A highly conserved WDYPKCDRA epitope in the RNA directed RNA polymerase of human coronaviruses can be used as epitope-based universal vaccine design

A multi-epitope based vaccine against the surface proteins expressed in cyst and trophozoite stages of parasite Entamoeba histolytica

Entamoeba histolytica, an anaerobic parasite, infects humans and other primates and causes fatal diseases, such as amebiasis, amebic liver abscesses, and many others. Thousands of people are infected and dying due to the need for a proper protective cure, especially in poor sanitizing regions, such as Latin America, Asia, and Africa. Around 10% of the world population is infected by E. histolytica every year. Consequently, novel preventive approaches are required to eliminate the threats of the parasite. A designed vaccine targeting the exposed proteins that are common between cyst and trophozoite stages of the parasite's life cycle would be an effective way to repress the impact of the parasite. Therefore, an in silico bioinformatics approach was performed to design an effective vaccine targeting surface proteins common between both stages of the parasite's life cycle using B-cell and T-cell epitopes. The epitopes derived from the conserved portions of the proteins and their corresponding isomers specific to the parasite suggested that the vaccine could benefit cross-protection. Furthermore, the three-dimensional structure of the designed vaccine was modelled, refined, and validated using multiple bioinformatics tools. The physiological properties and solubility were also predicted using different algorithmic tools and found to be highly soluble in nature. The vaccine was found interactcted with TLR immune receptors, and the stability was observed via dynamics simulation. Codon optimization and cloning were performed for expression analysis. Immune simulation prediction anticipated significant immune responses with a high IgG and IgM antibodies expression, Th and Tc cells population, B-cell population, memory cells, INF-γ, and IL-2 cytokines. Therefore, the constructed multi-epitope putative vaccine can effectively neutralize the parasite's harmful effects.

Role of artificial intelligence in peptide vaccine design against RNA viruses

RNA viruses have high rate of replication and mutation that help them adapt and change according to their environmental conditions. Many viral mutants are the cause of various severe and lethal diseases. Vaccines, on the other hand have the capacity to protect us from infectious diseases by eliciting antibody or cell-mediated immune responses that are pathogen-specific. While there are a few reviews pertaining to the use of artificial intelligence (AI) for SARS-COV-2 vaccine development, none focus on peptide vaccination for RNA viruses and the important role played by AI in it. Peptide vaccine which is slowly coming to be recognized as a safe and effective vaccination strategy has the capacity to overcome the mutant escape problem which is also being currently faced by SARS-COV-2 vaccines in circulation.Here we review the present scenario of peptide vaccines which are developed using mathematical and computational statistics methods to prevent the spread of disease caused by RNA viruses. We also focus on the importance and current stage of AI and mathematical evolutionary modeling using machine learning tools in the establishment of these new peptide vaccines for the control of viral disease.

HBeAg mediates inflammatory functions of macrophages by TLR2 contributing to hepatic fibrosis

BACKGROUND

We and others have confirmed activation of macrophages plays a critical role in liver injury and fibrogenesis during HBV infection. And we have also proved HBeAg can obviously induce the production of macrophage inflammatory cytokines compared with HBsAg and HBcAg. However, the receptor and functional domain of HBeAg in macrophage activation and its effects and mechanisms on hepatic fibrosis remain elusive.

METHODS

The potentially direct binding receptors of HBeAg were screened and verified by Co-IP assay. Meanwhile, the function domain and accessible peptides of HBeAg for macrophage activation were analyzed by prediction of surface accessible peptide, construction, and synthesis of truncated fragments. Furthermore, effects and mechanisms of the activation of hepatic stellate cells induced by HBeAg-treated macrophages were investigated by Transwell, CCK-8, Gel contraction assay, Phospho Explorer antibody microarray, and Luminex assay. Finally, the effect of HBeAg in hepatic inflammation and fibrosis was evaluated in both human and murine tissues by immunohistochemistry, immunofluorescence, ELISA, and detection of liver enzymes.

RESULTS

Herein, we verified TLR-2 was the direct binding receptor of HBeAg. Meanwhile, C-terminal peptide (122-143 aa.) of core domain in HBeAg was critical for macrophage activation. But arginine-rich domain of HBcAg hided this function, although HBcAg and HBeAg shared the same core domain. Furthermore, HBeAg promoted the proliferation, motility, and contraction of hepatic stellate cells (HSCs) in a macrophage-dependent manner, but not alone. PI3K-AKT-mTOR and p38 MAPK signaling pathway were responsible for motility phenotype of HSCs, while the Smad-dependent TGF-β signaling pathway for proliferation and contraction of them. Additionally, multiple chemokines and cytokines, such as CCL2, CCL5, CXCL10, and TNF-α, might be key mediators of HSC activation. Consistently, HBeAg induced transient inflammation response and promoted early fibrogenesis via TLR-2 in mice. Finally, clinical investigations suggested that the level of HBeAg is associated with inflammation and fibrosis degrees in patients infected with HBV.

