Designing a Fusion Protein Vaccine Against HCV: An In Silico Approach

Investigation of therapeutic potential of the Il24-p20 fusion protein against breast cancer: an in-silico approach

Targeted delivery of therapeutic anticancer chimeric molecules enhances drug efficacy. Numerous studies have focused on developing novel treatments by employing cytokines, particularly interleukins, to inhibit the growth of cancer cells. In the present study, we fused interleukin 24 with the tumor-targeting peptide P20 through a rigid linker to selectively target cancer cells. The secondary structure, tertiary structure, and physicochemical characteristics of the constructed chimeric IL-24-P20 protein were predicted by using bioinformatics tools. In-silico analysis revealed that the fusion construct has a basic nature with 175 amino acids and a molecular weight of 20 kDa. By using the Rampage and ERRAT2 servers, the validity and quality of the fusion protein were evaluated. The results indicated that 93% of the chimeric proteins contained 90.1% of the residues in the favoured region, resulting in a reliable structure. Finally, docking and simulation studies were conducted via ClusPro and Desmond Schrödinger, respectively. Our results indicate that the constructed fusion protein exhibits excellent quality, interaction capabilities, validity, and stability. These findings suggest that the fusion protein is a promising candidate for targeted cancer therapy.

Immunoinformatic approach to design an efficient multi-epitope peptide vaccine against melanoma

Melanoma is known to be the most hazardous and life-threatening type of skin cancer. Although numerous treatments have been authorized in recent years, they often result in severe side effects and may not fully cure the disease. To combat this issue, immunotherapy has emerged as a promising approach for the prevention and treatment of melanoma. Specifically, the use of epitope melanoma vaccine, a subset of immunotherapy, has recently gained attention. The aim of this study was to create a multi-epitope melanoma vaccine using immunoinformatic methods. Two well-known antigens, NYESO-1 and MAGE-C2, were selected due to their strong immunogenicity and high expression in melanoma. To enhance the immunogenicity of the peptide vaccine, Brucella cell-surface protein 31 (BCSP31), the G5 domain of resuscitation-promoting factor B (RpfB) adjuvants, and the helper epitope of pan HLADR-binding epitope (PADRE) were incorporated to vaccine construct. These different segments were connected with suitable linkers and the resulting vaccine structure was evaluated for its physicochemical, structural, and immunological properties using computational tools. The designed vaccine was found to have satisfactory allergenicity, antigenicity, and physicochemical parameters. Additionally, a high-quality tertiary structure of the vaccine was achieved through modeling, refinement, and validation. Docking and molecular dynamics studies showed that the vaccine had a stable and appropriate interaction with the cognate TLR2 and TLR4 receptors during the simulation period. Finally, in silico immune simulation analysis revealed a significant increase in the levels of helper and cytotoxic T cells, as well as the cytokines interferon-gamma and interleukin-2, after repeated exposure to the melanoma vaccine. These results suggest that the designed vaccine has the potential to be an effective therapeutic option for melanoma. However, additional in vitro and in vivo validations are crucial to assess real-world efficacy and safety.

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

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

Immunoinformatic Design of a Multivalent Peptide Vaccine Against Mucormycosis: Targeting FTR1 Protein of Major Causative Fungi

Mucormycosis is a potentially fatal illness that arises in immunocompromised people due to diabetic ketoacidosis, neutropenia, organ transplantation, and elevated serum levels of accessible iron. The sudden spread of mucormycosis in COVID-19 patients engendered massive concern worldwide. Comorbidities including diabetes, cancer, steroid-based medications, long-term ventilation, and increased ferritin serum concentration in COVID-19 patients trigger favorable fungi growth that in turn effectuate mucormycosis. The necessity of FTR1 gene-encoded ferrous permease for host iron acquisition by fungi has been found in different studies recently. Thus, targeting the transit component could be a potential solution. Unfortunately, no appropriate antifungal vaccine has been constructed as of yet. To date, mucormycosis has been treated with antiviral therapy and surgical treatment only. Thus, in this study, the FTR1 protein has been targeted to design a convenient and novel epitope-based vaccine with the help of immunoinformatics against four different virulent fungal species. Furthermore, the vaccine was constructed using 8 CTL, 2 HTL, and 1 LBL epitopes that were found to be highly antigenic, non-allergenic, non-toxic, and fully conserved among the fungi under consideration. The vaccine has very reassuring stability due to its high pI value of 9.97, conclusive of a basic range. The vaccine was then subjected to molecular docking, molecular dynamics, and immune simulation studies to confirm the biological environment’s safety, efficacy, and stability. The vaccine constructs were found to be safe in addition to being effective. Finally, we used in-silico cloning to develop an effective strategy for vaccine mass production. The designed vaccine will be a potential therapeutic not only to control mucormycosis in COVID-19 patients but also be effective in general mucormycosis events. However, further in vitro, and in vivo testing is needed to confirm the vaccine’s safety and efficacy in controlling fungal infections. If successful, this vaccine could provide a low-cost and effective method of preventing the spread of mucormycosis worldwide.

