Immunoinformatics approaches for designing a novel multi epitope peptide vaccine against human norovirus (Norwalk virus)

In-silico formulation of a next-generation polyvalent vaccine against multiple strains of monkeypox virus and other related poxviruses

Mpox (formerly known as monkeypox) virus and some related poxviruses including smallpox virus pose a significant threat to public health, and effective prevention and treatment strategies are needed. This study utilized a reverse vaccinology approach to retrieve conserved epitopes for monkeypox virus and construct a vaccine that could provide cross-protection against related viruses with similar antigenic properties. The selected virulent proteins of monkeypox virus, MPXVgp165, and Virion core protein P4a, were subjected to epitope mapping for vaccine construction. Two vaccines were constructed using selected T cell epitopes and B cell epitopes with PADRE and human beta-defensins adjuvants conjugated in the vaccine sequence. Both constructs were found to be highly antigenic, non-allergenic, nontoxic, and soluble, suggesting their potential to generate an adequate immune response and be safe for humans. Vaccine construct 1 was selected for molecular dynamic simulation studies. The simulation studies revealed that the TLR8-vaccine complex was more stable than the TLR3-vaccine complex. The lower RMSD and RMSF values of the TLR8 bound vaccine compared to the TLR3 bound vaccine suggested better stability and consistency of hydrogen bonds. The Rg values of the vaccine chain bound to TLR8 indicated overall stability, whereas the vaccine chain bound to TLR3 showed deviations throughout the simulation. These results suggest that the constructed vaccine could be a potential preventive measure against monkeypox and related viruses however, further experimental validation is required to confirm these findings.

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

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

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.

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.

In silico discovery of epitopes of gag and env proteins for the development of a multi-epitope vaccine candidate against Maedi Visna Virus using reverse vaccinology approach

Maedi Visna Virus (MVV) causes a chronic viral disease in sheep. Since there is no specific therapeutic drug that targets MVV, development of a vaccine against the MVV is inevitable. This study aimed to analyze the gag and env proteins as vaccine candidate proteins and to identify epitopes in these proteins. In addition, it was aimed to construct a multi-epitope vaccine candidate. According to the obtained results, the gag protein was detected to be more conserved and had a higher antigenicity value. Also, the number of alpha helix in the secondary structure was higher and transmembrane helices were not detected. Although many B cell and MHC-I/II epitopes were predicted, only 19 of them were detected to have the properties of antigenic, non-allergenic, non-toxic, soluble, and non-hemolytic. Of these epitopes, five were remarkable due to having the highest antigenicity value. However, the final multi-epitope vaccine was constructed with 19 epitopes. A strong affinity was shown between the final multi-epitope vaccine and TLR-2/4. In conclusion, the gag protein was a better antigen. However, both proteins had epitopes with high antigenicity value. Also, the final multi-epitope vaccine construct had a potential to be used as a peptide vaccine due to its immuno-informatics results.

Immunoinformatic exploration of a multi-epitope-based peptide vaccine candidate targeting emerging variants of SARS-CoV-2

Many countries around the world are facing severe challenges due to the recently emerging variants of SARS-CoV-2. Over the last few months, scientists have been developing treatments, drugs, and vaccines to subdue the virus and prevent its transmission. In this context, a peptide-based vaccine construct containing pathogenic proteins of the virus known to elicit an immune response was constructed. An analysis of the spike protein-based epitopes allowed us to design an "epitope-based subunit vaccine" against coronavirus using the approaches of "reverse vaccinology" and "immunoinformatics." Computational experimentation and a systematic, comprehensive protocol were followed with an aim to develop and design a multi-epitope-based peptide (MEBP) vaccine candidate. Our study attempted to predict an MEBP vaccine by introducing mutations of SARS-CoV-2 (Delta, Lambda, Iota, Omicron, and Kappa) in Spike glycoprotein and predicting dual-purpose epitopes (B-cell and T-cell). This was followed by screening the selected epitopes based on antigenicity, allergenicity, and population coverage and constructing them into a vaccine by using linkers and adjuvants. The vaccine construct was analyzed for its physicochemical properties and secondary structure prediction, and a 3D structure was built, refined, and validated. Furthermore, the peptide-protein interaction of the vaccine construct with Toll-like receptor (TLR) molecules was performed. Immune profiling was performed to check the immune response. Codon optimization of the vaccine construct was performed to obtain the GC content before cloning it into the E. coli genome, facilitating its progression it into a vector. Finally, an in-silico simulation of the vaccine-protein complex was performed to comprehend its stability and conformational behavior.

Novel adjuvant nano-vaccine induced immune response against Acinetobacter baumannii

Developing adjuvant vaccines to combat rising multidrug-resistant (MDR) Acinetobacter baumannii (A. baumannii) infections is a promising and cost-effective approach. The aim of this analysis was to construct a pDNA-CPG C274-adjuvant nano-vaccine and investigate its immunogenicity and protection in BALB/c mice. The CPG ODN C274 adjuvant was chemically synthesized and cloned into pcDNA3.1( +), and the cloning was verified using PCR and BamHI/EcoRV restriction enzyme digestion. Then, utilizing a complex coacervation approach, pDNA-CPG C274 was encapsulated by chitosan (CS) nanoparticles (NPs). TEM and DLS are used to explore the properties of the pDNA/CSNP complex. TLR-9 pathway activation was investigated in human HEK-293 and RAW 264.7 mouse cells. The vaccine's immunogenicity and immune-protective effectiveness were investigated in BALB/c mice. The pDNA-CPG C274/CSNPs were small (mean size 79.21 ± 0.23 nm), positively charged (+ 38.87 mV), and appeared to be spherical. A continuous slow release pattern was achieved. TLR-9 activation was greatest in the mouse model with CpG ODN (C274) at concentrations of 5 and 10 μg/ml with 56% and 55%, respectively (**P < 0.01). However, in HEK-293 human cells, by increasing the concentration of CpG ODN (C274) from 1 to 50 μg/ml, the activation rate of TLR-9 also increased, so that the highest activation rate (81%) was obtained at the concentration of 50 μg/ml (***P < 0.001). pDNA-CPG C274/CSNPs immunized BALB/c mice produced increased amounts of total-IgG, as well as IFN-γ and IL-1B in serum samples, compared to non-encapsulated pDNA-CPG C274. Furthermore, liver and lung injuries, as well as bacterial loads in the liver, lung, and blood, were reduced, and BALB/c mice immunized with pDNA-CPG C274/CSNPs showed potent protection (50-75%) against acute fatal Intraperitoneal A. baumannii challenge. pDNA-CPG C274/CSNPs evoked total-IgG antibodies, Th1 cellular immunity, and the TLR-9 pathway, as well as protection against an acute fatal A. baumannii challenge. Our findings suggest that this nano-vaccine is a promising approach for avoiding A. baumannii infection when used as a powerful adjuvant.