CONCLUSIONS

HBeAg activated macrophages via the TLR-2/NF-κB signal pathway and further exacerbated hepatic fibrosis by facilitating motility, proliferation, and contraction of HSCs with the help of macrophages.

An update on emerging therapeutics to combat COVID-19

BACKGROUND

The COVID-19 pandemic has demanded effective therapeutic protocol from researchers and clinicians across the world. Currently, a large amount of primary data have been generated from several preclinical studies. At least 300 clinical trials are underway for drug repurposing against COVID-19; the clinician needs objective evidence-based medication to treat COVID-19.

OBSERVATIONS

Single-stranded RNA viral genome of SARS-CoV-2 encodes structural proteins (spike protein), non-structural enzymatic proteins (RNA-dependent RNA polymerase, helicase, papain-like protease, 3-chymotrypsin-like protease) and other accessory proteins. These four enzymatic proteins on spike protein are rate-limiting steps in viral replications and, therefore, an attractive target for drug development against SARS-CoV-2. In silico and in vitro studies have identified various potential epitomes as candidate sequences for vaccine development. These studies have also revealed potential targets for drug development and drug repurposing against COVID-19. Clinical trials utilizing antiviral drugs and other drugs have given inconclusive results regarding their clinical efficacy and side effects. The need for angiotensin-converting enzyme (ACE-2) inhibitors/angiotensin receptor blockers and corticosteroids has been recommended. Western countries have adopted telemedicine as an alternative to prevent transmission of infection in the population. Currently, no proven, evidence-based therapeutic regimen exists for COVID-19.

CONCLUSION

The COVID-19 pandemic has put tremendous pressure on researchers to evaluate and approve drugs effective against the disease. Well-controlled randomized trials should assess medicines that are not marketed with substantial evidence of safety and efficacy and more emphasis on time tested approaches for drug evaluation.

Vaccine Strategy During the SARS-CoV-2 Pandemic: What School Nurses Need to Know

The National Association of School Nurses supports immunization to reduce the incidence of vaccine-preventable diseases. School nurses have the obligation to discern and understand vaccine strategies to aid in the advocacy and education of their school administrators, faculty, staff, students, and caregivers. Coronavirus disease 2019 (COVID-19) has spread to all continents, and the total number of those infected or immune through effective vaccination is well below the estimated need for herd immunity. To achieve herd immunity against the global outbreak of COVID-19, the rapid development of safe and effective vaccines is essential. Using multiple strategies and vaccine platforms to speed up the vaccine development process will inherently save more lives. Equipped with this knowledge of vaccine strategy, the school nurse can more aptly advocate for the use of the COVID-19 vaccines to move toward herd immunity in their communities.

Prediction and analyses of HLA-II restricted Mycobacterium tuberculosis CD4+ T cell epitopes in the Chinese population

The Bacillus Calmette-Guérin (BCG) vaccine has been used to prevent tuberculosis (TB), but it cannot prevent adults against TB. The Mycobacterium tuberculosis Beijing strain is the most popular strain in China, but no vaccine is designed for the Beijing strain. It is vital to design a multiepitopes-based vaccine against the Beijing strain for the Chinese population. The bioinformatics tools were used to predict CD4+ T-cell epitopes in five protective antigens based on the Chinese population-specific alleles. The antigenicity, allergenicity, toxicity, IFN-γ level, population coverage, and three-dimensional structure were predicted using Vaxijen, AllerTOP, ToxinPred, IFN-γ epitope server, IEDB, and I-TASSER, respectively. One-hundred one promiscuous epitopes were obtained from Rv1813c, Rv2608, Rv3131, and Rv3628 proteins. After screening with antigenicity, allergenicity, toxicity, and IFN-γ level, seven epitopes from Rv2608 and Rv3131 proteins were selected to be vaccine candidates. Further study determined their three-dimensional structure and the coverage in the Chinese population as high as 99%. Our study predicted seven CD4+ T-cell dominant epitopes from the proteins Rv2608 and Rv3131 of M. tuberculosis Beijing strain for the first time, which may provide a basis for improving the design of multiepitopes-based vaccines for TB.

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.

A Highly Conserved Epitope (RNNQIPQDF) of Porcine teschovirus Induced a Group-Specific Antiserum: A Bioinformatics-Predicted Model with Pan-PTV Potential

Porcine teschovirus (PTV) is an OIE-listed pathogen with 13 known PTV serotypes. Heterologous PTV serotypes frequently co-circulate and co-infect with another swine pathogen, causing various symptoms in all age groups, thus highlighting the need for a pan-PTV diagnostic tool. Here, a recombinant protein composed of a highly conserved “RNNQIPQDF” epitope on the GH loop of VP1, predicted in silico, and a tandem repeat of this epitope carrying the pan DR (PADRE) and Toxin B epitopes was constructed to serve as a PTV detection tool. This recombinant GST-PADRE-(RNNQIPQDF)ⁿ-Toxin B protein was used as an immunogen, which effectively raised non-neutralizing or undetectable neutralizing antibodies against PTV in mice. The raised antiserum was reactive against all the PTV serotypes (PTV–1–7) tested, but not against members of the closely related genera Sapelovirus and Cardiovirus, and the unrelated virus controls. This potential pan-PTV diagnostic reagent may be used to differentiate naturally infected animals from vaccinated animals that have antibodies against a subunit vaccine that does not contain this epitope or to screen for PTV before further subtyping. To our knowledge, this is the first report that utilized in silico PTV epitope prediction to find a reagent broadly reactive to various PTV serotypes.

