In silico designing of peptide based vaccine for Hepatitis viruses using reverse vaccinology approach

Computational exploration of novel antimicrobial modalities targeting fucose-binding lectins and ribosomes in Mycobacterium smegmatis using tRNA-encoded peptides

tRNA-Encoded Peptides (tREPs), encoded by small open reading frames (smORFs) within tRNA genes, have recently emerged as a new class of functional peptides exhibiting antiparasitic activity. The discovery of tREPs has led to a re-evaluation of the role of tRNAs in biology and has expanded our understanding of the genetic code. This presents an immense, unexplored potential in the realm of tRNA-peptide interactions, paving the way for groundbreaking discoveries and innovative applications in various biological functions. This study explores the antimicrobial potential of tREPs against protein targets by employing a computational method that uses verified data sources and highly recognized predictive algorithms to provide a sorted list of likely antimicrobial peptides, which were then filtered for toxicity, cell permeability, allergenicity and half-life. These peptides were then docked with screened protein targets and computationally validated using molecular dynamics (MD) simulations for 150 ns and the binding free energy was estimated. The peptides Pep2 (VVLWRKPRVRKTG) and Pep6 (HRLRLRRRKPWW) exhibited good binding affinities of -110.5 +/- 2.5 and -129.0 +/- 3.9, respectively, with RMSD values of 0.4 and 0.25 nm against the fucose-binding lectin (7NEF) and the 30S ribosome of Mycobacterium smegmatis (5O5J) protein targets. The 7NEF-Pep2 and 5O5J-Pep6 complexes indicated higher negative binding free energies of -52.55 kcal/mol and -55.52 kcal/mol respectively, as calculated by Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA). Thus, the tREPs derived peptides designed as a part of this study, provide novel approaches for potential anti-bacterial therapeutic modalities.Communicated by Ramaswamy H. Sarma.

Reverse engineering protection: A comprehensive survey of reverse vaccinology-based vaccines targeting viral pathogens

Vaccines have significantly reduced the impact of numerous deadly viral infections. However, there is an increasing need to expedite vaccine development in light of the recurrent pandemics and epidemics. Also, identifying vaccines against certain viruses is challenging due to various factors, notably the inability to culture certain viruses in cell cultures and the wide-ranging diversity of MHC profiles in humans. Fortunately, reverse vaccinology (RV) efficiently overcomes these limitations and has simplified the identification of epitopes from antigenic proteins across the entire proteome, streamlining the vaccine development process. Furthermore, it enables the creation of multiepitope vaccines that can effectively account for the variations in MHC profiles within the human population. The RV approach offers numerous advantages in developing precise and effective vaccines against viral pathogens, including extensive proteome coverage, accurate epitope identification, cross-protection capabilities, and MHC compatibility. With the introduction of RV, there is a growing emphasis among researchers on creating multiepitope-based vaccines aiming to stimulate the host's immune responses against multiple serotypes, as opposed to single-component monovalent alternatives. Regardless of how promising the RV-based vaccine candidates may appear, they must undergo experimental validation to probe their protection efficacy for real-world applications. The time, effort, and resources allocated to the laborious epitope identification process can now be redirected toward validating vaccine candidates identified through the RV approach. However, to overcome failures in the RV-based approach, efforts must be made to incorporate immunological principles and consider targeting the epitope regions involved in disease pathogenesis, immune responses, and neutralizing antibody maturation. Integrating multi-omics and incorporating artificial intelligence and machine learning-based tools and techniques in RV would increase the chances of developing an effective vaccine. This review thoroughly explains the RV approach, ideal RV-based vaccine construct components, RV-based vaccines designed to combat viral pathogens, its challenges, and future perspectives.

Reverse Vaccinology and Immunoinformatic Approach for Designing a Bivalent Vaccine Candidate Against Hepatitis A and Hepatitis B Viruses