Subunit vaccines for Acinetobacter baumannii

Acinetobacter baumannii is a gram-negative bacterium and a crucial opportunistic pathogen in hospitals. A. baumannii infection has become a challenging problem in clinical practice due to the increasing number of multidrug-resistant strains and their prevalence worldwide. Vaccines are effective tools to prevent and control A. baumannii infection. Many researchers are studying subunit vaccines against A. baumannii. Subunit vaccines have the advantages of high purity, safety, and stability, ease of production, and highly targeted induced immune responses. To date, no A. baumannii subunit vaccine candidate has entered clinical trials. This may be related to the easy degradation of subunit vaccines in vivo and weak immunogenicity. Using adjuvants or delivery vehicles to prepare subunit vaccines can slow down degradation and improve immunogenicity. The common immunization routes include intramuscular injection, subcutaneous injection, intraperitoneal injection and mucosal vaccination. The appropriate immunization method can also enhance the immune effect of subunit vaccines. Therefore, selecting an appropriate adjuvant and immunization method is essential for subunit vaccine research. This review summarizes the past exploration of A. baumannii subunit vaccines, hoping to guide current and future research on these vaccines.

Current Update on Rotavirus in-Silico Multiepitope Vaccine Design

Rotavirus gastroenteritis is one of the leading causes of pediatric morbidity and mortality worldwide in infants and under-five populations. The World Health Organization (WHO) recommended global incorporation of the rotavirus vaccine in national immunization programs to alleviate the burden of the disease. Implementation of the rotavirus vaccination in certain regions of the world brought about a significant and consistent reduction of rotavirus-associated hospitalizations. However, the efficacy of licensed vaccines remains suboptimal in low-income countries where the incidences of rotavirus gastroenteritis continue to happen unabated. The problem of low efficacy of currently licensed oral rotavirus vaccines in low-income countries necessitates continuous exploration, design, and development of new rotavirus vaccines. Traditional vaccine development is a complex, expensive, labor-intensive, and time-consuming process. Reverse vaccinology essentially utilizes the genome and proteome information on pathogens and has opened new avenues for in-silico multiepitope vaccine design for a plethora of pathogens, promising time reduction in the complete vaccine development pipeline by complementing the traditional vaccinology approach. A substantial number of reviews on licensed rotavirus vaccines and those under evaluation are already available in the literature. However, a collective account of rotavirus in-silico vaccines is lacking in the literature, and such an account may further fuel the interest of researchers to use reverse vaccinology to expedite the vaccine development process. Therefore, the main focus of this review is to summarize the research endeavors undertaken for the design and development of rotavirus vaccines by the reverse vaccinology approach utilizing the tools of immunoinformatics.

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.

In-Silico Exploration of Plant Metabolites as Potential Remedies of Norovirus

Research is still being carried out to develop specific medications or vaccinations to fight norovirus, a key contributor to foodborne illness. This study evaluated certain plant-based active chemicals as prospective candidates for such treatments using virtual screening techniques and other computer assessments. Twenty (20) plant metabolites were tested against the norovirus VP1, VP2, P48, and P22 protein domains using the molecular docking method. In terms of the lowest global binding energy, Asiatic acid, avicularin, guaijaverin, and curcumin exhibited the highest binding affinity with all selected proteins. Each viral protein's essential binding sites with the potential drugs and drug surface hotspots were uncovered. The ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis was used to further analyze the pharmacological profiles of the top candidates. According to the results, none of the substances showed any adverse consequences that would reduce their drug-like properties. According to the analysis of the toxicity pattern, no detectable tumorigenic, mutagenic, irritating, or reproductive effects of the compounds were discovered. However, among the top four alternatives, curcumin exhibited the highest levels of cytotoxicity and immunotoxicity. These discoveries may open the way for the development of effective norovirus therapies and safety measures. Due to the positive outcomes, we strongly propose more in vivo experiments for the experimental validation of our findings.

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.

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.

