A Brief Review of Computer-Assisted Approaches to Rational Design of Peptide Vaccines

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.

Identification and evaluation in-vitro of conserved peptides with high affinity to MHC-I as potential protective epitopes for Newcastle disease virus vaccines

BACKGROUND

Newcastle disease (ND) is a major threat to the poultry industry, leading to significant economic losses. The current ND vaccines, usually based on active or attenuated strains, are only partially effective and can cause adverse effects post-vaccination. Therefore, the development of safer and more efficient vaccines is necessary. Epitopes represent the antigenic portion of the pathogen and their identification and use for immunization could lead to safer and more effective vaccines. However, the prediction of protective epitopes for a pathogen is a major challenge, especially taking into account the immune system of the target species.

RESULTS

In this study, we utilized an artificial intelligence algorithm to predict ND virus (NDV) peptides that exhibit high affinity to the chicken MHC-I complex. We selected the peptides that are conserved across different NDV genotypes and absent in the chicken proteome. From the filtered peptides, we synthesized the five peptides with the highest affinities for the L, HN, and F proteins of NDV. We evaluated these peptides in-vitro for their ability to elicit cell-mediated immunity, which was measured by the lymphocyte proliferation in spleen cells of chickens previously immunized with NDV.

CONCLUSIONS

Our study identified five peptides with high affinity to MHC-I that have the potential to serve as protective epitopes and could be utilized for the development of multi-epitope NDV vaccines. This approach can provide a safer and more efficient method for NDV immunization.

Dengue determinants: Necessities and challenges for universal dengue vaccine development

Dengue illness can range from mild illness to life-threatening haemorrhage. It is an Aedes-borne infectious disease caused by the dengue virus, which has four serotypes. Each serotype acts as an independent infectious agent. The antibodies against one serotype confer homotypic immunity but temporary protection against heterotypic infection. Dengue has become a growing health concern for up to one third of the world's population. Currently, there is no potent anti-dengue medicine, and treatment for severe dengue relies on intravenous fluid management and pain medications. The burden of dengue dramatically increases despite advances in vector control measures. These factors underscore the need for a vaccine. Various dengue vaccine strategies have been demonstrated, that is, live attenuated vaccine, inactivated vaccine, DNA vaccine, subunit vaccine, and viral-vector vaccines, some of which are at the stage of clinical testing. Unfortunately, the forefront candidate vaccine is less than satisfactory, and its performance depends on serostatus and age factors. The lessons from clinical studies depicted ambiguity concerning the efficacy of dengue vaccine. Our study highlighted that viral structural heterogeneity, epitope accessibility, autoimmune complications, genetic variants, genetic diversities, antigen competition, virulence variation, host-pathogen specific interaction, antibody-dependent enhancement, cross-reactive immunity among Flaviviruses, and host-susceptibility determinants not only influence infection outcomes but also hampered successful vaccine development. This review integrates dengue determinants allocated necessities and challenges, which would provide insight for universal dengue vaccine development.

Immunoinformatics approach for designing a universal multiepitope vaccine against Chandipura Virus

Chandipura vesiculovirus (CHPV) is a fast-emerging virus that causes acute encephalitis with a high death rate. Because of its extensive prevalence in African and Asian countries, this infection has become a global hazard, and there is an urgent need to create an effective and non-allergenic vaccine or appropriate treatment to combat it. A vaccine candidate is offered utilizing a computational technique in this study. To build a potential vaccine candidate, viral protein sequences were acquired from the National Center for Biotechnology Information database and evaluated with several bioinformatics techniques to identify B-cell and T-cell epitopes. V1 was shown to be superior in terms of various physicochemical qualities, as well as highly immunogenic and non-allergic. Molecular docking revealed that the CHPV vaccine construct had a greater binding affinity with human Toll-like receptors (TLR-3 and TLR-8) and that it was stable in molecular dynamics simulations. MEC-CHPV was in silico cloned in the pET28a (+) expression vector using codon optimization. The current research identifies potential antigenic epitopes that could be used as vaccine candidates to eradicate the CHPV. This in-silico development of a CHPV vaccine with multiple epitopes could open the path for future rapid laboratory tests.

