine was determined to be highly immunogenic, cytokine-producing, antigenic, non-toxic, non-allergenic, and stable, as well as potentially effective against E. faecium. In addition, disulfide engineering, codon adaptation, and in silico cloning, were used to improve stability and expression efficiency in the host E. coli. Molecular docking and molecular dynamics simulations indicated that the structure of the vaccine is stable and has a high affinity for the TLR4 receptor. The immune simulation results revealed that both B and T cells had an increased response to the vaccination component. Conclusively, the in-depth in silico analysis suggests, the proposed vaccine to elicit a robust immune response against E. faecium infection and hence a promising target for further experimental trials.

Designing a novel multi‑epitope vaccine against Ebola virus using reverse vaccinology approach

Ebola virus (EBOV) is a dangerous zoonotic infectious disease. To date, more than 25 EBOV outbreaks have been documented, the majority of which have occurred in Central Africa. The rVSVG-ZEBOV-GP vaccine (ERVEBO), a live attenuated vaccine, has been approved by the US Food and Drug Administration (FDA) to combat EBOV. Because of the several drawbacks of live attenuated vaccines, multi-epitope vaccines probably appear to be safer than live attenuated vaccines. In this work, we employed immunoinformatics tools to design a multi-epitope vaccine against EBOV. We collected sequences of VP35, VP24, VP30, VP40, GP, and NP proteins from the NCBI database. T-cell and linear B-cell epitopes from target proteins were identified and tested for antigenicity, toxicity, allergenicity, and conservancy. The selected epitopes were then linked together in the vaccine's primary structure using appropriate linkers, and the 50S ribosomal L7/L12 (Locus RL7 MYCTU) sequence was added as an adjuvant to the vaccine construct's N-terminal. The physicochemical, antigenicity, and allergenicity parameters of the vaccine were all found to be satisfactory. The 3D model of the vaccine was predicted, refined, and validated. The vaccine construct had a stable and strong interaction with toll-like receptor 4 (TLR4) based on molecular docking and molecular dynamic simulation (MD) analysis. The results of codon optimization and in silico cloning revealed that the proposed vaccine was highly expressed in Escherichia coli (E. coli). The findings of this study are promising; however, experimental validations should be carried out to confirm these findings.

Design of a Recombinant Multivalent Epitope Vaccine Based on SARS-CoV-2 and Its Variants in Immunoinformatics Approaches

The development of an effective multivalent vaccine against SARS-CoV-2 variants is an important means to improve the global public health situation caused by COVID-19. In this study, we identified the antigen epitopes of the main global epidemic SARS-CoV-2 and mutated virus strains using immunoinformatics approach, and screened out 8 cytotoxic T lymphocyte epitopes (CTLEs), 17 helper T lymphocyte epitopes (HTLEs), 9 linear B-cell epitopes (LBEs) and 4 conformational B-cell epitopes (CBEs). The global population coverage of CTLEs and HTLEs was 93.16% and 99.9% respectively. These epitopes were spliced together by corresponding linkers and recombined into multivalent vaccine. In silico tests, the vaccine protein was a non-allergen and the docking with TLR-3 molecule showed a strong interaction. The results of immune simulation showed that the vaccine may be helpful to initiate both cellular and humoral immunity against all VOC. The optimistic immunogenicity of the vaccine was confirmed in vivo and in vitro finally. Therefore, our vaccine may have potential protection against SARS-CoV-2 and its variants.

Vaccinomics to Design a Multi-Epitopes Vaccine for Acinetobacter baumannii

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

Immunoinformatics and Biophysics Approaches to Design a Novel Multi-Epitopes Vaccine Design against Staphylococcus auricularis

Due to the misuse of antibiotics in our daily lives, antimicrobial resistance (AMR) has become a major health problem. Penicillin, the first antibiotic, was used in the 1930s and led to the emergence of AMR. Due to alterations in the microbe’s genome and the evolution of new resistance mechanisms, antibiotics are losing efficacy against microbes. There are high rates of mortality and morbidity due to antibiotic resistance, so addressing this major health issue requires new approaches. Staphylococcus auricularis is a Gram-positive cocci and is capable of causing opportunistic infections and sepsis. S. auricularis is resistant to several antibiotics and does not currently have a licensed vaccine. In this study, we used bacterial pan-genome analysis (BPGA) to study S. auricularis pan-genome and applied a reverse immunology approach to prioritize vaccine targets against S. auricularis. A total of 15,444 core proteins were identified by BPGA analysis, which were then used to identify good vaccine candidates considering potential vaccine filters. Two vaccine candidates were evaluated for epitope prediction including the superoxide dismutase and gamma-glutamyl transferase protein. The epitope prediction phase involved the prediction of a variety of B-Cell and T-cell epitopes, and the epitopes that met certain criteria, such as antigenicity, immunogenicity, non-allergenicity, and non-toxicity were chosen. A multi-epitopes vaccine construct was then constructed from all the predicted epitopes, and a cholera toxin B-subunit adjuvant was also added to increase vaccine antigenicity. Three-dimensional models of the vaccine were used for downward analyses. Using the best-modeled structure, binding potency was tested with MHC-I, MHC-II and TLR-4 immune cells receptors, proving that the vaccine binds strongly with the receptors. Further, molecular dynamics simulations interpreted strong intermolecular binding between the vaccine and receptors and confirmed the vaccine epitopes exposed to the host immune system. The results support that the vaccine candidate may be capable of eliciting a protective immune response against S. auricularis and may be a promising candidate for experimental in vitro and in vivo studies.

