Designing a multi-epitopic vaccine against the enterotoxigenic Bacteroides fragilis based on immunoinformatics approach

Natural products can be potential inhibitors of metalloproteinase II from Bacteroides fragilis to intervene colorectal cancer

Bacteroides fragilis, a gram negative and obligate anaerobe bacterium, is a member of normal gut microbiota and facilitates many essential roles being performed in human body in normal circumstances specifically in Gastrointestinal or GI tract. Sometimes, due to genetics, epigenetics, and environmental factors, Bacteroides fragilis and their protein(s) start interacting with intestinal epithelium thus damaging the lining leading to colorectal cancers (CRC). To identify these protein(s), we incorporated a novel subtractive proteomics approach in the study. Metalloproteinase II (MPII), a Bacteroides fragilis toxin (bft), was investigated for its virulence and unique pathways to demonstrate its specificity and uniqueness in pathogenicity followed by molecular docking against a set of small drug-like natural molecules to discover potential inhibitors against the toxin. All these identified inhibitor-like molecules were analyzed for their ADMET calculations and detailed physiochemical properties to predict their druggability, GI absorption, blood brain barrier and skin permeation, and others. Resultantly, a total of ten compounds with the least binding energies were obtained and were subjected to protein-compound interaction analysis. Interaction analysis revealed the most common ligand-interacting residues in MPII are His 345, Glu 346, His 339, Gly 310, Tyr 341, Pro 340, Asp 187, Phe 309, Lys 307, Ile 185, Thr 308, and Pro 184. Therefore, top three compounds complexed with MPII having best binding energies were selected in order to analyze their trajectories. RMSD, RMSF, Rg and MMPBSA analysis revealed that all compounds showed good binding and keeping the complex stable and compact throughout the simulation time in addition to all properties and qualities of being a potential inhibitor against MPII.

In silico design of a novel multi-epitope vaccine against HCV infection through immunoinformatics approaches

Infection with the hepatitis C virus (HCV) is one of the causes of liver cancer, which is the world's sixth most prevalent and third most lethal cancer. The current treatments do not prevent reinfection; because they are expensive, their usage is limited to developed nations. Therefore, a prophylactic vaccine is essential to control this virus. Hence, in this study, an immunoinformatics method was applied to design a multi-epitope vaccine against HCV. The best B- and T-cell epitopes from conserved regions of the E2 protein of seven HCV genotypes were joined with the appropriate linkers to design a multi-epitope vaccine. In addition, cholera enterotoxin subunit B (CtxB) was included as an adjuvant in the vaccine construct. This study is the first to present this epitopes-adjuvant combination. The vaccine had acceptable physicochemical characteristics. The vaccine's 3D structure was predicted and validated. The vaccine's binding stability with Toll-like receptor 2 (TLR2) and TLR4 was confirmed using molecular docking and molecular dynamics (MD) simulation. The immune simulation revealed the vaccine's efficacy by increasing the population of B and T cells in response to vaccination. In silico expression in Escherichia coli (E. coli) was also successful.

Development of membrane protein-based vaccine against lumpy skin disease virus (LSDV) using immunoinformatic tools

INTRODUCTION

Lumpy skin disease, an economically significant bovine illness, is now found in previously unheard-of geographic regions. Vaccination is one of the most important ways to stop its further spread.

AIM

Therefore, in this study, we applied advanced immunoinformatics approaches to design and develop an effective lumpy skin disease virus (LSDV) vaccine.

METHODS

The membrane glycoprotein was selected for prediction of the different B- and T-cell epitopes by using the immune epitope database. The selected B- and T-cell epitopes were combined with the appropriate linkers and adjuvant resulted in a vaccine chimera construct. Bioinformatics tools were used to predict, refine and validate the 2D, 3D structures and for molecular docking with toll-like receptor 4 using different servers. The constructed vaccine candidate was further processed on the basis of antigenicity, allergenicity, solubility, different physiochemical properties and molecular docking scores.

RESULTS

The in silico immune simulation induced significant response for immune cells. In silico cloning and codon optimization were performed to express the vaccine candidate in Escherichia coli. This study highlights a good signal for the design of a peptide-based LSDV vaccine.

CONCLUSION

Thus, the present findings may indicate that the engineered multi-epitope vaccine is structurally stable and can induce a strong immune response, which should help in developing an effective vaccine towards controlling LSDV infection.

Multi-epitope vaccine design for hepatitis E virus based on protein ORF2 and ORF3

Introduction

Hepatitis E virus (HEV), with heightened virulence in immunocompromised individuals and pregnant women, is a pervasive threat in developing countries. A globaly available vaccine against HEV is currently lacking.

Methods

We designed a multi-epitope vaccine based on protein ORF2 and ORF3 of HEV using immunoinformatics.

Results

The vaccine comprised 23 nontoxic, nonallergenic, soluble peptides. The stability of the docked peptide vaccine-TLR3 complex was validated by molecular dynamic simulations. The induction of effective cellular and humoral immune responses by the multi-peptide vaccine was verified by simulated immunization.

Discussion

These findings provide a foundation for future HEV vaccine studies.