Screening of potential antigens from whole proteome and development of multi-epitope vaccine against Rhizopus delemar using immunoinformatics approaches

Mucormycosis is a deadly fungal disease mainly caused by Rhizopus oryzae (strain 99-880), also known as Rhizopus delemar. Previously, mucormycosis occurs in immunocompromised patients of diabetes mellitus, cancer, organ transplant, etc. But there was a drastic increase in mucormycosis cases in the ongoing COVID-19 pandemic. Despite several available therapies and antifungal treatments, the mortality rate of mucormycosis is about more than 50%. Currently, there is no vaccine available in the market for mucormycosis that urgently needs to develop a potential vaccine against mucormycosis with high efficacy. In the present study, we have screened 4 genome-derived predicted antigens (GDPA) through sequential filtration of the whole proteome of R. delemar using different benchmarked bioinformatics tools. These 4 GDPA along with 4 randomly selected experimentally reported antigens (ERA) were sourced for prediction of B- and T- cell epitopes and utilized in designing of two potential multi-epitope vaccine candidates which can induce both innate and adaptive immunity against R. delemar. Besides these, comparative immune simulation studies and in silico cloning were performed using L. lactis as an expression system for their possible uses as oral vaccines. This is the first multi-epitope vaccine designed against R. delemar through systematic pipelined reverse vaccinology and immunoinformatic approaches. Although the wet-lab based experimental validation of designed vaccines is required before testing in the preclinical model, the current study will significantly help in reducing the cost of experimentation as well as improving the efficacy of vaccine therapy against mucormycosis and other pathogenic diseases.Communicated by Ramaswamy H. Sarma.

In Silico Designing of a Multitope Vaccine against Rhizopus microsporus with Potential Activity against Other Mucormycosis Causing Fungi

During the current era of the COVID-19 pandemic, the dissemination of Mucorales has been reported globally, with elevated rates of infection in India, and because of the high rate of mortality and morbidity, designing an effective vaccine against mucormycosis is a major health priority, especially for immunocompromised patients. In the current study, we studied shared Mucorales proteins, which have been reported as virulence factors, and after analysis of several virulent proteins for their antigenicity and subcellular localization, we selected spore coat (CotH) and serine protease (SP) proteins as the targets of epitope mapping. The current study proposes a vaccine constructed based on top-ranking cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B cell lymphocyte (BCL) epitopes from filtered proteins. In addition to the selected epitopes, β-defensins adjuvant and PADRE peptide were included in the constructed vaccine to improve the stimulated immune response. Computational tools were used to estimate the physicochemical and immunological features of the proposed vaccine and validate its binding with TLR-2, where the output data of these assessments potentiate the probability of the constructed vaccine to stimulate a specific immune response against mucormycosis. Here, we demonstrate the approach of potential vaccine construction and assessment through computational tools, and to the best of our knowledge, this is the first study of a proposed vaccine against mucormycosis based on the immunoinformatics approach.

Multi-epitope based subunit vaccine construction against Banna virus targeting on two outer proteins (VP4 and VP9): A computational approach

Recently, RNA viruses have gained a mammoth concern for causing various outbreaks, and due to pandemics, they are acquiring additional attention throughout the world. An emerging RNA as well as vector-borne Banna Virus (BAV) is a human pathogen resulting in encephalitis, fever, headache, muscle aches, and severe coma. Besides human, pathogenic BAV was also detected from pigs, cattle, ticks, midges, and mosquitoes in Indonesia, China, and Vietnam. Due to high mutation tendency and dearth of a species barrier, this virus will consider as a significant threat in the near future throughout the planet, particularly in Africa. Despite of severe human case fatalities in several countries, there are no specific therapeutics, available vaccines, and other preventive measures against BAV. Thus, to find out the effective therapeutics and preventive strategies are crying exigency. In the present study, a unique multi-epitope-based peptide vaccine candidate is constructed using bioinformatics' tools that efficiently instigate immune cells for generating BAV antibodies. The potential vaccine candidates were developed using both T and B -cell epitopes. UniprotKB database was used to retrieve of two outer proteins (VP9 and VP4), and homologous sequences of BAV taxid: 7763, 649,604, 77,763, and 8453 were searched by NCBI BLAST. These serotypes are the most closely associated with the disease. Then combining the best-selected epitopes in various combinations with different adjuvants, three distinct vaccine candidates were formed. The validity tests were performed for the screened vaccine candidate regarding stability, allergenicity, and antigenicity parameters. Moreover, molecular dynamic simulations of the selected vaccine with TLR-8 immune receptor confirmed the stability of the binding pose and showed a significant response to immune cells. Thus, the results established that the designed chimeric peptide vaccine could enhance the immune response against BAV.

Combination of highly antigenic nucleoproteins to inaugurate a cross-reactive next generation vaccine candidate against Arenaviridae family

Arenaviral infections often result lethal hemorrhagic fevers, affecting primarily in African and South American regions. To date, there is no FDA-approved licensed vaccine against arenaviruses and treatments have been limited to supportive therapy. Hence, the study was employed to design a highly immunogenic cross-reactive vaccine against Arenaviridae family using reverse vaccinology approach. The whole proteome of Lassa virus (LASV), Lymphocytic Choriomeningitis virus (LCMV), Lujo virus and Guanarito virus were retrieved and assessed to determine the most antigenic viral proteins. Both T-cell and B-cell epitopes were predicted and screened based on transmembrane topology, antigenicity, allergenicity, toxicity and molecular docking analysis. The final constructs were designed using different adjuvants, top epitopes, PADRE sequence and respective linkers and were assessed for the efficacy, safety, stability and molecular cloning purposes. The proposed epitopes were highly conserved (84%–100%) and showed greater cumulative population coverage. Moreover, T cell epitope GWPYIGSRS was conserved in Junin virus (Argentine mammarenavirus) and Sabia virus (Brazilian mammarenavirus), while B cell epitope NLLYKICLSG was conserved in Machupo virus (Bolivian mammarenavirus) and Sabia virus, indicating the possibility of final vaccine construct to confer a broad range immunity in the host. Docking analysis of the refined vaccine with different MHC molecules and human immune receptors were biologically significant. The vaccine-receptor (V1-TLR3) complex showed minimal deformability at molecular level and was compatible for cloning into pET28a(+) vector of E. coli strain K12. The study could be helpful in developing vaccine to combat arenaviral infections in the future. However, further in vitro and in vivo trials using model animals are highly recommended for the experimental validation of our findings.