Current Progress in the Development of Zika Virus Vaccines

Zika virus (ZIKV) is an arbovirus first discovered in the Americas. ZIKV infection is insidious based on its mild clinical symptoms observed after infection. In Brazil, after 2015, ZIKV infection broke out on a large scale, and many infected pregnant women gave birth to babies with microcephaly. The teratogenic effects of the virus on the fetus and its effects on nerves and the immune system have attracted great attention. Currently, no specific prophylactics or therapeutics are clinically available to treat ZIKV infection. Development of a safe and effective vaccine is essential to prevent the rise of any potential pandemic. In this review, we summarize the latest research on Zika vaccine development based on different strategies, including DNA vaccines, subunit vaccines, live-attenuated vaccines, virus-vector-based vaccines, inactivated vaccines, virus-like particles (VLPs), mRNA-based vaccines, and others. We anticipate that this review will facilitate further progress toward the development of effective and safe vaccines against ZIKV infection.

Numerical Characterization of DNA Sequences for Alignment-free Sequence Comparison - A Review

BACKGROUND

Biological macromolecules namely, DNA, RNA, and protein have their building blocks organized in a particular sequence and the sequential arrangement encodes evolutionary history of the organism (species). Hence, biological sequences have been used for studying evolutionary relationships among the species. This is usually carried out by multiple sequence algorithms (MSA). Due to certain limitations of MSA, alignment-free sequence comparison methods were developed. The present review is on alignment-free sequence comparison methods carried out using numerical characterization of DNA sequences. <P> Discussion: The graphical representation of DNA sequences by chaos game representation and other 2-dimesnional and 3-dimensional methods are discussed. The evolution of numerical characterization from the various graphical representations and the application of the DNA invariants thus computed in phylogenetic analysis is presented. The extension of computing molecular descriptors in chemometrics to the calculation of new set of DNA invariants and their use in alignment-free sequence comparison in a N-dimensional space and construction of phylogenetic tress is also reviewed. <P> Conclusion: The phylogenetic tress constructed by the alignment-free sequence comparison methods using DNA invariants were found to be better than those constructed using alignment-based tools such as PHLYIP and ClustalW. One of the graphical representation methods is now extended to study viral sequences of infectious diseases for the identification of conserved regions to design peptide-based vaccine by combining numerical characterization and graphical representation.

Mapping Biomolecular Sequences: Graphical Representations - their Origins, Applications and Future Prospects

The exponential growth in the depositories of biological sequence data have generated an urgent need to store, retrieve and analyse the data efficiently and effectively for which the standard practice of using alignment procedures are not adequate due to high demand on computing resources and time. Graphical representation of sequences has become one of the most popular alignment-free strategies to analyse the biological sequences where each basic unit of the sequences - the bases adenine, cytosine, guanine and thymine for DNA/RNA, and the 20 amino acids for proteins - are plotted on a multi-dimensional grid. The resulting curve in 2D and 3D space and the implied graph in higher dimensions provide a perception of the underlying information of the sequences through visual inspection; numerical analyses, in geometrical or matrix terms, of the plots provide a measure of comparison between sequences and thus enable study of sequence hierarchies. The new approach has also enabled studies of comparisons of DNA sequences over many thousands of bases and provided new insights into the structure of the base compositions of DNA sequences In this article we review in brief the origins and applications of graphical representations and highlight the future perspectives in this field.

Impact of Structural Observables From Simulations to Predict the Effect of Single-Point Mutations in MHC Class II Peptide Binders

The prediction of peptide binders to Major Histocompatibility Complex (MHC) class II receptors is of great interest to study autoimmune diseases and for vaccine development. Most approaches predict the affinities using sequence-based models trained on experimental data and multiple alignments from known peptide substrates. However, detecting activity differences caused by single-point mutations is a challenging task. In this work, we used interactions calculated from simulations to build scoring matrices for quickly estimating binding differences by single-point mutations. We modelled a set of 837 peptides bound to an MHC class II allele, and optimized the sampling of the conformations using the Rosetta backrub method by comparing the results to molecular dynamics simulations. From the dynamic trajectories of each complex, we averaged and compared structural observables for each amino acid at each position of the 9°mer peptide core region. With this information, we generated the scoring-matrices to predict the sign of the binding differences. We then compared the performance of the best scoring-matrix to different computational methodologies that range in computational costs. Overall, the prediction of the activity differences caused by single mutated peptides was lower than 60% for all the methods. However, the developed scoring-matrix in combination with existing methods reports an increase in the performance, up to 86% with a scoring method that uses molecular dynamics.