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.

Computational identification of a multi-peptide vaccine candidate in E2 glycoprotein against diverse Hepatitis C virus genotypes

Hepatitis C Virus (HCV) is estimated to affect nearly 180 million people worldwide, culminating in ∼0.7 million yearly casualties. However, a safe vaccine against HCV is not yet available. This study endeavored to identify a multi-genotypic, multi-epitopic, safe, and globally competent HCV vaccine candidate. We employed a consensus epitope prediction strategy to identify multi-epitopic peptides in all known envelope glycoprotein (E2) sequences, belonging to diverse HCV genotypes. The obtained peptides were screened for toxicity, allergenicity, autoimmunity and antigenicity, resulting in two favorable peptides viz., P2 (VYCFTPSPVVVG) and P3 (YRLWHYPCTV). Evolutionary conservation analysis indicated that P2 and P3 are highly conserved, supporting their use as part of a designed multi-genotypic vaccine. Population coverage analysis revealed that P2 and P3 are likely to be presented by >89% Human Leukocyte Antigen (HLA) molecules from six geographical regions. Indeed, molecular docking predicted the physical binding of P2 and P3 to various representative HLAs. We designed a vaccine construct using these peptides and assessed its binding to toll-like receptor 4 (TLR-4) by molecular docking and simulation. Subsequent analysis by energy-based and machine learning tools predicted high binding affinity and pinpointed the key binding residues (i.e. hotspots) in P2 and P3. Also, a favorable immunogenic profile of the construct was predicted by immune simulations. We encourage the scientific community to validate our vaccine construct in vitro and in vivo.Communicated by Ramaswamy H. Sarma.

Computational prediction of B and T-cell epitopes of Kyasanur Forest Disease virus marker proteins towards the development of precise diagnosis and potent subunit vaccine

Kyasanur Forest Disease (KFD), also known as 'monkey fever', caused by KFD Virus (KFDV), is a highly neglected tropical disease endemic to Western Ghat region of Karnataka, India. Recently, KFD, which is fatal for both monkeys and humans with a mortality rate of 2-10% has been found to spread from its epicenter to neighboring districts and states also. The current ELISA based KFD detection method is very non-specific due to cross-reactivity with other flaviviruses. Further, presently available formalin-inactivated vaccine has been found to be less effective leading to disease susceptibility and severity. To address these, the present study was aimed at predicting the potent specific B and T-cell epitopes of KFDV immunogenic marker proteins using diverse computational tools aiming at developing precise diagnostic method and an effective subunit vaccine. Here, we have chosen E, NS1 and NS5 proteins as markers of KFDV by taking into account of their differential and non-overlapping sequences with selected arboviruses. Based on the linear and nonlinear epitope prediction tools and important biophysical parameters, we identified three potential linear and ten nonlinear B-cell epitopes. We also predicted T-cell epitope peptides which binds to MHC class-I and class-II receptors for the effective T-cell activation. Thus, our molecular docking and molecular dynamics simulation analysis has identified six different TH-cell epitopes based on the distribution frequency of MHC-II haplotypes in the human population and one TC-cell epitope from NS5 protein that has maximum interaction with class-I MHC. Overall, we have successfully identified potential B and T-cell epitope marker peptides present in the envelope and two non-structural proteins.Communicated by Ramaswamy H. Sarma.

Multiplex Cas9-based excision of CLCuV betasatellite and DNA-A revealed reduction of viral load with asymptomatic cotton plants

MAIN CONCLUSION

Multiplexed Cas9-based genome editing of cotton resulted in reduction of viral load with asymptomatic cotton plants. In depth imaging of proteomic dynamics of resulting CLCuV betasatellite and DNA-A protein was also performed. The notorious  cotton leaf curl virus (CLCuV), which is transmitted by the sap-sucking insect whitefly, continuously damages cotton crops. Although the application of various toxins and RNAi has shown some promise, sustained control has not been achieved. Consequently, CRISPR_Cas9 was applied by designing multiplex targets against DNA-A (AC2 and AC3) and betasatellite (βC1) of CLCuV using CRISPR direct and ligating into the destination vector of the plant using gateway ligation method. The successful ligation of targets into the destination vector was confirmed by the amplification of 1049 bp using a primer created from the promoter and target, while restriction digestion using the AflII and Asc1 enzymes determined how compact the plasmid developed and the nucleotide specificity of the plasmid was achieved through Sanger sequencing. PCR confirmed the successful introduction of plasmid into CKC-1 cotton variety. Through Sanger sequencing and correlation with the mRNA expression of DNA-A and betasatellite in genome-edited cotton plants subjected to agroinfiltration of CLCuV infectious clone, the effectiveness of knockout was established. The genome-edited cotton plants demonstrated edited efficacy of 72% for AC2 and AC3 and 90% for the (βC1) through amplicon sequencing, Molecular dynamics (MD) simulations were used to further validate the results. Higher RMSD values for the edited βC1 and AC3 proteins indicated functional loss caused by denaturation. Thus, CRISPR_Cas9 constructs can be rationally designed using high-throughput MD simulation technique. The confidence in using this technology to control plant virus and its vector was determined by the knockout efficiency and the virus inoculation assay.