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.

An overview of in silico vaccine design against different pathogens and cancer

INTRODUCTION

Due to overcome the hardness of the vaccine design, computational vaccinology is emerging widely. Prediction of T cell and B cell epitopes, antigen processing analysis, antigenicity analysis, population coverage, conservancy analysis, allergenicity assessment, toxicity prediction, and protein-peptide docking are important steps in the process of designing and developing potent vaccines against various viruses and cancers. In order to perform all of the analyses, several bioinformatics tools and online web servers have been developed. Scientists must take the decision to apply more suitable and precise servers for each part based on their accuracy.

AREAS COVERED

In this review, a wide-range list of different bioinformatics tools and online web servers has been provided. Moreover, some studies were proposed to show the importance of various bioinformatics tools for predicting and developing efficient vaccines against different pathogens including viruses, bacteria, parasites, and fungi as well as cancer.

EXPERT OPINION

Immunoinformatics is the best way to find potential vaccine candidates against different pathogens. Thus, the selection of the most accurate tools is necessary to predict and develop potent preventive and therapeutic vaccines. To further evaluation of the computational and in silico vaccine design, in vitro/in vivo analyses are required to develop vaccine candidates.

Neutralizing antibodies mediate virus-immune pathology of COVID-19

SARS-CoV-2 is a novel beta-coronavirus causing over 200.000 lethal cases within six months of first infecting humans. SARS-CoV-2 causes COVID-19, a form of severe acute respiratory syndrome (SARS). COVID-19 is characterized by two phases: the first resembles the flu with pneumonia, but after about seven or eight days the disease suddenly worsens to a sepsis-like syndrome. It is difficult to explain this virus-immune-pathology sequence from virology or immunology only. This paper hypothesizes that host-produced anti-spike protein antibodies are responsible for immune-induced viral dissemination. Subsequently, systemic distribution of virus-antibodies complexes activates the immune pathology observed in severe COVID-19.

This hypothesis may be counterintuitive to immunologist that consider many anti-spike antibodies to be virus-neutralizing antibodies. Although anti-spike antibodies may hinder infection of epithelial cells, antibody binding to the spike protein may facilitate virus infection of myeloid leukocytes. If myeloid leukocytes reenter the circulation, they could spread the virus from a locoregional infection to a systemic disease. Disseminated virus in combination with antibodies results in dispersed virus-antibody complexes that overstimulate the immune system.

The hypothesis aligns with the sequences of virus, immune and pathological events in COVID-19. The delay in onset from both syndromes results from an immune system still naïve to the non-cross-reactive spike protein. Details of this hypothesis are in concordance with many clinical characteristics of COVID-19, including its predominant lethality for the elderly, and the mostly asymptomatic course of disease in children. It predicts putative detrimental effects of vaccines that induce virus-neutralizing antibodies against the spike protein, as has been shown for other coronaviruses.

This hypothesis has consequences for treatment of patients, evaluation of personal and herd immunity and vaccine development. In patients, cellular immunity should be stimulated. Neutralizing antibodies might not be indicative for immunity. Vaccines should aim to stimulate cellular immunity COVID-19 and/or stimulate humoral immunity against viral proteins except for the immunodominant spike protein.

T-cell Epitope-based Vaccine Design for Nipah Virus by Reverse Vaccinology Approach

AIM AND OBJECTIVE

Nipah virus (NiV) is a zoonotic virus of the paramyxovirus family that sporadically breaks out from livestock and spreads in humans through breathing resulting in an indication of encephalitis syndrome. In the current study, T cell epitopes with the NiV W protein antigens were predicted.

MATERIALS AND METHODS

Modelling of unavailable 3D structure of W protein followed by docking studies of respective Human MHC - class I and MHC - class II alleles predicted was carried out for the highest binding rates. In the computational analysis, epitopes were assessed for immunogenicity, conservation, and toxicity analysis. T - cell-based vaccine development against NiV was screened for eight epitopes of Indian - Asian origin.

RESULTS

Two epitopes, SPVIAEHYY and LVNDGLNII, have been screened and selected for further docking study based on toxicity and conservancy analyses. These epitopes showed a significant score of -1.19 kcal/mol and 0.15 kcal/mol with HLA- B*35:03 and HLA- DRB1 * 07:03, respectively by using allele - Class I and Class II from AutoDock. These two peptides predicted by the reverse vaccinology approach are likely to induce immune response mediated by T - cells.

CONCLUSION

Simulation using GROMACS has revealed that LVNDGLNII epitope forms a more stable complex with HLA molecule and will be useful in developing the epitope-based Nipah virus vaccine.