Topological Analysis for Sequence Variability: Case Study on more than 2K SARS-CoV-2 sequences of COVID-19 infected 54 countries in comparison with SARS-CoV-1 and MERS-CoV

The pandemic due to novel coronavirus, SARS-CoV-2 is a serious global concern now. More than thousand new COVID-19 infections are getting reported daily for this virus across the globe. Thus, the medical research communities are trying to find the remedy to restrict the spreading of this virus, while the vaccine development work is still under research in parallel. In such critical situation, not only the medical research community, but also the scientists in different fields like microbiology, pharmacy, bioinformatics and data science are also sharing effort to accelerate the process of vaccine development, virus prediction, forecasting the transmissible probability and reproduction cases of virus for social awareness. With the similar context, in this article, we have studied sequence variability of the virus primarily focusing on three aspects: (a) sequence variability among SARS-CoV-1, MERS-CoV and SARS-CoV-2 in human host, which are in the same coronavirus family, (b) sequence variability of SARS-CoV-2 in human host for 54 different countries and (c) sequence variability between coronavirus family and country specific SARS-CoV-2 sequences in human host. For this purpose, as a case study, we have performed topological analysis of 2391 global genomic sequences of SARS-CoV-2 in association with SARS-CoV-1 and MERS-CoV using an integrated semi-alignment based computational technique. The results of the semi-alignment based technique are experimentally and statistically found similar to alignment based technique and computationally faster. Moreover, the outcome of this analysis can help to identify the nations with homogeneous SARS-CoV-2 sequences, so that same vaccine can be applied to their heterogeneous human population.

Peptide and peptide-based inhibitors of SARS-CoV-2 entry

To date, no effective vaccines or therapies are available against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pandemic agent of the coronavirus disease 2019 (COVID-19). Due to their safety, efficacy and specificity, peptide inhibitors hold great promise for the treatment of newly emerging viral pathogens. Based on the known structures of viral proteins and their cellular targets, antiviral peptides can be rationally designed and optimized. The resulting peptides may be highly specific for their respective targets and particular viral pathogens or exert broad antiviral activity. Here, we summarize the current status of peptides inhibiting SARS-CoV-2 entry and outline the strategies used to design peptides targeting the ACE2 receptor or the viral spike protein and its activating proteases furin, transmembrane serine protease 2 (TMPRSS2), or cathepsin L. In addition, we present approaches used against related viruses such as SARS-CoV-1 that might be implemented for inhibition of SARS-CoV-2 infection.

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.

B-cell epitope peptide cancer vaccines: a new paradigm for combination immunotherapies with novel checkpoint peptide vaccine

In light of the numerous US FDA-approved humanized monoclonal antibodies (mAbs) for cancer immunotherapy, it is surprising that the advancement of B-cell epitope vaccines designed to elicit a natural humoral polyclonal antibody response has not gained traction in the immune-oncology landscape. Passive immunotherapy with humanized mAbs (Trastuzumab [Herceptin®]; Pertuzumab [Perjeta®]) has provided clinical benefit to breast cancer patients, albeit with significant shortcomings including toxicity problems and resistance, high costs, sophisticated therapeutic regimen and long half-life. The role of B-cell humoral immunity in cancer is under appreciated and underdeveloped. We have advanced the idea of active immunotherapy with chimeric B-cell epitope peptides incorporating a 'promiscuous' T-cell epitope that elicits a polyclonal antibody response, which provides safe, cost-effective therapeutic advantage over mAbs. We have created a portfolio of validated B-cell peptide epitopes against multiple receptor tyrosine kinases (HER-1, HER-3, IGF-1R and VEGF). We have successfully translated two HER-2 combination B-cell peptide vaccines in Phase I and II clinical trials. We have recently developed an effective novel PD-1 vaccine. In this article, I will review our approaches and strategies that focus on B-cell epitope cancer vaccines.

Rational Design of Antigen Incorporation Into Subunit Vaccine Biomaterials Can Enhance Antigen-Specific Immune Responses