Designing multi-epitope vaccine against important colorectal cancer (CRC) associated pathogens based on immunoinformatics approach

BACKGROUND

It seems that several members of intestinal gut microbiota like Streptococcus bovis, Bacteroides fragilis, Helicobacter pylori, Fusobacterium nucleatum, Enterococcus faecalis, Escherichia coli, Peptostreptococcus anaerobius may be considered as the causative agents of Colorectal Cancer (CRC). The present study used bioinformatics and immunoinformatics approaches to design a potential epitope-based multi-epitope vaccine to prevent CRC with optimal population coverage.

METHODS

In this study, ten amino acid sequences of CRC-related pathogens were retrieved from the NCBI database. Three ABCpred, BCPREDS and LBtope online servers were considered for B cells prediction and the IEDB server for T cells (CD4⁺ and CD8⁺) prediction. Then, validation, allergenicity, toxicity and physicochemical analysis of all sequences were performed using web servers. A total of three linkers, AAY, GPGPG, and KK were used to bind CTL, HTL and BCL epitopes, respectively. In addition, the final construct was subjected to disulfide engineering, molecular docking, immune simulation and codon adaptation to design an effective vaccine production strategy.

RESULTS

A total of 19 sequences of different lengths for linear B-cell epitopes, 19 and 18 sequences were considered as epitopes of CD4⁺ T and CD8⁺ cells, respectively. The predicted epitopes were joined by appropriate linkers because they play an important role in producing an extended conformation and protein folding. The final multi-epitope construct and Toll-like receptor 4 (TLR4) were evaluated by molecular docking, which revealed stable and strong binding interactions. Immunity simulation of the vaccine showed significantly high levels of immunoglobulins, helper T cells, cytotoxic T cells and INF-γ.

CONCLUSION

Finally, the results showed that the designed multi-epitope vaccine could serve as an excellent prophylactic candidate against CRC-associated pathogens, but in vitro and animal studies are needed to justify our findings for its use as a possible preventive measure.

Oncomicrobial vaccines: The potential for a Fusobacterium nucleatum vaccine to improve colorectal cancer outcomes

There is increasing awareness of the many different ways host-microbe interactions relate to cancer initiation and progression. Vaccines designed to drive immune responses against key tumor-promoting mechanisms of oncomicrobes like F. nucleatum may provide novel and effective interventions against colorectal cancer and other diseases.

Computer-aided genomic data analysis of drug-resistant Neisseria gonorrhoeae for the Identification of alternative therapeutic targets

Neisseria gonorrhoeae is an emerging multidrug resistance pathogen that causes sexually transmitted infections in men and women. The N. gonorrhoeae has demonstrated an emerging antimicrobial resistance against reported antibiotics, hence fetching the attention of researchers to address this problem. The present in-silico study aimed to find putative novel drug and vaccine targets against N. gonorrhoeae infection by the application of bioinformatics approaches. Core genes set of 69 N. gonorrhoeae strains was acquired from complete genome sequences. The essential and non-homologous metabolic pathway proteins of N. gonorrhoeae were identified. Moreover, different bioinformatics databases were used for the downstream analysis. The DrugBank database scanning identified 12 novel drug targets in the prioritized list. They were preferred as drug targets against this bacterium. A viable vaccine is unavailable so far against N. gonorrhoeae infection. In the current study, two outer-membrane proteins were prioritized as vaccine candidates via reverse vaccinology approach. The top lead B and T-cells overlapped epitopes were utilized to generate a chimeric vaccine construct combined with immune-modulating adjuvants, linkers, and PADRE sequences. The top ranked prioritized vaccine construct (V7) showed stable molecular interaction with human immune cell receptors as inferred during the molecular docking and MD simulation analyses. Considerable response for immune cells was interpreted by in-silico immune studies. Additional tentative validation is required to ensure the effectiveness of the prioritized vaccine construct against N. gonorrhoeae infection. The identified proteins can be used for further rational drug and vaccine designing to develop potential therapeutic entities against the multi-drug resistant N. gonorrhoeae.

Design of a multi-epitope vaccine against Haemophilus parasuis based on pan-genome and immunoinformatics approaches

Background

Glässer's disease, caused by Haemophilus parasuis (HPS), is responsible for economic losses in the pig industry worldwide. However, the existing commercial vaccines offer poor protection and there are significant barriers to the development of effective vaccines.

Methods

In the current study, we aimed to identify potential vaccine candidates and design a multi-epitope vaccine against HPS by performing pan-genomic analysis of 121 strains and using a reverse vaccinology approach.

Results

The designed vaccine constructs consist of predicted epitopes of B and T cells derived from the outer membrane proteins of the HPS core genome. The vaccine was found to be highly immunogenic, non-toxic, and non-allergenic as well as have stable physicochemical properties. It has a high binding affinity to Toll-like receptor 2. In addition, in silico immune simulation results showed that the vaccine elicited an effective immune response. Moreover, the mouse polyclonal antibody obtained by immunizing the vaccine protein can be combined with different serotypes and non-typable Haemophilus parasuis in vitro.