Designing a novel mRNA vaccine against Vibrio harveyi infection in fish: an immunoinformatics approach

Vibrio harveyi belongs to the family Vibrionaceae of class Gammaproteobacteria. Around 12 Vibrio species can cause gastroenteritis (gastrointestinal illness) in humans. A large number of bacterial particles can be found in the infected cells, which may cause death. Despite these devastating complications, there is still no cure or vaccine for the bacteria. As a result, we used an immunoinformatics approach to develop a multi-epitope vaccine against the most pathogenic hemolysin gene of V. harveyi. The immunodominant T- and B-cell epitopes were identified using the hemolysin protein. We developed a vaccine employing three possible epitopes: cytotoxic T-lymphocytes, helper T-lymphocytes, and linear B-lymphocyte epitopes, after thorough testing. The vaccine was developed to be antigenic, immunogenic, and non-allergenic, as well as have a better solubility. Molecular dynamics simulation revealed significant structural stiffness and binding stability. In addition, the immunological simulation generated by computers revealed that the vaccination might elicit immune reactions Escherichia coli K12 as a model, codon optimization yielded ideal GC content and a higher codon adaptation index value, which was then included in the cloning vector pET2+ (a). Altogether, our experiment implies that the proposed peptide vaccine might be a good option for vibriosis prophylaxis.

Development of multivalent vaccine targeting M segment of Crimean Congo Hemorrhagic Fever Virus (CCHFV) using immunoinformatic approaches

Crimean-Congo Hemorrhagic Fever (CCHF) is a tick-borne viral infection with no licensed vaccine or therapeutics available for its treatment. In the present study we have developed the first multi-epitope subunit vaccine effective against all the seven genotypes of CCHF virus (CCHFV). The vaccine contains five B-cell, two MHC-II (HTL), and three MHC-I (CTL) epitopes screened from two structural glycoproteins (Gc and Gn in M segment) of CCHFV with an N-terminus human β-defensin as an adjuvant, as well as an N-terminus EAAAK sequence. The epitopes were rigorously investigated for their antigenicity, allergenicity, IFN gamma induction, anti-inflammatory responses, stability, and toxicity. The three-dimensional structure of the vaccine was predicted and docked with TLR-3, TLR-8, and TLR-9 receptors to find the strength of the binding complexes via molecular dynamics simulation. After codon adaptation, the subunit vaccine construct was developed in a pDual-GC plasmid and has population coverage of 98.47% of the world's population (HLA-I & II combined). The immune simulation studies were carried out on the C-ImmSim in-silico interface showing a marked increase in the production of cellular and humoral response (B-cell and T-cell) as well as TGFβ, IL-2, IL-10, and IL-12 indicating that the proposed vaccine would be able to sufficiently provoke both humoral and cell-mediated immune responses. Thus, making it a new and promising vaccine candidate against CCHFV.

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.

Rational design of chimeric Multiepitope Based Vaccine (MEBV) against human T-cell lymphotropic virus type 1: An integrated vaccine informatics and molecular docking based approach

Human T-cell lymphotropic virus type 1 (HTLV-1) is an infectious virus that has been linked to adult T cell leukemia /lymphoma, aggressive CD4-T cell malignancy and many other immune-related medical illnesses. So far, no effective vaccine is known to combat HTLV-1, hence, the current research work was performed to design a potential multi-epitope-based subunit vaccine (MEBV) by adopting the latest methodology of reverse vaccinology. Briefly, three highly antigenic proteins (Glycoprotein, Accessory protein, and Tax protein) with no or minimal (<37%) similarity with human proteome were sorted out and potential B- and T-cell epitopes were forecasted from them. Highly antigenic, immunogenic, non-toxic, non-allergenic and overlapping epitopes were short-listed for vaccine development. The chosen T-cell epitopes displayed a strong binding affinity with their corresponding Human Leukocyte Antigen alleles and demonstrated 95.8% coverage of the world's population. Finally, nine Cytotoxic T Lymphocytes, six Helper T Lymphocytes and five Linear B Lymphocytes epitopes, joint through linkers and adjuvant, were exploited to design the final MEBV construct, comprising of 382 amino acids. The developed MEBV structure showed highly antigenic properties while being non-toxic, soluble, non-allergenic, and stable in nature. Moreover, disulphide engineering further enhanced the stability of the final vaccine protein. Additionally, Molecular docking analysis and Molecular Dynamics (MD) simulations confirmed the strong association between MEBV construct and human pathogenic immune receptor TLR-3. Repeated-exposure simulations and Immune simulations ensured the rapid antigen clearance and higher levels of cell-mediated immunity, respectively. Furthermore, MEBV codon optimization and in-silico cloning was carried out to confirm its augmented expression. Results of our experiments suggested that the proposed MEBV could be a potential immunogenic against HTLV-1; nevertheless, additional wet lab experiments are needed to elucidate our conclusion.