Peptide subunit vaccines increase safety by reducing the risk of off-target responses and improving the specificity of the induced adaptive immune response. The immunogenicity of most soluble peptides, however, is often insufficient to produce robust and lasting immunity. Many biomaterials and delivery vehicles have been developed for peptide antigens to improve immune response while maintaining specificity. Peptide nanoclusters (PNC) are a subunit peptide vaccine material that has shown potential to increase immunogenicity of peptide antigens. PNC are comprised only of crosslinked peptide antigen and have been synthesized from several peptide antigens as small as 8 amino acids in length. However, as with many peptide vaccine biomaterials, synthesis requires adding residues to the peptide and/or engaging amino acids within the antigen epitope covalently to form a stable material. The impact of antigen modifications made to enable biomaterial incorporation or formation is rarely investigated, since the goal of most studies is to compare the soluble antigen with biomaterial form of antigen. This study investigates PNC as a platform vaccine biomaterial to evaluate how peptide modification and biomaterial formation with different crosslinking chemistries affect epitope-specific immune cell presentation and activation. Several types of PNC were synthesized by desolvation from the model peptide epitope SIINFEKL, which is derived from the immunogenic protein ovalbumin. SIINFEKL was altered to include extra residues on each end, strategically chosen to enable multiple conjugation chemistry options for incorporation into PNC. Several crosslinking methods were used to control which functional groups were used to stabilize the PNC, as well as the reducibility of the crosslinking. These variations were evaluated for immune responses and biodistribution following in vivo immunization. All modified antigen formulations still induced comparable immune responses when incorporated into PNC compared to unmodified soluble antigen alone. However, some crosslinking methods led to a significant increase in desirable immune responses while others did not, suggesting that not all PNC were processed the same. These results help guide future peptide vaccine biomaterial design, including PNC and a wide variety of conjugated and self-assembled peptide antigen materials, to maximize and tune the desired immune response.

Advancements in prophylactic and therapeutic nanovaccines

Vaccines activate suitable immune responses to fight against diseases but can possess limitations such as compromised efficacy and immunogenic responses, poor stability, and requirement of adherence to multiple doses. ‘Nanovaccines’ have been explored to elicit a strong immune response with the advantages of nano-sized range, high antigen loading, enhanced immunogenicity, controlled antigen presentation, more retention in lymph nodes and promote patient compliance by a lower frequency of dosing. Various types of nanoparticles with diverse pathogenic or foreign antigens can help to overcome immunotolerance and alleviate the need of booster doses as required with conventional vaccines. Nanovaccines have the potential to induce both cell-mediated and antibody-mediated immunity and can render long-lasting immunogenic memory. With such properties, nanovaccines have shown high potential for the prevention of infectious diseases such as acquired immunodeficiency syndrome (AIDS), malaria, tuberculosis, influenza, and cancer. Their therapeutic potential has also been explored in the treatment of cancer. The various kinds of nanomaterials used for vaccine development and their effects on immune system activation have been discussed with special relevance to their implications in various pathological conditions.

Statement of Significance

Interaction of nanoparticles with the immune system has opened multiple avenues to combat a variety of infectious and non-infectious pathological conditions. Limitations of conventional vaccines have paved the path for nanomedicine associated benefits with a hope of producing effective nanovaccines. This review highlights the role of different types of nanovaccines and the role of nanoparticles in modulating the immune response of vaccines. The applications of nanovaccines in infectious and non-infectious diseases like malaria, tuberculosis, AIDS, influenza, and cancers have been discussed. It will help the readers develop an understanding of mechanisms of immune activation by nanovaccines and design appropriate strategies for novel nanovaccines.

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.

Computational Methodology for Peptide Vaccine Design for Zika Virus: A Bioinformatics Approach

With the increasing frequency of viral epidemics, vaccines to augment the human immune response system have been the medium of choice to combat viral infections. The tragic consequences of the Zika virus pandemic in South and Central America a few years ago brought the issues into sharper focus. While traditional vaccine development is time-consuming and expensive, recent advances in information technology, immunoinformatics, genetics, bioinformatics, and related sciences have opened the doors to new paradigms in vaccine design and applications.Peptide vaccines are one group of the new approaches to vaccine formulation. In this chapter, we discuss the various issues involved in the design of peptide vaccines and their advantages and shortcomings, with special reference to the Zika virus for which no drugs or vaccines are as yet available. In the process, we outline our work in this field giving a detailed step-by-step description of the protocol we follow for such vaccine design so that interested researchers can easily follow them and do their own designing. Several flowcharts and figures are included to provide a background of the software to be used and results to be anticipated.