Conclusion

The overall results of the study suggest that the designed multi-epitope vaccine is a promising candidate for pan-prophylaxis against different strains of HPS.

Repositioning small molecule drugs as allosteric inhibitors of the BFT-3 toxin from enterotoxigenic Bacteroides fragilis

Bacteroides fragilis is an abundant commensal component of the healthy human colon. However, under dysbiotic conditions, enterotoxigenic B. fragilis (ETBF) may arise and elicit diarrhea, anaerobic bacteremia, inflammatory bowel disease, and colorectal cancer. Most worrisome, ETBF is resistant to many disparate antibiotics. ETBF's only recognized specific virulence factor is a zinc-dependent metallopeptidase (MP) called B. fragilis toxin (BFT) or fragilysin, which damages the intestinal mucosa and triggers disease-related signaling mechanisms. Thus, therapeutic targeting of BFT is expected to limit ETBF pathogenicity and improve the prognosis for patients. We focused on one of the naturally occurring BFT isoforms, BFT-3, and managed to repurpose several approved drugs as BFT-3 inhibitors through a combination of biophysical, biochemical, structural, and cellular techniques. In contrast to canonical MP inhibitors, which target the active site of mature enzymes, these effectors bind to a distal allosteric site in the proBFT-3 zymogen structure, which stabilizes a partially unstructured, zinc-free enzyme conformation by shifting a zinc-dependent disorder-to-order equilibrium. This yields proBTF-3 incompetent for autoactivation, thus ablating hydrolytic activity of the mature toxin. Additionally, a similar destabilizing effect is observed for the activated protease according to biophysical and biochemical data. Our strategy paves a novel way for the development of highly specific inhibitors of ETBF-mediated enteropathogenic conditions.

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.

Computational construction of a glycoprotein multi-epitope subunit vaccine candidate for old and new South-African SARS-CoV-2 virus strains

The discovery of a new SARS-CoV-2 virus strain in South Africa presents a major public health threat, therefore contributing to increased infections and transmission rates during the second wave of the global pandemic. This study lays the groundwork for the development of a novel subunit vaccine candidate from the circulating strains of South African SARS-CoV-2 and provides an understanding of the molecular epidemiological trend of the circulating strains. A total of 475 whole-genome nucleotide sequences from South Africa submitted between December 1, 2020 and February 15, 2021 available at the GISAID database were retrieved based on its size, coverage level and hosts. To obtain the distribution of the clades and lineages of South African SARS-CoV-2 circulating strains, the metadata of the sequence retrieved were subjected to an epidemiological analysis. There was a prediction of the cytotoxic T lymphocytes (CTL), Helper T cells (HTL) and B-cell epitopes. Furthermore, there was allergenicity, antigenicity and toxicity predictions on the epitopes. The analysis of the physicochemical properties of the vaccine construct was performed; the secondary structure, tertiary structure and B-cell 3D conformational structure of the vaccine construct were predicted. Also, molecular binding simulations and dynamics simulations were adopted in the prediction of the vaccine construct's stability and binding affinity with TLRs. Result obtained from the metadata analysis indicated lineage B.1.351 to be in higher circulation among various circulating strains of SARS-CoV-2 in South Africa and GH has the highest number of circulating clades. The construct of the novel vaccine was antigenic, non-allergenic and non-toxic. The Instability index (II) score and aliphatic index were estimated as 41.74 and 78.72 respectively. The computed half-life in mammalian reticulocytes was 4.4 h in vitro, for yeast and in E. coli was >20 h and >10 h in vivo respectively. The grand average of hydropathicity (GRAVY) score is estimated to be -0.129, signifying the hydrophilic nature of the protein. The molecular docking indicates that the vaccine construct has a high binding affinity towards the TLRs with TLR 3 having the highest binding energy (-1203.2 kcal/mol) and TLR 9 with the lowest (-1559.5 kcal/mol). These results show that the vaccine construct is promising and should be evaluated using animal model.

In silico Design and Characterization of Multi-epitopes Vaccine for SARS-CoV2 from Its Spike Protein

COVID 19 is a disease caused by a novel coronavirus, SARS-CoV2 originated in China most probably of Bat origin. Multiepitopes vaccine would be useful in eliminating SARS-CoV2 infections as asymptomatic patients are in large numbers. In response to this, we utilized bioinformatic tools to develop an efficient vaccine candidate against SARS-CoV2. The designed vaccine has effective BCR and TCR epitopes screened from the sequence of S-protein of SARS-CoV2. Predicted BCR and TCR epitopes found antigenic, non-toxic and probably non-allergen. Modeled and the refined tertiary structure predicted as valid for further use. Protein–Protein interaction prediction of TLR2/4 and designed vaccine indicates promising binding. The designed multiepitope vaccine has induced cell-mediated and humoral immunity along with increased interferon-gamma response. Macrophages and dendritic cells were also found to increase upon the vaccine exposure. In silico codon optimization and cloning in expression vector indicates that the vaccine can be efficiently expressed in E. coli. In conclusion, the predicted vaccine is a good antigen, probable no allergen, and has the potential to induce cellular and humoral immunity.