A Multiepitope Peptide, rOmp22, Encapsulated in Chitosan-PLGA Nanoparticles as a Candidate Vaccine Against Acinetobacter baumannii Infection

Background

The development of vaccines is a promising and cost-effective strategy to prevent emerging multidrug-resistant (MDR) Acinetobacter baumannii (A. baumannii) infections. The purpose of this study was to prepare a multiepitope peptide nanovaccine and evaluate its immunogenicity and protective effect in BALB/c mice.

Methods

The B-cell and T-cell epitopes of Omp22 from A. baumannii were predicted using bioinformatics methods and identified by immunological experiments. The optimal epitopes were conjugated in series by 6-aminocaproic acid and chemically synthesized multiepitope polypeptide rOmp22. Then, rOmp22 was encapsulated by chitosan (CS) and poly (lactic-co-glycolic) acid (PLGA) to prepare CS-PLGA-rOmp22 nanoparticles (NPs). The immunogenicity and immunoprotective efficacy of the vaccine were evaluated in BALB/c mice.

Results

CS-PLGA-rOmp22 NPs were small (mean size of 272.83 nm) with apparently spherical structures, positively charged (4.39 mV) and nontoxic to A549 cells. A high encapsulation efficiency (54.94%) and a continuous slow release pattern were achieved. Compared with nonencapsulated rOmp22, CS-PLGA-rOmp22 immunized BALB/c mice induced higher levels of rOmp22-specific IgG in serum and IFN-γ in splenocyte supernatant. Additionally, lung injury and bacterial burdens in the lung and blood were suppressed, and potent protection (57.14%-83.3%) against acute lethal intratracheal A. baumannii challenge was observed in BALB/c mice vaccinated with CS-PLGA-rOmp22.

Conclusion

CS-PLGA-rOmp22 NPs elicited specific IgG antibodies, Th1 cellular immunity and protection against acute lethal intratracheal A. baumannii challenge. Our results indicate that this nanovaccine is a desirable candidate for preventing A. baumannii infection.

Implementation of in silico methods to predict common epitopes for vaccine development against Chikungunya and Mayaro viruses

Being a Positive sense RNA virus the recent reemergence of Chikungunya and Mayaro virus has taken the concern of the leading scientific communities of the world. Though the outbreak of Mayaro virus is limited to Neotropical region only, Chikungunya is already identified in over 60 countries around the world. Besides, the lack of a strong protective treatment, misdiagnosis issue and co-circulation of both the viruses calls for a new strategy which could potentially prevent these infections from spreading. In this study, we therefore, identified the peptide based vaccine candidates e.g. epitopes for B cell and T cell from Chikungunya virus which also showed to be homologous to the Mayaro virus through immuno-informatics and computational approaches. Final epitopes identified from the most antigenic structural polyprotein of both the viruses were 5 for CD8+ T cell Epitopes (209KPGDSGRPI217, 219TGTMGHFIL227, 239ALSVVTWNK247, 98KPGRRERMC106 and 100GRRERMCMK108), 2 epitopes for CD4+ T cell (105MCMKIENDCIFEVKH119 and 502DRTLLSQQSGNVKIT516) and a single epitope for B cell (504GGRFTIPTGAGKPGDSGRPI518). Analysis of our predicted epitopes for population coverage showed prominent population coverage (92.43%) around the world. Finally, molecular docking simulation of the foreseen T cell epitopes with respondent HLA alleles secured good HLA-epitope interaction. This study was directed towards the discovery of potential antigenic epitopes which can open up a new skyline to design novel vaccines for combating both of the diseases at the same time.

Immunoinformatics designed T cell multi epitope dengue peptide vaccine derived from non structural proteome

Dengue viral disease has been reported as an Aedes aegypti mosquito-borne human disease and causing a severe global public health concern. In this study, immunoinformatics methods was deployed for crafting CTL T-cell epitopes as dengue vaccine candidates. The NS1 protein sequence of dengue serotype 1 strain retrieved from the protein database and T-cell epitopes (n = 85) were predicted by the artificial neural network. The conserved epitopes (n = 10) were predicted and selected for intensive computational analysis. The machine learning technique and quantitative matrix-based toxicity analysis assured nontoxic peptide selection. Hidden Markov Model derived Structural Alphabet (SA) based algorithm predicted the 3D molecular structure and all-atom structure of peptide ligand validated by Ramachandran-plot. Three-tier molecular docking approaches were used to predictthe peptide - HLA docking complex. Molecular dynamics (MD) simulation study confirmed the docking complex was stable in the time frame of 100ns. Population coverage analysis predicted the interaction epitope interaction with a particular population of HLA. These results concluded that the computationally designed HTLWSNGVL and FTTNIWLKL epitope peptides could be used as putative agents for the multi CTL T cell epitope vaccine. The vaccine protein sequence expression and translation were analyzed in the prokaryotic vector adapted by codon usage. Such in silico formulated CTL T-cell-based prophylactic vaccines could encourage the commercial development of dengue vaccines.

A comprehensive screening of the whole proteome of hantavirus and designing a multi-epitope subunit vaccine for cross-protection against hantavirus: Structural vaccinology and immunoinformatics study