Protein and Peptide Biomaterials for Engineered Subunit Vaccines and Immunotherapeutic Applications

Although vaccines have been the primary defense against widespread infectious disease for decades, there is a critical need for improvement to combat complex and variable diseases. More control and specificity over the immune response can be achieved by using only subunit components in vaccines. However, these often lack sufficient immunogenicity to fully protect, and conjugation or carrier materials are required. A variety of protein and peptide biomaterials have improved effectiveness and delivery of subunit vaccines for infectious, cancer, and autoimmune diseases. They are biodegradable and have control over both material structure and immune function. Many of these materials are built from naturally occurring self-assembling proteins, which have been engineered for incorporation of vaccine components. In contrast, others are de novo designs of structures with immune function. In this review, protein biomaterial design, engineering, and immune functionality as vaccines or immunotherapies are discussed.

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

Elizabethkingia anophelis is an emerging human pathogen causing neonatal meningitis, catheter-associated infections and nosocomial outbreaks with high mortality rates. Besides, they are resistant to most antibiotics used in empirical therapy. In this study, therefore, we used immunoinformatic approaches to design a prophylactic peptide vaccine against E. anophelis as an alternative preventive measure. Initially, cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and linear B-lymphocyte (LBL) epitopes were predicted from the highest antigenic protein. The CTL and HTL epitopes together had a population coverage of 99.97% around the world. Eventually, six CTL, seven HTL, and two LBL epitopes were selected and used to construct a multi-epitope vaccine. The vaccine protein was found to be highly immunogenic, non-allergenic, and non-toxic. Codon adaptation and in silico cloning were performed to ensure better expression within E. coli K12 host system. The stability of the vaccine structure was also improved by disulphide bridging. In addition, molecular docking and dynamics simulation revealed strong and stable binding affinity between the vaccine and toll-like receptor 4 (TLR4) molecule. The immune simulation showed higher levels of T-cell and B-cell activities which was in coherence with actual immune response. Repeated exposure simulation resulted in higher clonal selection and faster antigen clearance. Nevertheless, experimental validation is required to ensure the immunogenic potency and safety of this vaccine to control E. anophelis infection in the future.Communicated by Ramaswamy H. Sarma.

In Silico Design and Immunologic Evaluation of HIV-1 p24-Nef Fusion Protein to Approach a Therapeutic Vaccine Candidate

Background:

Acquired immune deficiency syndrome (HIV/AIDS) has been a major glob-al health concern for over 38 years. No safe and effective preventive or therapeutic vaccine has been developed although many products have been investigated. Computational methods have facilitated vaccine developments in recent decades. Among HIV-1 proteins, p24 and Nef are two suitable targets to provoke the cellular immune response. However, the fusion form of these two proteins has not been analyzed in silico yet.

Objective:

This study aimed at the evaluation of possible fusion forms of p24 and Nef in order to achieve a potential therapeutic subunit vaccine against HIV-1.

Method:

In this study, various computational approaches have been applied to predict the most effec-tive fusion form of p24-Nef including CTL (Cytotoxic T lymphocytes) response, immunogenicity, conservation and population coverage. Moreover, binding to MHC (Major histocompatibility com-plex) molecules was assessed in both human and BALB/c.

Results:

After analyzing six possible fusion protein forms using AAY linker, we came up with the most practical form of p24 from 80 to 231 and Nef from 120 to 150 regions (according to their refer-ence sequence of HXB2 strain) using an AAY linker, based on their peptides affinity to MHC mole-cules which are located in a conserved region among different virus clades. The selected fusion protein contains seventeen MHC I antigenic epitopes, among them KRWIILGLN, YKRWIILGL, DIAG-TTSTL and FPDWQNYTP are fully conserved between the virus clades. Furthermore, analyzed class I CTL epitopes showed greater affinity binding to HLA-B 57*01, HLA-B*51:01 and HLA-B 27*02 molecules. The population coverage with the rate of >70% coverage in the Persian population supports this truncated form as an appropriate candidate against HIV-I virus.

Conclusion:

The predicted fusion protein, p24-AAY-Nef in a truncated form with a high rate of T cell epitopes and high conservancy rate among different clades, provides a helpful model for developing a therapeutic vaccine candidate against HIV-1.