Engineering a multi-epitope vaccine candidate against Leishmania infantum using comprehensive Immunoinformatics methods

Visceral leishmaniasis (VL) is a severe disease with particular endemicity in over 80 countries worldwide. There is no approved human vaccine against VL in the market. This study was aimed at designing and evaluation of a multimeric vaccine candidate against Leishmania infantum through utilization of helper T lymphocyte (HTL) and cytotoxic T lymphocyte (CTL) immunodominant proteins from histone H1, KMP11, LACK and LeIF antigens. Top-ranked mouse MHC-I, MHC-II binders and CTL epitopes were predicted and joined together via spacers. Also, a TLR-4 agonist (RS-09 synthetic protein) and His-tag were added to the N- and C-terminal of the vaccine sequence, respectively. The final chimeric vaccine had a length of 184 amino acids with a molecular weight of 18.99 kDa. Physico-chemical features showed a soluble, highly-antigenic and non-allergenic candidate. Secondary and tertiary structures were predicted, and subsequent analyses confirmed the construct stability that was capable to properly interact with TLR-4/MD2 receptor. Immunoinformatics simulation displayed potent stimulation of T cell immune responses, with particular rise in IFN-γ, upon vaccination with the proposed multi-epitope candidate. In conclusion, immunoinformatics data demonstrated a highly antigenic vaccine candidate in mouse, which could develop considerable levels clearance mechanisms and other components of cellular immune profile, and can be directed for VL prophylactic purposes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11756-021-00934-3.

Toxoplasma gondii Tyrosine-Rich Oocyst Wall Protein: A Closer Look through an In Silico Prism

Toxoplasmosis is a global threat with significant zoonotic concern. The present in silico study was aimed at determination of bioinformatics features and immunogenic epitopes of a tyrosine-rich oocyst wall protein (TrOWP) of Toxoplasma gondii. After retrieving the amino acid sequence from UniProt database, several parameters were predicted including antigenicity, allergenicity, solubility and physico-chemical features, signal peptide, transmembrane domain, and posttranslational modifications. Following secondary and tertiary structure prediction, the 3D model was refined, and immunogenic epitopes were forecasted. It was a 25.57 kDa hydrophilic molecule with 236 residues, a signal peptide, and significant antigenicity scores. Moreover, several linear and conformational B-cell epitopes were present. Also, potential mouse and human cytotoxic T-lymphocyte (CTL) and helper T-lymphocyte (HTL) epitopes were predicted in the sequence. The findings of the present in silico study are promising as they render beneficial characteristics of TrOWP to be included in future vaccination experiments.

Introduction of novel putative immunogenic targets against Proteus mirabilis using a reverse vaccinology approach

Multi-drug resistance of Proteus mirabilis, a frequent cause of catheter-associated urinary tract infections, renders ineffective treatment. Therefore, new advanced strategies are needed to overcome it. In the meantime, vaccination may be the most effective and promising method. In this study antigenicity, allergenicity, subcellular localization, human homology, B-cell epitopes and MHC-II binding sites, conserved domains and protein-protein interactions were predicted using different reverse vaccinology methods and bioinformatics databases to find new putative immunogenic targets against P. mirabilis. Finally, 5 putative immunogenic targets against P. mirabilis were identified. Considering all criteria, QKQ94350.1 (Cell envelope opacity-associated protein A), QKQ94681.1 (Porin), QKQ95001.1 (TonB-dependent hemoglobin/ transferrin/ lactoferrin family receptor), QKQ95221.1 (AsmA) and QKQ94335.1 (N-acetylmuramoyl-L-alanine amidase) are excellent putative immunogenic targets. Finally, a multi-epitope vaccine was designed using the conserved linear epitopes of two OMPs (QKQ94681.1 and QKQ95001.1) and N-acetylmuramoyl-L-alanine amidase (QKQ94335.1), which have promising properties for immunization. These findings can simplify the development of efficient vaccines against P. mirabilis.

Insights into the biochemical features and immunogenic epitopes of common bradyzoite markers of the ubiquitous Toxoplasma gondii

The widespread distribution of Toxoplasma gondii (T. gondii) infection and its harsh outcomes in pregnant women and immunocompromised patients lead researchers towards vaccination strategies. The present in silico investigation was done to reveal biophysical properties and immunogenic epitopes of six bradyzoite markers for rational vaccine design in future. For this purpose, different web servers were used to predict antigenicity, allergenicity, solubility, physicochemical properties, post-translational modification sites (PTMs), the presence of signal peptide and transmembrane domains. Moreover, the secondary and tertiary structures of the proteins were revealed followed by refinement and validation. Finally, NetCTL server was used to predict cytotoxic T-lymphocyte (CTL) epitopes, with subsequent immunogenicity analysis. Also, IEDB server was utilized to predict helper T-lymphocyte (HTL) epitopes, followed by IFN-γ and IL-4 induction, antigenicity and population coverage analysis. As well, several linear antigenic B-cell epitopes were found, with good water solubility and without allergenicity. Totally, these proteins showed appropriate antigenicity, abundant PTMs as well as many CTL, HTL and B-cell epitopes, which could be directed for future vaccination studies in the context of multi-epitope vaccine design.