Hantaviruses are an emerging zoonotic group of rodent-borne viruses that are having serious implications on global public health due to the increase in outbreaks. Since there is no permanent cure, there is increasing interest in developing a vaccine against the hantavirus. This research aimed to design a robust cross-protective subunit vaccine using a novel immunoinformatics approach. After careful evaluation, the best predicted cytotoxic & helper T-cell and B-cell epitopes from nucleocapsid proteins, glycoproteins, RdRp proteins, and non-structural proteins were considered as potential vaccine candidates. Among the four generated vaccine models with different adjuvant, the model with toll-like receptor-4 (TLR-4) agonist adjuvant was selected because of its high antigenicity, non-allergenicity, and structural quality. The selected model was 654 amino acids long and had a molecular weight of 70.5 kDa, which characterizes the construct as a good antigenic vaccine candidate. The prediction of the conformational B-lymphocyte (CBL) epitope secured its ability to induce the humoral response. Thereafter, disulfide engineering improved vaccine stability. Afterwards, the molecular docking confirmed a good binding affinity of -1292 kj/mol with considered immune receptor TLR-4 and the dynamics simulation showed high stability of the vaccine-receptor complex. Later, the in silico cloning confirmed the better expression of the constructed vaccine protein in E. coli K12. Finally, in in silico immune simulation, significantly high levels of immunoglobulin M (IgM), immunoglobulin G1 (IgG1), cytotoxic & helper T lymphocyte (CTL & HTL) populations, and numerous cytokines such as interferon-γ (IFN-γ), interleukin-2 (IL-2) etc. were found as coherence with actual immune response and also showed faster antigen clearance for repeated exposures. Nonetheless, experimental validation can demonstrate the safety and cross-protective ability of the proposed vaccine to fight against hantavirus infection.

Designing of a next generation multiepitope based vaccine (MEV) against SARS-COV-2: Immunoinformatics and in silico approaches

Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory coronavirus 2 (SARS-COV-2) is a significant threat to global health security. Till date, no completely effective drug or vaccine is available to cure COVID-19. Therefore, an effective vaccine against SARS-COV-2 is crucially needed. This study was conducted to design an effective multiepitope based vaccine (MEV) against SARS-COV-2. Seven highly antigenic proteins of SARS-COV-2 were selected as targets and different epitopes (B-cell and T-cell) were predicted. Highly antigenic and overlapping epitopes were shortlisted. Selected epitopes indicated significant interactions with the HLA-binding alleles and 99.93% coverage of the world's population. Hence, 505 amino acids long MEV was designed by connecting 16 MHC class I and eleven MHC class II epitopes with suitable linkers and adjuvant. MEV construct was non-allergenic, antigenic, stable and flexible. Furthermore, molecular docking followed by molecular dynamics (MD) simulation analyses, demonstrated a stable and strong binding affinity of MEV with human pathogenic toll-like receptors (TLR), TLR3 and TLR8. Finally, MEV codons were optimized for its in silico cloning into Escherichia coli K-12 system, to ensure its increased expression. Designed MEV in present study could be a potential candidate for further vaccine production process against COVID-19. However, to ensure its safety and immunogenic profile, the proposed MEV needs to be experimentally validated.

Development of multi-epitope subunit vaccine for protection against the norovirus' infections based on computational vaccinology

Human Norovirus belongs to a family Calciviridae, and was identified in the outbreak of gastroenteritis in Norwalk, due to its seasonal prevalence known as "winter vomiting disease." Treatment of Norovirus infection is still mysterious because there is no effective antiviral drugs or vaccine developed to protect against the infection, to eradicate the infection an effective vaccine should be developed. In this study, capsid protein (A7YK10), small protein (A7YK11), and polyprotein (A7YK09) were utilized. These proteins were subjected to B and T cell epitopes prediction by using reliable immunoinformatics tools. The antigenic and non-allergenic epitopes were selected for the subunit vaccine, which can activate cellular and humoral immune responses. Linkers joined these epitopes together. The vaccine structure was modelled and validated by using Errat, ProSA, and rampage servers. The modelled vaccine was docked with TLR-7. The stability of the docked complex was evaluated by MD simulation. To apply the concept in a wet lab, the reverse translated vaccine sequence was cloned in pET28a (+). The vaccine developed in this study requires experimental validation to ensure its effectiveness against the disease.Communicated by Ramaswamy H. Sarma.

Genome based evolutionary lineage of SARS-CoV-2 towards the development of novel chimeric vaccine

The present study aimed to predict a novel chimeric vaccine by simultaneously targeting four major structural proteins via the establishment of ancestral relationship among different strains of coronaviruses. Conserved regions from the homologous protein sets of spike glycoprotein, membrane protein, envelope protein and nucleocapsid protein were identified through multiple sequence alignment. The phylogeny analyses of whole genome stated that four proteins reflected the close ancestral relation of SARS-CoV-2 to SARS-COV-1 and bat coronavirus. Numerous immunogenic epitopes (both T cell and B cell) were generated from the common fragments which were further ranked on the basis of antigenicity, transmembrane topology, conservancy level, toxicity and allergenicity pattern and population coverage analysis. Top putative epitopes were combined with appropriate adjuvants and linkers to construct a novel multiepitope subunit vaccine against COVID-19. The designed constructs were characterized based on physicochemical properties, allergenicity, antigenicity and solubility which revealed the superiority of construct V3 in terms safety and efficacy. Essential molecular dynamics and normal mode analysis confirmed minimal deformability of the refined model at molecular level. In addition, disulfide engineering was investigated to accelerate the stability of the protein. Molecular docking study ensured high binding affinity between construct V3 and HLA cells, as well as with different host receptors. Microbial expression and translational efficacy of the constructs were checked using pET28a(+) vector of E. coli strain K12. However, the in vivo and in vitro validation of suggested vaccine molecule might be ensured with wet lab trials using model animals for the implementation of the presented data.