Predicting the Affinity of Peptides to Major Histocompatibility Complex Class II by Scoring Molecular Dynamics Simulations

Predicting the binding affinity of peptides able to interact with major histocompatibility complex (MHC) molecules is a priority for researchers working in the identification of novel vaccines candidates. Most available approaches are based on the analysis of the sequence of peptides of known experimental affinity. However, for MHC class II receptors, these approaches are not very accurate, due to the intrinsic flexibility of the complex. To overcome these limitations, we propose to estimate the binding affinity of peptides bound to an MHC class II by averaging the score of the configurations from finite-temperature molecular dynamics simulations. The score is estimated for 18 different scoring functions, and we explored the optimal manner for combining them. To test the predictions, we considered eight peptides of known binding affinity. We found that six scoring functions correlate with the experimental ranking of the peptides significantly better than the others. We then assessed a set of techniques for combining the scoring functions by linear regression and logistic regression. We obtained a maximum accuracy of 82% for the predicted sign of the binding affinity using a logistic regression with optimized weights. These results are potentially useful to improve the reliability of in silico protocols to design high-affinity binding peptides for MHC class II receptors.

Towards the first multi-epitope recombinant vaccine against Crimean-Congo hemorrhagic fever virus: A computer-aided vaccine design approach

Crimean-Congo hemorrhagic fever (CCHF) is considered one of the major public health concerns with case fatality rates of up to 80%. Currently, there is no effective approved vaccine for CCHF. In this study, we used a computer-aided vaccine design approach to develop the first multi-epitope recombinant vaccine for CCHF. For this purpose, linear B-cell and T-cell binding epitopes from two structural glycoproteins of CCHF virus including Gc and Gn were predicted. The epitopes were further studied regarding their antigenicity, allergenicity, hydrophobicity, stability, toxicity and population coverage. A total number of seven epitopes including five T-cell and two B-cell epitopes were screened for the final vaccine construct. Final vaccine construct composed of 382 amino acid residues which were organized in four domains including linear B-cell, T-cell epitopes and cholera toxin B-subunit (CTxB) along with heat labile enterotoxin IIc B subunit (LT-IIc) as adjuvants. All the segments were joined using appropriate linkers. The physicochemical properties as well as the presence of IFN-γ inducing epitopes in the proposed vaccine, was also checked to determining the vaccine stability, solubility and its ability to induce cell-mediated immune responses. The 3D structure of proposed vaccine was subjected to the prediction of computational B-cell epitopes and molecular docking studies with MHC-I and II molecules. Furthermore, molecular dynamics stimulations were performed to study the vaccine-MHCs complexes stability during stimulation time. The results suggest that our proposed vaccine was stable, well soluble in water and potentially antigenic. Results also demonstrated that the vaccine can induce both humoral and cell-mediated immune responses and could serve as a promising anti-CCHF vaccine candidate.

Identification of relevant regions on structural and nonstructural proteins of Zika virus for vaccine and diagnostic test development: an in silico approach

Zika virus (ZIKV) is an arbovirus belonging to the Flaviviridae family and the genus Flavivirus. Infection with ZIKV causes a mild, self-limiting febrile illness called Zika fever. However, ZIKV infection has been recently associated with microcephaly and Guillain-Barré syndrome. Vaccines for the disease are a high priority of World Health Organization. Several studies are currently being conducted to develop a vaccine against ZIKV, but until now there is no licensed ZIKV vaccine. This study used a novel immunoinformatics approach to identify potential T-cell immunogenic epitopes present in the structural and nonstructural proteins of ZIKV. Fourteen T-cell candidate epitopes were identified on ZIKV structural and nonstructural proteins: pr^36-50; C^61-75; C^103-117; E^374-382; E^477-491; NS2a^90-104; NS2a^174-188; NS2a^179-193; NS2a^190-204; NS2a^195-209; NS2a^200-214; NS3^175-189; and NS4a^82-96; NS4a^99-113. Among these epitopes, only E^374-382 is a human leukocyte antigen (HLA) type I restricted epitope. All identified epitopes showed a low similarity with other important flaviviruses but had a high conservation rate among the ZIKV strains and a high population coverage rate. Therefore, these predicted T-cell epitopes are potential candidates targets for development of vaccines to prevent ZIKV infection.

Vaccine Target Discovery

With the rise in novel infectious agents and disease pandemics, a new era of vaccine discovery is necessary. To address this, the new field of immunomics is described, which is synergistically powered by integrating bioinformatics methodologies with technological advances in biology and high-throughput instrumentation. By incorporating biological data from immunology and molecular biology with current genomics and proteomics, immunomics is geared to deliver an insight into immune function, optimal stimulation of immune responses and precise mapping and rational selection of immune targets that cover antigenic diversity. These efforts are expected to contribute towards the development of new generation of vaccines, tailored to both the genetic make-up of the human population and of the pathogen. Vaccine technologies are also being explored for prevention or control of non-communicable diseases.