Quest for Novel Preventive and Therapeutic Options Against Multidrug-Resistant Pseudomonas aeruginosa

Pseudomonas aeruginosa (P. aeruginosa) is a critical healthcare challenge due to its ability to cause persistent infections and the acquisition of antibiotic resistance mechanisms. Lack of preventive vaccines and rampant drug resistance phenomenon has rendered patients vulnerable. As new antimicrobials are in the preclinical stages of development, mining for the unexploited drug targets is also crucial. In the present study, we designed a B- and T-cell multi-epitope vaccine against P. aeruginosa using a subtractive proteomics and immunoinformatics approach. A total of five proteins were shortlisted based on essentiality, extracellular localization, virulence, antigenicity, pathway association, hydrophilicity, and low molecular weight. These include two outer membrane porins; OprF (P13794) and OprD (P32722), a protein activator precursor pra (G3XDA9), a probable outer membrane protein precursor PA1288 (Q9I456), and a conserved hypothetical protein PA4874 (Q9HUT9). These shortlisted proteins were further analyzed to identify immunogenic and antigenic B- and T-cell epitopes. The best scoring epitopes were then further subjected to the construction of a polypeptide multi-epitope vaccine and joined with cholera toxin B subunit adjuvant. The final chimeric construct was docked with TLR4 and confirmed by normal mode simulation studies. The designed B- and T-cell multi-epitope vaccine candidate is predicted immunogenic in nature and has shown strong interactions with TLR-4. Immune simulation predicted high-level production of B- and T-cell population and maximal expression was ensured in E. coli strain K12. The identified drug targets qualifying the screening criteria were: UDP-2-acetamido-2-deoxy-d-glucuronic acid 3-dehydrogenase WbpB (G3XD23), aspartate semialdehyde dehydrogenase (Q51344), 2-amino-4-hydroxy-6-hydroxymethyldihydropteridine pyrophosphokinase (Q9HV71), 3-deoxy-D-manno-octulosonic-acid transferase (Q9HUH7), glycyl-tRNA synthetase alpha chain (Q9I7B7), riboflavin kinase/FAD synthase (Q9HVM3), aconitate hydratase 2 (Q9I2V5), probable glycosyltransferase WbpH (G3XD85) and UDP-3-O-[3-hydroxylauroyl] glucosamine N-acyltransferase (Q9HXY6). For druggability and pocketome analysis crystal and homology structures of these proteins were retrieved and developed. A sequence-based search was performed in different databases (ChEMBL, Drug Bank, PubChem and Pseudomonas database) for the availability of reported ligands and tested drugs for the screened targets. These predicted targets may provide a basis for the development of reliable antibacterial preventive and therapeutic options against P. aeruginosa.

Design of a novel multiple epitope-based vaccine: An immunoinformatics approach to combat SARS-CoV-2 strains

BACKGROUND

Since the SARS-CoV-2 outbreak in December 2019 in Wuhan, China, the virus has infected more than 153 million individuals across the world due to its human-to-human transmission. The USA is the most affected country having more than 32-million cases till date. Sudden high fever, pneumonia and organ failure have been observed in infected individuals.

OBJECTIVES

In the current situation of emerging viral disease, there is no specific vaccine, or any therapeutics available for SARS-CoV-2, thus there is a dire need to design a potential vaccine to combat the virus by developing immunity in the population. The purpose of present study was to develop a potential vaccine by targeting B and T-cell epitopes using bioinformatics approaches.

METHODS

B- and T-cell epitopes are predicted from novel M protein-SARS-CoV-2 for the development of a unique multiple epitope vaccine by applying bioinformatics approaches. These epitopes were analyzed and selected for their immunogenicity, antigenicity scores, and toxicity in correspondence to their ability to trigger immune response. In combination to epitopes, best multi-epitope of potential immunogenic property was constructed. The epitopes were joined using EAAAK, AAY and GPGPG linkers.

RESULTS

The constructed vaccine showed good results of worldwide population coverage and promising immune response. This constructed vaccine was subjected to in-silico immune simulations by C-ImmSim. Chimeric protein construct was cloned into PET28a (+) vector for expression study in Escherichia coli using snapgene.

CONCLUSION

This vaccine design proved effective in various computer-based immune response analysis as well as showed good population coverage. This study is solely dependent on developing M protein-based vaccine, and these in silico findings would be a breakthrough in the development of an effective vaccine to eradicate SARS-CoV-2 globally.