Hepatitis A and B are two crucial viral infections that still dramatically affect public health worldwide. Hepatitis A Virus (HAV) is the main cause of acute hepatitis, whereas Hepatitis B Virus (HBV) leads to the chronic form of the disease, possibly cirrhosis or liver failure. Therefore, vaccination has always been considered the most effective preventive method against pathogens. At this moment, we aimed at the immunoinformatic analysis of HAV-Viral Protein 1 (VP1) as the major capsid protein to come up with the most conserved immunogenic truncated protein to be fused by HBV surface antigen (HBs Ag) to achieve a bivalent vaccine against HAV and HBV using an AAY linker. Various computational approaches were employed to predict highly conserved regions and the most immunogenic B-cell and T-cell epitopes of HAV-VP1 capsid protein in both humans and BALB/c. Moreover, the predicted fusion protein was analyzed regarding primary and secondary structures and also homology validation. Afterward, the three-dimensional structure of vaccine constructs docked with various toll-like receptors (TLR) 2, 4 and 7. According to the bioinformatics tools, the region of 99-259 amino acids of VP1 was selected with high immunogenicity and conserved epitopes. T-cell epitope prediction showed that this region contains 32 antigenic peptides for Human leukocyte antigen (HLA) class I and 20 antigenic peptides in terms of HLA class II which are almost fully conserved in the Iranian population. The vaccine design includes 5 linear and 4 conformational B-cell lymphocyte (BCL) epitopes to induce humoral immune responses. The designed VP1-AAY-HBsAg fusion protein has the potency to be constructed and expressed to achieve a bivalent vaccine candidate, especially in the Iranian population. These findings led us to claim that the designed vaccine candidate provides potential pathways for creating an exploratory vaccine against Hepatitis A and Hepatitis B Viruses with high confidence for the identified strains.

Mapping Potential Vaccine Candidates Predicted by VaxiJen for Different Viral Pathogens between 2017-2021-A Scoping Review

Reverse vaccinology (RV) is a promising alternative to traditional vaccinology. RV focuses on in silico methods to identify antigens or potential vaccine candidates (PVCs) from a pathogen's proteome. Researchers use VaxiJen, the most well-known RV tool, to predict PVCs for various pathogens. The purpose of this scoping review is to provide an overview of PVCs predicted by VaxiJen for different viruses between 2017 and 2021 using Arksey and O'Malley's framework and the Preferred Reporting Items for Systematic Reviews extension for Scoping Reviews (PRISMA-ScR) guidelines. We used the term 'vaxijen' to search PubMed, Scopus, Web of Science, EBSCOhost, and ProQuest One Academic. The protocol was registered at the Open Science Framework (OSF). We identified articles on this topic, charted them, and discussed the key findings. The database searches yielded 1033 articles, of which 275 were eligible. Most studies focused on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), published between 2020 and 2021. Only a few articles (8/275; 2.9%) conducted experimental validations to confirm the predictions as vaccine candidates, with 2.2% (6/275) articles mentioning recombinant protein expression. Researchers commonly targeted parts of the SARS-CoV-2 spike (S) protein, with the frequently predicted epitopes as PVCs being major histocompatibility complex (MHC) class I T cell epitopes WTAGAAAYY, RQIAPGQTG, IAIVMVTIM, and B cell epitope IAPGQTGKIADY, among others. The findings of this review are promising for the development of novel vaccines. We recommend that vaccinologists use these findings as a guide to performing experimental validation for various viruses, with SARS-CoV-2 as a priority, because better vaccines are needed, especially to stay ahead of the emergence of new variants. If successful, these vaccines could provide broader protection than traditional vaccines.

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

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

A Systematic Immuno-Informatic Approach to Design a Multiepitope-Based Vaccine Against Emerging Multiple Drug Resistant Serratia marcescens