Bioinformatics in Design of Antiviral Vaccines

Viral diseases and epidemics are occurring across the world with increasing frequency and with incidences of new and old viruses with renewed vigor. Traditional drugs and vaccines with their long developmental times, incidences of allergenic reactions, growth of resistant strains and other issues are proving inadequate to curb the menace. Advancements in computer science and technology, in genetics and immunology and the growth of the new science of bioinformatics are leading to a more focused approach in a new paradigm of vaccine design that challenges the traditional approach and promises to be more effective; lead times should get much shorter, preselection of peptide antivirals will be designed to preclude allergenic reactions, stability against mutational changes to viral strains will be much more assured, and coverage of immunological status will enable community-specific vaccines development. We outline in this article the basics of viruses, immune responses, and traditional vaccines and move on to describe the bioinformatics methods and development of new vaccines.

Design and testing of a highly conserved human rotavirus VP8* immunogenic peptide with potential for vaccine development

Rotavirus infection of young children particularly below five years of age resulting in severe diarhoea, is the cause of a large number of infant deaths all over the world, more so in developing countries like India. Vaccines developed against this infection in the last two decades have shown mixed results with some of them leading to complications. Oral vaccines have not been very effective in India. Significant diversity has been found in circulating virus strains in India. Development of a vaccine against diverse genetic variants of the different strains would go a long way in reducing the incidence of infection in developing countries. Success of such a vaccine would depend to a large extent on the antigenic peptide to be used in antibody production. The non-glycosylated protein VP4 on the surface capsid of the virus is important in rota viral immunogenicity and the major antigenic site(s) responsible for neutralization of the virus via VP4 is in the VP8* subunit of VP4. It is necessary that the peptide should be very specific and a peptide sequence which would stimulate both the T and B immunogenic cells would provide maximum protection against the virus. Advanced computational techniques and existing databases of sequences of the VP4 protein of rotavirus help in identification of such specific sequences. Using an in silico approach we have identified a highly conserved VP8* subunit of the VP4 surface protein of rotavirus which shows both T and B cell processivity and is also non-allergenic. This sub-unit could be used in in vivo models for induction of antibodies.

Analysis of epitope-based vaccine candidates against the E antigen of the hepatitis B virus based on the B genotype sequence: An in silico and in vitro approach

Chronic hepatitis B virus infection is a worldwide health problem with no current effective strategy to achieve a cure. The Hepatitis B virus (HBV) E antigen (HBeAg) has a negative effect on the immune system and a therapeutic vaccine is a promising strategy in order to treat chronic virus infection. In this study, we analyzed and identified the MHC-I, MHC-II and B cell epitopes of the HBeAg based on a B genotype sequence of HBV using a bioinformatic approach and in vitro experiments. The computational approach provided us with four epitopes (LLWFHISCL, YLVSFGVWI, MQLFHLCLI, TVLEYLVSF) of the specific MHC-I allele HLA-A0201 that conformed to all criteria. Molecular docking and a peptide binding assay showed that epitope TVLEYLVSF had the lowest binding energy and epitope LLWFHISCL had the highest binding affinity to the HLA-A0201 molecule. An interferonγenzyme-linked immunospot assay and cytotoxicity assay revealed that epitope LLWFHISCL had the highest ability to induce and stimulate T cells. Furthermore, we determined four core peptides of MHC-II epitopes and a region of the B cell epitope. The epitopes and region identified in this research may be helpful in designing epitope-based vaccines and boosting the mechanism research of HBeAg and its effect on the immune system.

Evaluation of the efficacy of a novel porcine circovirus type 2 synthetic peptide vaccine

A novel porcine circovirus type 2 (PCV2) peptide vaccine comprised of a consensus capsid (Cap) protein domain encoded by open reading frame 2 was developed to control PCV2 infection. The efficacy of the vaccine was evaluated against a commercial baculovirus-expressed recombinant PCV2 subunit vaccine based on the Cap protein. The amino acid sequence of this Cap protein was designed based on the alignment of amino acid sequences from different isolates from Europe, North America, and Asia. The vaccine was evaluated in either phosphate-buffered saline or adjuvanted with aluminum hydroxide, cobalt oxide, or liposome. Overall the PCV2 peptide vaccine was less efficacious against PCV2 challenge compared with the commercial PCV2 vaccine. The peptide vaccine was the most efficacious when liposome was used as an adjuvant, significantly (P < 0.05) reducing viremia while increasing the levels of neutralizing antibodies and interferon-γ secreting cells. This suggests, in the presence of liposome, the peptide vaccine was able to elicit both humoral and cellular immune responses.