Epitope-Based Peptide Vaccine against Glycoprotein G of Nipah Henipavirus Using Immunoinformatics Approaches

Background

Nipah belongs to the genus Henipavirus and the Paramyxoviridae family. It is an endemic most commonly found at South Asia and has first emerged in Malaysia in 1998. Bats are found to be the main reservoir for this virus, causing disease in both humans and animals. The last outbreak has occurred in May 2018 in Kerala. It is characterized by high pathogenicity and fatality rates which varies from 40% to 70% depending on the severity of the disease and on the availability of adequate healthcare facilities. Currently, there are no antiviral drugs available for NiV disease and the treatment is just supportive. Clinical presentations for this virus range from asymptomatic infection to fatal encephalitis.

Objective

This study is aimed at predicting an effective epitope-based vaccine against glycoprotein G of Nipah henipavirus, using immunoinformatics approaches.

Methods and Materials

Glycoprotein G of the Nipah virus sequence was retrieved from NCBI. Different prediction tools were used to analyze the epitopes, namely, BepiPred-2.0: Sequential B Cell Epitope Predictor for B cell and T cell MHC classes II and I. Then, the proposed peptides were docked using Autodock 4.0 software program. Results and Conclusions. The two peptides TVYHCSAVY and FLIDRINWI have showed a very strong binding affinity to MHC class I and MHC class II alleles. Furthermore, considering the conservancy, the affinity, and the population coverage, the peptide FLIDRINWIT is highly suitable to be utilized to formulate a new vaccine against glycoprotein G of Nipah henipavirus. An in vivo study for the proposed peptides is also highly recommended.

A Computational Vaccine Designing Approach for MERS-CoV Infections

The aim of this study was to use IEDB software to predict the suitable MERS-CoV epitope vaccine against the most known world population alleles through four selecting proteins such as S glycoprotein and envelope protein and their modification sequences after the pandemic spread of MERS-CoV in 2012. IEDB services is one of the computational methods; the output of this study showed that S glycoprotein, envelope (E) protein, and S and E protein modified sequences of MERS-CoV might be considered as a protective immunogenic with high conservancy because they can elect both neutralizing antibodies and T-cell responses when reacting with B-cell, T-helper cell, and cytotoxic T lymphocyte. NetCTL, NetChop, and MHC-NP were used to confirm our results. Population coverage analysis showed that the putative helper T-cell epitopes and CTL epitopes could cover most of the world population in more than 60 geographical regions. According to AllerHunter results, all those selected different protein showed non-allergen; this finding makes this computational vaccine study more desirable for vaccine synthesis.

Epitope Prediction by Novel Immunoinformatics Approach: A State-of-the-art Review

Immunoinformatics is a science that helps to create significant immunological information using bioinformatics softwares and applications. One of the most important applications of immunoinformatics is the prediction of a variety of specific epitopes for B cell recognition and T cell through MHC class I and II molecules. This method reduces costs and time compared to laboratory tests. In this state-of-the-art review, we review about 50 papers to find the latest and most used immunoinformatic tools as well as their applications for predicting the viral, bacterial and tumoral structural and linear epitopes of B and T cells. In the clinic, the main application of prediction of epitopes is for designing peptide-based vaccines. Peptide-based vaccines are a considerably potential alternative to low-cost vaccines that may reduce the risks related to the production of common vaccines.

Conserved B and T cell epitopes prediction of ebola virus glycoprotein for vaccine development: An immuno-informatics approach

Ebola virus (EBOV), a non-segmented single-stranded RNA virus, is often-most transmitted through body fluids like sweat, tears, saliva, and nasal secretions. Till date, there is no licensed vaccine of EBOV is available in the market; however, the world is increasingly vulnerable to this emerging threat. Hence, it is the need of time to develop a vaccine for EBOV to hinder its dissemination. The current study has been designed for identification and characterization of the potential B and T-cell epitopes using the Immuno-informatics tools, and it helped in finding the potent vaccine candidates against EBOV. Prediction, antigenicity and allergenicity testing of predicted B and T cells' epitopes was done as well to identify their potential as a vaccine candidate and to measure their safety level respectively. Among B-cell epitopes "WIPAGIGVTGVIIA" showed a high antigenicity score and it would play an important role in evoking the immune response. In T-cell epitopes, peptides "AIGLAWIPY" and "IRGFPRCRY" presented high antigenicity score, which binds to MHC class-I and MHC class-II alleles respectively. All predicted epitopes were analyzed and compared with already reported peptides carefully. Comparatively, Peptides predicted in the present study showed more immunogenicity score than already reported peptides, used as positive control, and are more immunogenic as compared to them. Peptides reported in the present study do not target only Zaire EBOV (ZEBOV), as in previous studies, but also other species, i.e. Tai Forest EBOV (TAFV), Sudan EBOV (SUDV), Bundibugyo EBOV (BDBV), and Reston EBOV (RESTV) and would bring the promising results as potent vaccine candidates.