Serratia marcescens is now an important opportunistic pathogen that can cause serious infections in hospitalized or immunocompromised patients. Here, we used extensive bioinformatic analyses based on reverse vaccinology and subtractive proteomics-based approach to predict potential vaccine candidates against S. marcescens. We analyzed the complete proteome sequence of 49 isolate of Serratia marcescens and identified 5 that were conserved proteins, non-homologous from human and gut flora, extracellular or exported to the outer membrane, and antigenic. The identified proteins were used to select 5 CTL, 12 HTL, and 12 BCL epitopes antigenic, non-allergenic, conserved, hydrophilic, and non-toxic. In addition, HTL epitopes were able to induce interferon-gamma immune response. The selected peptides were used to design 4 multi-epitope vaccines constructs (SMV1, SMV2, SMV3 and SMV4) with immune-modulating adjuvants, PADRE sequence, and linkers. Peptide cleavage analysis showed that antigen vaccines are processed and presented via of MHC class molecule. Several physiochemical and immunological analyses revealed that all multiepitope vaccines were non-allergenic, stable, hydrophilic, and soluble and induced the immunity with high antigenicity. The secondary structure analysis revealed the designed vaccines contain mainly coil structure and alpha helix structures. 3D analyses showed high-quality structure. Molecular docking analyses revealed SMV4 as the best vaccine construct among the four constructed vaccines, demonstrating high affinity with the immune receptor. Molecular dynamics simulation confirmed the low deformability and stability of the vaccine candidate. Discontinuous epitope residues analyses of SMV4 revealed that they are flexible and can interact with antibodies. In silico immune simulation indicated that the designed SMV4 vaccine triggers an effective immune response. In silico codon optimization and cloning in expression vector indicate that SMV4 vaccine can be efficiently expressed in E. coli system. Overall, we showed that SMV4 multi-epitope vaccine successfully elicited antigen-specific humoral and cellular immune responses and may be a potential vaccine candidate against S. marcescens. Further experimental validations could confirm its exact efficacy, the safety and immunogenicity profile. Our findings bring a valuable addition to the development of new strategies to prevent and control the spread of multidrug-resistant Gram-negative bacteria with high clinical relevance.

In-silico designing of epitope-based vaccine against the seven banded grouper nervous necrosis virus affecting fish species

Neural necrosis virus (NNV) of family Nodaviridae affect wide range of fish species with viral encephalopathy and retinopathy causing mass mortality up to 100%. Currently there is no effective treatment and depopulation is only suggested recommendation. New avenues and approach are required to control this harmful malady. In this study we developed an epitope-based vaccine (EBV), against NNV using computation approach. We have selected two conserved proteins RNA-dependent RNA polymerase (RdRP) and capsid proteins. Based on more than ~ 1000 epitopes we selected six antigenic epitopes. These were conjugated to adjuvant and linker peptides to generate a full-length vaccine candidate. Biochemical structural properties were analyzed by Phyre2 server. ProtParam, Molprobity. Ramachandran plot results indicate that 98.7% residues are in a favorable region and 93.4% residues in the favored region. The engineered EBV binds to toll like receptor-5 (TLR5) an important elicitor of immune response. Further molecular docking by PatchDock server reveals the atomic contact energy (i.e. − 267.08) for the best docked model of EBV and TLR5 receptor. The molecular simulation results suggest a stable interaction; the RMSD and RMSF values are 1–4 Ǻ and 1–12Ǻ, respectively. Further we have suggested the best possible codon optimized sequence for its cloning and subsequent purification of the protein. Overall, this is a first report to suggest an in-silico method for generation of an EBV candidate against NNV. We surmise that the method and approach suggested could be used as a promising cure for NNVs.

A computational study to disclose potential drugs and vaccine ensemble for COVID-19 conundrum

The nucleocapsid (N) protein of SARS-COV-2, a virus responsible for the current COVID-19 pandemic, is considered a potential candidate for the design of new drugs and vaccines. The protein is central to several critical events in virus production, with its highly druggable nature and rich antigenic determinants making it an excellent anti-viral biomolecule. Docking-based virtual screening using the Asinex anti-viral library identified binding of drug molecules at three specific positions: loop 1 region, loop 2 region and β-sheet core pockets, the loop 2 region being the most common binding and stable site for the bulk of the molecules. In parallel, the protein was characterized by vaccine design perspective and harboured three potential B cell-derived T cell epitopes: PINTNSSPD, GVPINTNSS, and DHIGTRNPA. The epitopes are highly antigenic, virulent, non-allergic, non-toxic, bind with good affinity to the highly prevalent DRB*0101 allele and show an average population coverage of 95.04%. A multi-epitope vaccine ensemble which was 83 amino acids long was created. This was highly immunogenic, robust in generating both humoral and cellular immune responses, thermally stable, and had good physicochemical properties that could be easily analyzed in in vivo and in vitro studies. Conformational dynamics of both drug and vaccine ensemble with respect to the receptors are energetically stable, shedding light on favourable conformation and chemical interactions. These facts were validated by subjecting the complexes to relative and absolute binding free energy methods of MMGB/PBSA and WaterSwap. A strong agreement on the system stability was disclosed that supported ligand high affinity potential for the receptors. Collectively, this work sought to provide preliminary experimental data of existing anti-viral drugs as a possible therapy for COVID-19 infections and a new peptide-based vaccine for protection against this pandemic virus.

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

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