Ghost probiotics with a combined regimen: a novel therapeutic approach against the Zika virus, an emerging world threat

The Zika virus (ZIKV) used to be an obscure flavivirus closely related to dengue virus (DENV). Transmission of this epidemic pathogen occurs mainly via mosquitoes, but it is also capable of placental and sexual transmission. Although the characteristics of these viruses are well defined, infections are unpredictable in terms of disease severity, unusual clinical manifestations, unexpected methods of transmission, long-term persistence, and the development of new strains. Recently, ZIKV has gained huge medical attention following the large-scale epidemics around the world, and reported cases of congenital abnormalities associated with Zika virus infections which have created a public health emergency of international concern. Despite continuous research on ZIKV, no specific treatment or vaccine has been developed, excepting a preventive strategy for congenital ZIKV infection. Probiotics, known as GRAS, are bacteria that confer various health beneficial effects, and have been shown to be effective at curing a number of viral diseases by modulating the immune system. Furthermore, probiotic preparations consisting of dead cells and cellular metabolites, so-called "Ghost probiotics", can also act as biological response modifiers. Here, we review available information on the epidemiology, transmission, and clinical features of ZIKV, and on treatment and prevention strategies. In addition, we emphasize the use of probiotics and plant-based natural remedies and describe their action mechanisms, and the green technologies for microbial conversion, which could contribute to the development of novel therapies that may reduce the pathogenicity of ZIKV. Accordingly, we draw attention to new findings, unanswered questions, unresolved issues, and controversies regarding ZIKV.

A Bioinformatics approach to designing a Zika virus vaccine

The Zika virus infections have reached epidemic proportions in the Latin American countries causing severe birth defects and neurological disorders. While several organizations have begun research into design of prophylactic vaccines and therapeutic drugs, computer assisted methods with adequate data resources can be expected to assist in these measures to reduce lead times through bioinformatics approaches. Using 60 sequences of the Zika virus envelope protein available in the GenBank database, our analysis with numerical characterization techniques and several web based bioinformatics servers identified four peptide stretches on the Zika virus envelope protein that are well conserved and surface exposed and are predicted to have reasonable epitope binding efficiency. These peptides can be expected to form the basis for a nascent peptide vaccine which, enhanced by incorporation of suitable adjuvants, can elicit immune response against the Zika virus infections.

In silico analyses of heat shock protein 60 and calreticulin to designing a novel vaccine shifting immune response toward T helper 2 in atherosclerosis

Recent experiments demonstrated that atherosclerosis is a Th1 dominant autoimmune condition, whereas Th2 cells are rarely detected within the atherosclerotic lesions. Several studies have indicated that Th2 type cytokines could be effective in the reduction and stabilization of atherosclerotic plaque. Therefore, the modulation of the adaptive immune response by shifting immune responses toward Th2 cells by a novel vaccine could represent a promising approach to prevent from progression and thromboembolic events in coronary artery disease. In the present study, an in silico approach was applied to design a novel multi-epitope vaccine to elicit a desirable immune response against atherosclerosis. Six novel IL-4 inducing epitopes were selected from HSP60 and calreticulin proteins. To enhance epitope presentation, IL-4 inducing epitopes were linked together by AAY and HEYGAEALERAG linkers. In addition, helper epitopes selected from Tetanus toxin fragment C (TTFrC) were applied to induce CD4+ helper T lymphocytes (HTLs) responses. Moreover, cholera toxin B (CTB) was employed as an adjuvant. A multi-epitope construct was designed based on predicted epitopes which was 320 residues in length. Then, the physico-chemical properties, secondary and tertiary structures, stability, intrinsic protein disorder, solubility and allergenicity of this chimeric protein were analyzed using bioinformatics tools and servers. Based on bioinformatics analysis, a soluble, and non-allergic protein with 35.405kDa molecular weight was designed. Expasy ProtParam classified this chimeric protein as a stable protein. In addition, predicted epitopes in the chimeric vaccine indicated strong potential to induce B-cell mediated immune response and shift immune responses toward protective Th2 immune response. Various in silico analyses indicate that this vaccine is a qualified candidate for improvement of atherosclerosis by inducing immune responses toward T helper 2.

Data Analysis in Chemistry and Bio-Medical Sciences

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