Identification of potential inhibitory analogs of metastasis tumor antigens (MTAs) using bioactive compounds: revealing therapeutic option to prevent malignancy.. [DOI: 10.1101/2020.10.19.345975]

The deeper understanding of metastasis phenomenon and detection of drug targets could be a potential approach to minimize cancer mortality. In this study, attempts were taken to unmask novel therapeutics to prevent metastasis and cancer progression. Initially, we explored the physiochemical, structural and functional insights of three metastasis tumor antigens (MTAs) and evaluated some plant based bioactive compounds as potent MTA inhibitors. From 50 plant metabolites screened, isoflavone, gingerol, citronellal and asiatic acid showed maximum binding affinity with all three MTA proteins. The ADME analysis detected no undesirable toxicity that could reduce the drug likeness properties of top plant metabolites. Moreover, molecular dynamics studies revealed that the complexes were stable and showed minimum fluctuation at molecular level. We further performed ligand based virtual screening to identify similar drug molecules using a large collection of 3,76,342 compounds from DrugBank. The results suggested that several structural analogs (e.g. Tramadol, Nabumetone, DGLA, Hydrocortisone) may act as agonist to block the MTA proteins and inhibit cancer progression at early stage. The study could be useful to develop effective medications against cancer metastasis in future. Due to encouraging results, we highly recommend furtherin vitroandin vivotrials for the experimental validation of the findings.

Ancestral origin, antigenic resemblance and epidemiological insights of novel coronavirus (SARS-CoV-2): Global burden and Bangladesh perspective

SARS-CoV-2, a new coronavirus strain responsible for COVID-19, has emerged in Wuhan City, China, and continuing its global pandemic nature. The availability of the complete gene sequences of the virus helps to know about the origin and molecular characteristics of this virus. In the present study, we performed bioinformatic analysis of the available gene sequence data of SARS-CoV-2 for the understanding of evolution and molecular characteristics and immunogenic resemblance of the circulating viruses. Phylogenetic analysis was performed for four types of representative viral proteins (spike, membrane, envelope and nucleoprotein) of SARS-CoV-2, HCoV-229E, HCoV-OC43, SARS-CoV, HCoV-NL63, HKU1, MERS-CoV, HKU4, HKU5 and BufCoV-HKU26. The findings demonstrated that SARS-CoV-2 exhibited convergent evolutionary relation with previously reported SARS-CoV. It was also depicted that SARS-CoV-2 proteins were highly similar and identical to SARS-CoV proteins, though proteins from other coronaviruses showed a lower level of resemblance. The cross-checked conservancy analysis of SARS-CoV-2 antigenic epitopes showed significant conservancy with antigenic epitopes derived from SARS-CoV. Descriptive epidemiological analysis on several epidemiological indices was performed on available epidemiological outbreak information from several open databases on COVID-19 (SARS-CoV-2). Satellite-derived imaging data have been employed to understand the role of temperature in the environmental persistence of the virus. Findings of the descriptive analysis were used to describe the global impact of newly emerged SARS-CoV-2, and the risk of an epidemic in Bangladesh.

Design of a multi-epitope peptide vaccine candidate against chandipura virus: an immuno-informatics study

Chandipura virus (CHPV) is an emerging pathogen responsible for acute encephalitic syndrome (AES) in pediatric population in India. Several outbreaks of CHPV have been reported from different states of India since the year 2003. At present there is no vaccine or therapeutic measures available to curtail the disease. In this study, we have identified both T-cell and B-cell epitopes of different antigenic proteins of CHPV like Nucleoprotein (N), Phosphoprotein (P) and Matrix protein (M) along with the immuno-dominant glycoprotein (G) and conducted in silico characterization for the same. The idea is to design a multi-epitope peptide construct using the epitopes, which were found to be non-toxic, non-allergenic and possessing high immunogenicity. The final multi-epitope construct named as: MEC-CHPV, comprised of β-defensin adjuvant at N-terminal for enhancement of immunogenicity followed by fourteen B-cell epitopes, four Helper T-cell epitopes and six Cytotoxic T-cell epitopes. The characterization of designed construct was carried out in terms of physicochemical parameters, antigenicity and allergenicity. The 3D structure prediction was performed. Molecular docking and molecular-dynamics simulation of MEC-CHPV with Toll like receptors (TLR-3 and TLR-8) showed stable interactions. In silico cloning of MEC-CHPV in pET30a(+) expression vector was also conducted using codon optimization. The in silico immune-simulation indicated a typical immune response against MEC-CHPV when used as a potential vaccine. This study provides a cost-effective and time-saving way to design a peptide vaccine candidate against CHPV using immuno-informatics approach. Development of the MEC-CHPV construct may pave the way for future laboratory experiments.Communicated by Ramaswamy H. Sarma.

Comprehensive genome based analysis of Vibrio parahaemolyticus for identifying novel drug and vaccine molecules: Subtractive proteomics and vaccinomics approach

Multidrug-resistant Vibrio parahaemolyticus has become a significant public health concern. The development of effective drugs and vaccines against Vibrio parahaemolyticus is the current research priority. Thus, we aimed to find out effective drug and vaccine targets using a comprehensive genome-based analysis. A total of 4822 proteins were screened from V. parahaemolyticus proteome. Among 16 novel cytoplasmic proteins, 'VIBPA Type II secretion system protein L' and 'VIBPA Putative fimbrial protein Z' were subjected to molecular docking with 350 human metabolites, which revealed that Eliglustat, Simvastatin and Hydroxocobalamin were the top drug molecules considering free binding energy. On the contrary, 'Sensor histidine protein kinase UhpB' and 'Flagellar hook-associated protein of 25 novel membrane proteins were subjected to T-cell and B-cell epitope prediction, antigenicity testing, transmembrane topology screening, allergenicity and toxicity assessment, population coverage analysis and molecular docking analysis to generate the most immunogenic epitopes. Three subunit vaccines were constructed by the combination of highly antigenic epitopes along with suitable adjuvant, PADRE sequence and linkers. The designed vaccine constructs (V1, V2, V3) were analyzed by their physiochemical properties and molecular docking with MHC molecules- results suggested that the V1 is superior. Besides, the binding affinity of human TLR-1/2 heterodimer and construct V1 could be biologically significant in the development of the vaccine repertoire. The vaccine-receptor complex exhibited deformability at a minimum level that also strengthened our prediction. The optimized codons of the designed construct was cloned into pET28a(+) vector of E. coli strain K12. However, the predicted drug molecules and vaccine constructs could be further studied using model animals to combat V. parahaemolyticus associated infections.