In silico analysis and prediction of immunogenic epitopes for pre-erythrocytic proteins of the deadly Plasmodium falciparum

Malaria is the deadliest parasitic disease in tropical and subtropical areas around the world, with considerable morbidity and mortality, particularly due to the life-threatening Plasmodium falciparum. The present in silico investigation was performed to reveal the biophysical characteristics and immunogenic epitopes of the six pre-erythrocytic proteins of the P. falciparum using comprehensive immunoinformatics approaches. For this aim, different web servers were employed to predict subcellular localization, antigenicity, allergenicity, solubility, physico-chemical properties, post-translational modification sites (PTMs), the presence of signal peptide and transmembrane domains. Moreover, the secondary and tertiary structures of the proteins were revealed followed by refinement and validations. Finally, NetCTL server was used to predict cytotoxic T-lymphocyte (CTL) epitopes, followed by subsequent screening in terms of antigenicity and immunogenicity. Also, IEDB server was utilized to predict helper T-lymphocyte (HTL) epitopes, followed by screening regarding interferon gamma induction and population coverage. These proteins showed appropriate antigenicity, abundant PTMs as well as many CTL and HTL epitopes, which could be directed for future vaccination studies in the context of multi-epitope vaccine design.

In Silico Prediction of a Multitope Vaccine against Moraxella catarrhalis: Reverse Vaccinology and Immunoinformatics

Moraxella catarrhalis (M. catarrhalis) is a Gram-negative bacterium that can cause serious respiratory tract infections and middle ear infections in children and adults. M. catarrhalis has demonstrated an increasing rate of antibiotic resistance in the last few years, thus development of an effective vaccine is a major health priority. We report here a novel designed multitope vaccine based on the mapped epitopes of the vaccine candidates filtered out of the whole proteome of M. catarrhalis. After analysis of 1615 proteins using a reverse vaccinology approach, only two proteins (outer membrane protein assembly factor BamA and LPS assembly protein LptD) were nominated as potential vaccine candidates. These proteins were found to be essential, outer membrane, virulent and non-human homologs with appropriate molecular weight and high antigenicity score. For each protein, cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL) and B cell lymphocyte (BCL) epitopes were predicted and confirmed to be highly antigenic and cover conserved regions of the proteins. The mapped epitopes constituted the base of the designed multitope vaccine where suitable linkers were added to conjugate them. Additionally, beta defensin adjuvant and pan-HLA DR-binding epitope (PADRE) peptide were also incorporated into the construct to improve the stimulated immune response. The constructed multitope vaccine was analyzed for its physicochemical, structural and immunological characteristics and it was found to be antigenic, soluble, stable, non-allergenic and have a high affinity to its target receptor. Although the in silico analysis of the current study revealed that the designed multitope vaccine has the ability to trigger a specific immune response against M. catarrhalis, additional translational research is required to confirm the effectiveness of the designed vaccine.

Immunoinformatics and molecular dynamics approaches: Next generation vaccine design against West Nile virus

West Nile Virus (WNV) is a life threatening flavivirus that causes significant morbidity and mortality worldwide. No preventive therapeutics including vaccines against WNV are available for human use. In this study, immunoinformatics approach was performed to design a multi epitope-based subunit vaccine against this deadly pathogen. Human (HLA) and Mice (H-2) allele specific potential T-cell and B-cell epitopes were shortlisted through a stringent procedure. Molecular docking showed selected epitopes that have stronger binding affinity with human TLR-4. Molecular dynamics simulation confirmed the stable nature of the docked complex. Furthermore, in silico cloning analysis ensures efficient expression of desired gene in the microbial system. Interestingly, previous studies showed that two of our selected epitopes have strong immune response against WNV. Therefore, selected epitopes could be strong vaccine candidates to prevent WNV infections in human. However, further in vitro and in vivo investigations could be strengthening the validation of the vaccine candidate against WNV.

Development of a chimeric vaccine candidate based on Toxoplasma gondii major surface antigen 1 and apicoplast proteins using comprehensive immunoinformatics approaches

This study was aimed at designing and evaluation of a multimeric vaccine construct against Toxoplasma gondii via utilization of SAG1 along with apicoplast ribosomal proteins (S2, S5 and L11). Top-ranked MHC-I and MHC-II binding as well as shared, immunodominant linear B-cell epitopes were predicted and joined together via appropriate linkers. Also, TLR-4 agonist (RS-09 synthetic protein) and His-tag were added to the N- and C-terminal of the vaccine sequence. The finally-engineered chimeric vaccine had a length of 291 amino acids with a molecular weight of 31.46 kDa. Physico-chemical features showed a soluble, highly-antigenic and non-allergenic candidate. Secondary and tertiary structures were predicted, and subsequent analyses confirmed the construct stability that was capable to properly interact with human TLR-4. Immunoinformatics-based simulation displayed potent stimulation of T- and B-cell mediated immune responses upon vaccination with the proposed multi-epitope candidate. In conclusion, obtained information demonstrated a highly antigenic vaccine candidate, which could develop high levels of IFN-γ and other components of cellular immune profile, and can be directed for toxoplasmosis prophylactic purposes.