Highly conserved epitopes of DENV structural and non-structural proteins: Candidates for universal vaccine targets

Dengue is a severe emerging arthropod borne viral disease occurring globally. Around two fifths of the world's population, or up to 3.9 billion people, are at a risk of dengue infection. Infection induces a life-long protective immunity to the homologous serotype but confers only partial and transient protection against subsequent infection caused by other serotypes. Thus, there is a need for a vaccine which is capable of providing a life- long protection against all the serotypes of dengue virus. In our study, comparative genomics of Dengue virus (DENV) was conducted to explore potential candidates for novel vaccine targets. From our analysis we successfully found 100% conserved epitopes in Envelope protein (RCPTQGE); NS3 (SAAQRRGR, PGTSGSPI); NS4A (QRTPQDNQL); NS4B (LQAKATREAQKRA) and NS5 proteins (QRGSGQV) in all DENV serotypes. Some serotype specific conserved motifs were also found in NS1, NS5, Capsid, PrM and Envelope proteins. Using comparative genomics and immunoinformatics approach, we could find conserved epitopes which can be explored as peptide vaccine candidates to combat dengue worldwide. Serotype specific epitopes can also be exploited for rapid diagnostics. All ten proteins are explored to find the conserved epitopes in DENV serotypes, thus making it the most extensively studied viral genome so far.

Reverse vaccinology approach to design a novel multi-epitope subunit vaccine against avian influenza A (H7N9) virus

H7N9, a novel strain of avian origin influenza was the first recorded incidence where a human was transited by a N9 type influenza virus. Effective vaccination against influenza A (H7N9) is a major concern, since it has emerged as a life threatening viral pathogen. Here, an in silico reverse vaccinology strategy was adopted to design a unique chimeric subunit vaccine against avian influenza A (H7N9). Induction of humoral and cell-mediated immunity is the prime concerned characteristics for a peptide vaccine candidate, hence both T cell and B cell immunity of viral proteins were screened. Antigenicity testing, transmembrane topology screening, allergenicity and toxicity assessment, population coverage analysis and molecular docking approach were adopted to generate the most antigenic epitopes of avian influenza A (H7N9) proteome. Further, a novel subunit vaccine was designed by the combination of highly immunogenic epitopes along with suitable adjuvant and linkers. Physicochemical properties and secondary structure of the designed vaccine were assessed to ensure its thermostability, h ydrophilicity, theoretical PI and structural behavior. Homology modeling, refinement and validation of the designed vaccine allowed to construct a three dimensional structure of the predicted vaccine, further employed to molecular docking analysis with different MHC molecules and human immune TLR8 receptor present on lymphocyte cells. Moreover, disulfide engineering was employed to lessen the high mobility region of the designed vaccine in order to extend its stability. Furthermore, we investigated the molecular dynamic simulation of the modeled subunit vaccine and TLR8 complexed molecule to strengthen our prediction. Finally, the suggested vaccine was reverse transcribed and adapted for E. coli strain K12 prior to insertion within pET28a(+) vector for checking translational potency and microbial expression.

Bottlenecks in the transmission of porcine reproductive and respiratory syndrome virus (PRRSV1) to naïve pigs and the quasi-species variation of the virus during infection in vaccinated pigs

This paper describes the results of two experiments regarding porcine reproductive and respiratory syndrome virus (PRRSV1): the first one studied the existence of bottlenecks in an experimental one-to-one model of transmission in pigs; while the second analysed the differences between viral quasi-species in vaccinated pigs that developed shorter or longer viraemias after natural challenge. Serum samples, as well as the initial inoculum, were deep-sequenced and a viral quasi-species was constructed per sample. For the first experiment, the results consistently reported a reduction in the quasi-species diversity after a transmission event, pointing to the existence of bottlenecks during PRRSV1 transmission. However, despite the identified preferred and un-preferred transmitted variants not being randomly distributed along the virus genome, it was not possible to identify any variant producing a structural change in any viral protein. In contrast, the mutations identified in GP2, nsp9 and M of the second experiment pointed to changes in the amino acid charges and the viral RNA-dependent RNA polymerase structure. The fact that the affected proteins are known targets of the immunity against PRRSV, plus the differential level of neutralizing antibodies present in pigs developing short or long viraemias, suggests that the immune response selected those changes.