Designing a novel mRNA vaccine against SARS-CoV-2: An immunoinformatics approach

SARS-CoV-2 is the deadly virus behind COVID-19, the disease that went on to ravage the world and caused the biggest pandemic 21st century has witnessed so far. On the face of ongoing death and destruction, the urgent need for the discovery of a vaccine against the virus is paramount. This study resorted to the emerging discipline of immunoinformatics in order to design a multi-epitope mRNA vaccine against the spike glycoprotein of SARS-CoV-2. Various immunoinformatics tools were utilized to predict T and B lymphocyte epitopes. The epitopes were channeled through a filtering pipeline comprised of antigenicity, toxicity, allergenicity, and cytokine inducibility evaluation with the goal of selecting epitopes capable of generating both T and B cell-mediated immune responses. Molecular docking simulation between the epitopes and their corresponding MHC molecules was carried out. 13 epitopes, a highly immunogenic adjuvant, elements for proper sub-cellular trafficking, a secretion booster, and appropriate linkers were combined for constructing the vaccine. The vaccine was found to be antigenic, almost neutral at physiological pH, non-toxic, non-allergenic, capable of generating a robust immune response and had a decent worldwide population coverage. Based on these parameters, this design can be considered a promising choice for a vaccine against SARS-CoV-2.

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SARS-CoV-2, the causative agent for COVID-19, has caused the biggest pandemic 21st century has witnessed so far.

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Here, immunoinformatics was used for designing a muti-epitope mRNA vaccine against the spike glycoprotein of SARS-CoV-2.

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Through stringent selection of T and B cell epitopes and other necessary elements, a vaccine was constructed in silico.

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Proposed mechanism of its synthesis, delivery and action has also been presented.

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The vaccine was found to be immunogenic, almost neutral, non-toxic, non-allergenic and has a decent worldwide coverage.

Multiepitope-Based Subunit Vaccine Design and Evaluation against Respiratory Syncytial Virus Using Reverse Vaccinology Approach

Respiratory syncytial virus (RSV) is primarily associated with respiratory disorders globally. Despite the availability of information, there is still no competitive vaccine available for RSV. Therefore, the present study has been designed to develop a multiepitope-based subunit vaccine (MEV) using a reverse vaccinology approach to curb RSV infections. Briefly, two highly antigenic and conserved proteins of RSV (glycoprotein and fusion protein) were selected and potential epitopes of different categories (B-cell and T-cell) were identified from them. Eminently antigenic and overlapping epitopes, which demonstrated strong associations with their respective human leukocyte antigen (HLA) alleles and depicted collective ~70% coverage of the world's populace, were shortlisted. Finally, 282 amino acids long MEV construct was established by connecting 13 major histocompatibility complex (MHC) class-I with two MHC class-II epitopes with appropriate adjuvant and linkers. Adjuvant and linkers were added to increase the immunogenic stimulation of the MEV. Developed MEV was stable, soluble, non-allergenic, non-toxic, flexible and highly antigenic. Furthermore, molecular docking and molecular dynamics (MD) simulations analyses were carried out. Results have shown a firm and robust binding affinity of MEV with human pathogenic toll-like receptor three (TLR3). The computationally mediated immune response of MEV demonstrated increased interferon-γ production, a significant abundance of immunoglobulin and activation of macrophages which are essential for immune-response against RSV. Moreover, MEV codons were optimized and in silico cloning was performed, to ensure its increased expression. These outcomes proposed that the MEV developed in this study will be a significant candidate against RSV to control and prevent RSV-related disorders if further investigated experimentally.

3CL hydrolase-based multiepitope peptide vaccine against SARS-CoV-2 using immunoinformatics

The present study provides the first multiepitope vaccine construct using the 3CL hydrolase protein of SARS-CoV-2. The coronavirus 3CL hydrolase (Mpro) enzyme is essential for proteolytic maturation of the virus. This study was based on immunoinformatics and structural vaccinology strategies. The design of the multiepitope vaccine was built using helper T-cell and cytotoxic T-cell epitopes from the 3CL hydrolase protein along with an adjuvant to enhance immune response; these are joined to each other by short peptide linkers. The vaccine also carries potential B-cell linear epitope regions, B-cell discontinuous epitopes, and interferon-γ-inducing epitopes. Epitopes of the constructed multiepitope vaccine were found to be antigenic, nonallergic, nontoxic, and covering large human populations worldwide. The vaccine construct was modeled, validated, and refined by different programs to achieve a high-quality three-dimensional structure. The resulting high-quality model was applied for conformational B-cell epitope selection and docking analyses with toll-like receptor-3 for understanding the capability of the vaccine to elicit an immune response. In silico cloning and codon adaptation were also performed with the pET-19b plasmid vector. The designed multiepitope peptide vaccine may prompt the development of a vaccine to control SARS-CoV-2 infection.

A cutting-edge immunoinformatics approach for design of multi-epitope oral vaccine against dreadful human malaria

Human malaria is a pathogenic disease mainly caused by Plasmodium falciparum, which was responsible for about 405,000 deaths globally in the year 2018. To date, several vaccine candidates have been evaluated for prevention, which failed to produce optimal output at various preclinical/clinical stages. This study is based on designing of polypeptide vaccines (PVs) against human malaria that cover almost all stages of life-cycle of Plasmodium and for the same 5 genome derived predicted antigenic proteins (GDPAP) have been used. For the development of a multi-immune inducer, 15 PVs were initially designed using T-cell epitope ensemble, which covered >99% human population as well as linear B-cell epitopes with or without adjuvants. The immune simulation of PVs showed higher levels of T-cell and B-cell activities compared to positive and negative vaccine controls. Furthermore, in silico cloning of PVs and codon optimization followed by enhanced expression within Lactococcus lactis host system was also explored. Although, the study has sound theoretical and in silico findings, the in vitro/in vivo evaluation seems imperative to warrant the immunogenicity and safety of PVs towards management of P. falciparum infection in the future.