Bioinformatics features and immunogenic epitopes of Echinococcus granulosus Myophilin as a promising target for vaccination against cystic echinococcosis

Cystic echinococcosis (CE) is a neglected zoonosis especially in underdeveloped countries around the world. Hence, immunization strategies are beneficial to avert the infection. The present investigation was aimed to predict the primary biochemical characteristics of the EgMyophilin and its potential B-cell and human leukocyte antigen (HLA)-binding epitopes as a promising vaccine candidate. Different web servers were used to predict physico-chemical, antigenic and allergenic profiles, transmembrane domain, subcellular localization, post-translational modification (PTM) sites, secondary and 3D structure, tertiary model refinement and validations. B-cell and HLA-binding epitopes were predicted and screened in terms antigenicity, allergenicity, solubility (B-cell) or hydrophobicity (T-cell). The 89.82 KDa protein was non-allergenic, hydrophilic, stable, with improved thermotolerance and 94 post-translational modification sites. The secondary structure included 42.94% alpha helix, 42.82% random coil and 41.23% extended strand. Based on Ramachandran plot output for refined model, 96.2%, 99.5%, and 0.45% of amino acid residues were incorporated in the favored, allowed, and outlier regions of the refined model, respectively. After epitope screening, four B-cell and five HLA-binding epitopes possessed the highest antigenic index in the protein sequence. This paper is a premise for further researches, and provides insights for the development of a suitable vaccine against CE. More empirical studies are required using the EgMyophilin alone or in combination with other antigens/epitopes in the future.

Designing a conserved peptide-based subunit vaccine against SARS-CoV-2 using immunoinformatics approach

The widespread of coronavirus (COVID-19) is a new global health crisis that poses a threat to the world. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originated in bats and was discovered first in Wuhan, Hubei province, China in December 2019. Immunoinformatics and bioinformatics tools were employed for the construction of a multi-epitope subunit vaccine to prevent the diseases. The antigenicity, toxicity and allergenicity of all epitopes used in the construction of the vaccine were predicted and then conjugated with adjuvants and linkers. Vaccine Toll-Like Receptors (2, 3, 4, 8 and 9) complex was also evaluated. The vaccine construct was antigenic, non-toxic and non-allergic, which indicates the vaccines ability to induce antibodies in the host, making it an effective vaccine candidate.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-020-00062-x.

Designing spike protein (S-Protein) based multi-epitope peptide vaccine against SARS COVID-19 by immunoinformatics

The outbreak of COVID-19 was originated from China, responsible for Several Acute Respiratory Syndrome (SARS). Scientists are forced to develop vaccine and effective drugs to control COVID-19 infection. To develop effective vaccine for SARS - COVID 19, immunoinformatics and computational approaches could helps to design successful vaccine against this biggest danger for humanity. Here we used various in - silico approaches to designed vaccine against COVID-19. To develop vaccine, we target S- protein, expressed on the virus surface plays important role in COVID-19 infection. We identified 12 B-cell, 9 T-helper and 20 Cytotoxic T-cell epitope based on criteria of selection. The predicted epitopes were link simultaneously with GPGPG & AAY linkers. The β-defensin was used as adjuvant, linked with selected epitope by using EAAAK linker. For vaccine construct justification we analysed its immunogenicity, allergenicity and physiochemical properties. Our study revealed that vaccine was non toxic, immunogenic and antigenic in nature and covers 98.6% of world population, important for vaccine effectively. In- silico cloning was used to analyse its expression in vector. Molecular docking was performed to study the interaction of construct with TLR (TLR3, TLR4, and TLR9) molecules. The immune simulation was conducted and conformed that our vaccine constructs can induces both acquired and humoral immunity effectively against COVID-19 at very low concentration, but along with bioinformatics study we need to conduct experiment in laboratory to validate its safety and effectiveness.

Exploring the out of sight antigens of SARS-CoV-2 to design a candidate multi-epitope vaccine by utilizing immunoinformatics approaches

SARS-CoV-2 causes a severe respiratory disease called COVID-19. Currently, global health is facing its devastating outbreak. However, there is no vaccine available against this virus up to now. In this study, a novel multi-epitope vaccine against SARS-CoV-2 was designed to provoke both innate and adaptive immune responses. The immunodominant regions of six non-structural proteins (nsp7, nsp8, nsp9, nsp10, nsp12 and nsp14) of SARS-CoV-2 were selected by multiple immunoinformatic tools to provoke T cell immune response. Also, immunodominant fragment of the functional region of SARS-CoV-2 spike (400-510 residues) protein was selected for inducing neutralizing antibodies production. The selected regions' sequences were connected to each other by furin-sensitive linker (RVRR). Moreover, the functional region of β-defensin as a well-known agonist for the TLR-4/MD complex was added at the N-terminus of the vaccine using (EAAAK)3 linker. Also, a CD4 + T-helper epitope, PADRE, was used at the C-terminal of the vaccine by GPGPG and A(EAAAK)2A linkers to form the final vaccine construct. The physicochemical properties, allergenicity, antigenicity, functionality and population coverage of the final vaccine construct were analyzed. The final vaccine construct was an immunogenic, non-allergen and unfunctional protein which contained multiple CD8 + and CD4 + overlapping epitopes, IFN-γ inducing epitopes, linear and conformational B cell epitopes. It could form stable and significant interactions with TLR-4/MD according to molecular docking and dynamics simulations. Global population coverage of the vaccine for HLA-I and II were estimated 96.2% and 97.1%, respectively. At last, the final vaccine construct was reverse translated to design the DNA vaccine. Although the designed vaccine exhibited high efficacy in silico, further experimental validation is necessary.