Advances in Designing and Developing Vaccines, Drugs, and Therapies to Counter Ebola Virus

Ebola virus (EBOV), a member of the family Filoviridae, is responsible for causing Ebola virus disease (EVD) (formerly named Ebola hemorrhagic fever). This is a severe, often fatal illness with mortality rates varying from 50 to 90% in humans. Although the virus and associated disease has been recognized since 1976, it was only when the recent outbreak of EBOV in 2014-2016 highlighted the danger and global impact of this virus, necessitating the need for coming up with the effective vaccines and drugs to counter its pandemic threat. Albeit no commercial vaccine is available so far against EBOV, a few vaccine candidates are under evaluation and clinical trials to assess their prophylactic efficacy. These include recombinant viral vector (recombinant vesicular stomatitis virus vector, chimpanzee adenovirus type 3-vector, and modified vaccinia Ankara virus), Ebola virus-like particles, virus-like replicon particles, DNA, and plant-based vaccines. Due to improvement in the field of genomics and proteomics, epitope-targeted vaccines have gained top priority. Correspondingly, several therapies have also been developed, including immunoglobulins against specific viral structures small cell-penetrating antibody fragments that target intracellular EBOV proteins. Small interfering RNAs and oligomer-mediated inhibition have also been verified for EVD treatment. Other treatment options include viral entry inhibitors, transfusion of convalescent blood/serum, neutralizing antibodies, and gene expression inhibitors. Repurposed drugs, which have proven safety profiles, can be adapted after high-throughput screening for efficacy and potency for EVD treatment. Herbal and other natural products are also being explored for EVD treatment. Further studies to better understand the pathogenesis and antigenic structures of the virus can help in developing an effective vaccine and identifying appropriate antiviral targets. This review presents the recent advances in designing and developing vaccines, drugs, and therapies to counter the EBOV threat.

An Immunopharmacoinformatics Approach in Development of Vaccine and Drug Candidates for West Nile Virus

An outbreak of West Nile Virus (WNV) like the recent Ebola can be more epidemic and fatal to public health throughout the world. WNV possesses utmost threat as no vaccine or drug is currently available for its treatment except mosquito control. The current study applied the combined approach of immunoinformatics and pharmacoinformatics to design potential epitope-based vaccines and drug candidates against WNV. By analyzing the whole proteome of 2994 proteins, the WNV envelope glycoprotein was selected as a therapeutic target based on its highest antigenicity. After proper assessment “KSFLVHREW” and “ITPSAPSYT” were found to be the most potential T and B-cell epitopes, respectively. Besides, we have designed and validated four novel drugs from a known WNV inhibitor, AP30451 by adopting computational approaches. Toxicity assessment and drug score confirmed the effectiveness of these drug candidates. This in silico research might greatly facilitate the wet lab experiments to develop vaccine and drug against WNV.

Homology modeling and prediction of B‑cell and T‑cell epitopes of the house dust mite allergen Der f 20

House dust mite allergens can cause allergic diseases, including asthma, atopic dermatitis and rhinitis. Der f 20 is a novel allergen of Dermatophagoides farina (Der f), which is an arginine kinase. In the present study, the B‑cell and T‑cell epitopes of Der f 20 were predicted. The protein attribution, patterns, physicochemical properties and secondary structure of Der f 20 were also predicted. Der f 20 is a member of the ATP:guanido phosphotransferase family and contains a phosphagen kinase pattern. Using homology modeling, the present study constructed a reasonable tertiary structure of Der f 20. Using BcePred, ABCpred, BCPred and BPAP systems, B‑cell epitopes at 20‑25, 41‑49, 111‑118, 131‑141, 170‑174 and 312‑321 were predicted. Using NetMHCIIpan‑3.0 and NetMHCII‑2.2, T‑cell epitopes were predicted at 194‑202, 239‑247 and 274‑282. These results provide a theoretical basis for the design off Der f 20 epitope‑based vaccines.

In silico-based vaccine design against Ebola virus glycoprotein

Ebola virus (EBOV) is one of the lethal viruses, causing more than 24 epidemic outbreaks to date. Despite having available molecular knowledge of this virus, no definite vaccine or other remedial agents have been developed yet for the management and avoidance of EBOV infections in humans. Disclosing this, the present study described an epitope-based peptide vaccine against EBOV, using a combination of B-cell and T-cell epitope predictions, followed by molecular docking and molecular dynamics simulation approach. Here, protein sequences of all glycoproteins of EBOV were collected and examined via in silico methods to determine the most immunogenic protein. From the identified antigenic protein, the peptide region ranging from 186 to 220 and the sequence HKEGAFFLY from the positions of 154-162 were considered the most potential B-cell and T-cell epitopes, correspondingly. Moreover, this peptide (HKEGAFFLY) interacted with HLA-A*32:15 with the highest binding energy and stability, and also a good conservancy of 83.85% with maximum population coverage. The results imply that the designed epitopes could manifest vigorous enduring defensive immunity against EBOV.

Conserved antigenic sites between MERS-CoV and Bat-coronavirus are revealed through sequence analysis

Background

MERS-CoV is a newly emerged human coronavirus reported closely related with HKU4 and HKU5 Bat coronaviruses. Bat and MERS corona-viruses are structurally related. Therefore, it is of interest to estimate the degree of conserved antigenic sites among them. It is of importance to elucidate the shared antigenic-sites and extent of conservation between them to understand the evolutionary dynamics of MERS-CoV.