Extensive immunoinformatics study for the prediction of novel peptide-based epitope vaccine with docking confirmation against envelope protein of Chikungunya virus: a computational biology approach

Chikungunya virus (CHIKV) instigating Chikungunya fever is a global infective menace resulting in high fever, weakened joint-muscle pain, and brain inflammation. Inaccessibility and unavailability of effective drugs have led us to an uncertain arena when it comes to providing proper medical treatment to the affected people. In this study, authentic encroachment has been made concerning the peptide-based epitope vaccine designing against CHIKV. A Proteome-wide search was performed to locate a conserved portion among the accessible viral outer membrane proteins which showcase a remarkable immune response using specific immunoinformatics and docking simulation tools. Primarily, the most probable immunogenic envelope glycoproteins E1 and E2 were identified from the UniProt database depending on their antigenicity scores. Subsequently, we selected two distinctive sequences "SEDVYANTQLVLQRP" and "IMLLYPDHPTLLSYR" in both E1 and E2 glycoproteins respectively. These two sequences identified as the most potent T and B cell epitope-based peptides as they interacted with 6 and 7 HLA-I and 5 HLA-II molecules with an extremely low IC50 score that was verified by molecular docking. Moreover, the sequences possess no allergenicity and are certainly located outside the transmembrane region. In addition, the sequences exhibited 88.46% and 100.00% Conservancy, covering high population coverage of 89.49% to 94.74% and 60.51% to 88.87% respectively in endemic countries. The identified peptide SEDVYANTQLVLQRP and IMLLYPDHPTLLSYR can be utilized next for the development of peptide-based epitope vaccine contrary to CHIKV, so further documentations and experimentations like Antigen testing, Antigen production, Clinical trials are needed to prove the validity of it. Communicated by Ramaswamy H. Sarma.

Exploring T & B-cell epitopes and designing multi-epitope subunit vaccine targeting integration step of HIV-1 lifecycle using immunoinformatics approach

Till now, AIDS, caused by the human immunodeficiency virus (HIV) is still a severe health problem worldwide. It weakens the immune system by targeting the T-helper cells. Specifically, the severity of the pandemic HIV-1 makes the emergence of an enduring effective vaccine against HIV-1. Therefore, we have applied a series of immunoinformatics approaches to the four conserved domains of HIV-1 integrase (IN) proteins to design an effective multi-epitope based subunit vaccine which might induce a competent immunity against HIV-1. Therefore, we have selected three peptide fragments that contained all overlapping epitopes (35 CD4⁺, 8 CD8⁺ T-cell epitopes, and 3 B-cell epitopes) where the epitopes had a high conservancy score. The cumulative population coverage for combined CD8⁺ and CD4⁺ T-cell epitopes and their respective HLA-alleles were found as 98.03% in the world which is also followed by East Asia (96.24%), South Asia (96.31%), North Africa (96.14%), North America (98.99%), and Europe (98.80%). The proposed vaccine composed by an adjuvant (β-defensin) at the N-terminal site of the vaccine constructs and three peptide fragments where the adjuvant was fused by EAAAK linker and the peptide fragments were fused by GPGPG linker. The designed final vaccine construct (length: 159 amino acid) was found to be antigenic and non-allergic, which indicates its safety. The vaccine construct was found as good antigenic, stable, higher thermostable, and hydrophilic in nature. The codon adaptation and in silico cloning ensured the high expression rate of the vaccine constructs in E. coli K12 with CAI value of 1.0. Finally, the binding affinity of the vaccine constructs with the immune receptor TLR3 was confirmed by the lowest energy score of -1026.8 evaluated by molecular docking. However, the proposed in silico vaccine construct needs experimental validation for assuring the safety and immunogenicity profile which will ensure an active immunity against HIV-1.

Contriving a chimeric polyvalent vaccine to prevent infections caused by herpes simplex virus (type-1 and type-2): an exploratory immunoinformatic approach

Herpes simplex virus type 1 (HSV-1) and 2 (HSV-2) cause a variety of infections including oral-facial infections, genital herpes, herpes keratitis, cutaneous infection and so on. To date, FDA-approved licensed HSV vaccine is not available yet. Hence, the study was conducted to identify and characterize an effective epitope based polyvalent vaccine against both types of Herpes Simplex Virus. The selected proteins were retrieved from ViralZone and assessed to design highly antigenic epitopes by binding analyses of the peptides with MHC class-I and class-II molecules, antigenicity screening, transmembrane topology screening, allergenicity and toxicity assessment, population coverage analysis and molecular docking approach. The final vaccine was constructed by the combination of top CTL, HTL and BCL epitopes from each protein along with suitable adjuvant and linkers. Physicochemical and secondary structure analysis, disulfide engineering, molecular dynamic simulation and codon adaptation were further employed to develop a unique multi-epitope peptide vaccine. Docking analysis of the refined vaccine structure with different MHC molecules and human immune TLR-2 receptor demonstrated higher interaction. Complexed structure of the modeled vaccine and TLR-2 showed minimal deformability at molecular level. Moreover, translational potency and microbial expression of the modeled vaccine was analyzed with pET28a(+) vector for E. coli strain K12 and the vaccine constructs had no similarity with entire human proteome. The study enabled design of a novel chimeric polyvalent vaccine to confer broad range immunity against both HSV serotypes. However, further wet lab based research using model animals are highly recommended to experimentally validate our findings.Communicated by Ramaswamy H. Sarma.