Results

Multiple sequence alignment of the spike (S), membrane (M), enveloped (E) and nucleocapsid (N) proteins was employed to identify the sequence conservation among MERS and Bat (HKU4, HKU5) coronaviruses. We used various in silico tools to predict the conserved antigenic sites. We found that MERS-CoV shared 30 % of its S protein antigenic sites with HKU4 and 70 % with HKU5 bat-CoV. Whereas 100 % of its E, M and N protein’s antigenic sites are found to be conserved with those in HKU4 and HKU5.

Conclusion

This sharing suggests that in case of pathogenicity MERS-CoV is more closely related to HKU5 bat-CoV than HKU4 bat-CoV. The conserved epitopes indicates their evolutionary relationship and ancestry of pathogenicity.

Electronic supplementary material

The online version of this article (doi:10.1186/s13029-016-0049-7) contains supplementary material, which is available to authorized users.

Two highly similar LAEDDTNAQKT and LTDKIGTEI epitopes in G glycoprotein may be useful for effective epitope based vaccine design against pathogenic Henipavirus

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Computational approaches were used to identify epitopes for vaccine development against Henipavirus.

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The strategy combines B-cell epitope prediction, T-cell epitope prediction, docking simulation assay, and cytotoxicity analysis of the G glycoprotein.

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Two potential epitopes were predicted which may be used for the development of peptide vaccines.

Nipah virus and Hendra virus, two members of the genus Henipavirus, are newly emerging zoonotic pathogens which cause acute respiratory illness and severe encephalitis in human. Lack of the effective antiviral therapy endorses the urgency for the development of vaccine against these deadly viruses. In this study, we employed various computational approaches to identify epitopes which has the potential for vaccine development. By analyzing the immune parameters of the conserved sequences of G glycoprotein using various databases and bioinformatics tools, we identified two potential epitopes which may be used as peptide vaccines. Using different B cell epitope prediction servers, four highly similar B cell epitopes were identified. Immunoinformatics analyses revealed that LAEDDTNAQKT is a highly flexible and accessible B-cell epitope to antibody. Highly similar putative CTL epitopes were analyzed for their binding with the HLA-C 12*03 molecule. Docking simulation assay revealed that LTDKIGTEI has significantly lower binding energy, which bolstered its potential as epitope-based vaccine design. Finally, cytotoxicity analysis has also justified their potential as promising epitope-based vaccine candidate. In sum, our computational analysis indicates that either LAEDDTNAQKT or LTDKIGTEI epitope holds a promise for the development of universal vaccine against all kinds of pathogenic Henipavirus. Further in vivo and in vitro studies are necessary to validate the obtained findings.

Epitope-based peptide vaccine design and target site depiction against Ebola viruses: an immunoinformatics study

Ebola viruses (EBOVs) have been identified as an emerging threat in recent year as it causes severe haemorrhagic fever in human. Epitope‐based vaccine design for EBOVs remains a top priority because a mere progress has been made in this regard. Another reason is the lack of antiviral drug and licensed vaccine although there is a severe outbreak in Central Africa. In this study, we aimed to design an epitope‐based vaccine that can trigger a significant immune response as well as to prognosticate inhibitor that can bind with potential drug target sites using various immunoinformatics and docking simulation tools. The capacity to induce both humoral and cell‐mediated immunity by T cell and B cell was checked for the selected protein. The peptide region spanning 9 amino acids from 42 to 50 and the sequence TLASIGTAF were found as the most potential B and T cell epitopes, respectively. This peptide could interact with 12 HLAs and showed high population coverage up to 80.99%. Using molecular docking, the epitope was further appraised for binding against HLA molecules to verify the binding cleft interaction. In addition with this, the allergenicity of the epitopes was also evaluated. In the post‐therapeutic strategy, docking study of predicted 3D structure identified suitable therapeutic inhibitor against targeted protein. However, this computational epitope‐based peptide vaccine designing and target site prediction against EBOVs open up a new horizon which may be the prospective way in Ebola viruses research; the results require validation by in vitro and in vivo experiments.

Middle East respiratory syndrome: obstacles and prospects for vaccine development

The recent emergence of Middle East respiratory syndrome (MERS) highlights the need to engineer new methods for expediting vaccine development against emerging diseases. However, several obstacles prevent pursuit of a licensable MERS vaccine. First, the lack of a suitable animal model for MERS complicates the in vivo testing of candidate vaccines. Second, due to the low number of MERS cases, pharmaceutical companies have little incentive to pursue MERS vaccine production as the costs of clinical trials are high. In addition, the timeline from bench research to approved vaccine use is 10 years or longer. Using novel methods and cost-saving strategies, genetically engineered vaccines can be produced quickly and cost-effectively. Along with progress in MERS animal model development, these obstacles can be circumvented or at least mitigated.

Middle East respiratory syndrome: An emerging coronavirus infection tracked by the crowd

In 2012 in Jordan, infection by a novel coronavirus (CoV) caused the first known cases of Middle East respiratory syndrome (MERS). MERS-CoV sequences have since been found in a bat and the virus appears to be enzootic among dromedary camels across the Arabian Peninsula and in parts of Africa. The majority of human cases have occurred in the Kingdom of Saudi Arabia (KSA). In humans, the etiologic agent, MERS-CoV, has been detected in severe, mild and influenza-like illness and in those without any obvious signs or symptoms of disease. MERS is often a lower respiratory tract disease associated with fever, cough, breathing difficulties, pneumonia that can progress to acute respiratory distress syndrome, multiorgan failure and death among more than a third of those infected. Severe disease is usually found in older males and comorbidities are frequently present in cases of MERS. Compared to SARS, MERS progresses more rapidly to respiratory failure and acute kidney injury, is more often observed as severe disease in patients with underlying illnesses and is more often fatal. MERS-CoV has a broader tropism than SARS-CoV, rapidly triggers cellular damage, employs a different receptor and induces a delayed proinflammatory response in cells. Most human cases have been linked to lapses in infection prevention and control in healthcare settings, with a fifth of virus detections reported among healthcare workers. This review sets out what is currently known about MERS and the MERS-CoV, summarises the new phenomenon of crowd-sourced epidemiology and lists some of the many questions that remain unanswered, nearly three years after the first reported case.

A comprehensive immunoinformatics and target site study revealed the corner-stone toward Chikungunya virus treatment

Recent concerning facts of Chikungunya virus (CHIKV); a Togaviridae family alphavirus has proved this as a worldwide emerging threat which causes Chikungunya fever and devitalizing arthritis. Despite severe outbreaks and lack of antiviral drug, a mere progress has been made regarding to an epitope-based vaccine designed for CHIKV. In this study, we aimed to design an epitope-based vaccine that can trigger a significant immune response as well as to prognosticate inhibitor that can bind with potential drug target sites by using various immunoinformatics and docking simulation tools. Initially, whole proteome of CHIKV was retrieved from database and perused to identify the most immunogenic protein. Structural properties of the selected protein were analyzed. The capacity to induce both humoral and cell-mediated immunity by T cell and B cell were checked for the selected protein. The peptide region spanning 9 amino acids from 397 to 405 and the sequence YYYELYPTM were found as the most potential B cell and T cell epitopes respectively. This peptide could interact with as many as 19 HLAs and showed high population coverage ranging from 69.50% to 84.94%. By using in silico docking techniques the epitope was further assessed for binding against HLA molecules to verify the binding cleft interaction. In addition with this, the allergenicity of the epitopes was also evaluated. In the post therapeutic strategy, three dimensional structure was predicted along with validation and verification that resulted in molecular docking study to identify the potential drug binding sites and suitable therapeutic inhibitor against targeted protein. Finally, pharmacophore study was also performed in quest of seeing potent drug activity. However, this computational epitope-based peptide vaccine designing and target site prediction against CHIKV opens up a new horizon which may be the prospective way in Chikungunya virus research; the results require validation by in vitro and in vivo experiments.

Receptor-binding domain-based subunit vaccines against MERS-CoV

Development of effective vaccines, in particular, subunit-based vaccines, against emerging Middle East respiratory syndrome (MERS) caused by the MERS coronavirus (MERS-CoV) will provide the safest means of preventing the continuous spread of MERS in humans and camels. This review briefly describes the structure of the MERS-CoV spike (S) protein and its receptor-binding domain (RBD), discusses the current status of MERS vaccine development and illustrates the strategies used to develop RBD-based subunit vaccines against MERS. It also summarizes currently available animal models for MERS-CoV and proposes a future direction for MERS vaccines. Taken together, this review will assist researchers working to develop effective and safe subunit vaccines against MERS-CoV and any other emerging coronaviruses that might cause future pandemics.

Design of an epitope-based peptide vaccine against spike protein of human coronavirus: an in silico approach

Human coronavirus (HCoV), a member of Coronaviridae family, is the causative agent of upper respiratory tract infections and “atypical pneumonia”. Despite severe epidemic outbreaks on several occasions and lack of antiviral drug, not much progress has been made with regard to an epitope-based vaccine designed for HCoV. In this study, a computational approach was adopted to identify a multiepitope vaccine candidate against this virus that could be suitable to trigger a significant immune response. Sequences of the spike proteins were collected from a protein database and analyzed with an in silico tool, to identify the most immunogenic protein. Both T cell immunity and B cell immunity were checked for the peptides to ensure that they had the capacity to induce both humoral and cell-mediated immunity. The peptide sequence from 88–94 amino acids and the sequence KSSTGFVYF were found as the most potential B cell and T cell epitopes, respectively. Furthermore, conservancy analysis was also done using in silico tools and showed a conservancy of 64.29% for all epitopes. The peptide sequence could interact with as many as 16 human leukocyte antigens (HLAs) and showed high cumulative population coverage, ranging from 75.68% to 90.73%. The epitope was further tested for binding against the HLA molecules, using in silico docking techniques, to verify the binding cleft epitope interaction. The allergenicity of the epitopes was also evaluated. This computational study of design of an epitope-based peptide vaccine against HCoVs allows us to determine novel peptide antigen targets in spike proteins on intuitive grounds, albeit the preliminary results thereof require validation by in vitro and in vivo experiments.