Designing a novel E2-IFN-γ fusion protein against CSFV by immunoinformatics and structural vaccinology approaches

Subunit vaccines with high purity and safety are gradually becoming a main trend in vaccinology. However, adjuvants such as interferon-gamma (IFN-γ) are required to enhance immune responses of subunit vaccines due to their poor immunogenicity. The conjugation of antigen with adjuvant can induce more potent immune responses compared to the mixture of antigen and adjuvant. At the same time, the selection of linker, indispensable in the construction of the stable and bioactive fusion proteins, is complicated and time-consuming. The development of immunoinformatics and structural vaccinology approaches provides a means to address the abovementioned problem. Therefore, in this study, a E2-IFN-γ fusion protein with an optimal linker (E2-R2-PIFN) was designed by bioinformatics approaches to improve the immunogenicity of the classical swine fever virus (CSFV) E2 subunit vaccine. Moreover, the E2-R2-PIFN fusion protein was expressed in HEK293T cells and the biological effects of IFN-γ in E2-R2-PIFN were confirmed in vitro via Western blotting. Here, an alternative method is utilized to simplify the design and validation of the antigen-adjuvant fusion protein, providing a potential subunit vaccine candidate against CSFV. KEY POINTS: • An effective and simple workflow of antigen-adjuvant fusion protein design and validation was established by immunoinformatics and structural vaccinology. • A novel E2-IFN-γ fusion protein with an optimal linker was designed as a potential CSFV vaccine. • The bioactivity of the newly designed fusion protein was preliminarily validated through in vitro experiments.

A Novel Multi-Epitope Edible Vaccine Candidate for Newcastle Disease Virus: In Silico Approach

Background

Newcastle disease, is one of the most important illnesses in the aviculture industry which shows a constant threat. In this case, the vaccine could be considered an important solution to prevent and control this disease. So, the development of a new and more effective vaccine against Newcastle disease is an urgent need. Immune informatics is an important field that provides insight into the experimental procedure and could facilitate the analysis of large amounts of immunological data generated by experimental research and help to design a new vaccine candidate.

Objectives

This study is aimed at bioinformatics to investigate and select the most immunogenic and conserved epitopes derived from F and HN glycoproteins, which play a key role in pathogenesis and immunity. This strategy could cover a wide range of Newcastle disease viruses.

Materials and Method

For expression in both E. coli (as an injectable recombinant vaccine candidate) and maize plant (as an edible vaccine candidate) host, two constructs were designed and analyzed separately. Furthermore, the role of LTB as an effective bio-adjuvant for general eliciting of the immune system and simultaneous expressions with those two antigens was evaluated. Hence, here a multimeric recombinant protein with the abbreviation LHN2F from the highly immunogenic part of HN, F and LTB proteins were designed. The synthetic construct was analyzed based on different bioinformatics tools.

Results

The proper immunogenicity and stability of this multimeric fusion protein have been shown by immunoinformatic methods from various servers. To confirm the function of the designed protein, the final molecule was docked to chicken MHC class I using the Pyrex-python 0.8 program. the results of Immune Epitope analysis were confirmed by the docking results between protein and receptor.

Conclusions

‎The results of structural and immunological computational studies proposed that the protein deduced from this novel construct could act as a vaccine candidate for Newcastle disease virus‎ control and prophylactic.

An alphavirus-derived self-amplifying mRNA encoding PpSP15-LmSTI1 fusion protein for the design of a vaccine against leishmaniasis

The main aims of the present study were to design a fusion protein of Leishmania major stress-inducible protein 1 (LmSTI1) and Phlebotomus papatasi SP15 (PpSP15), and to express it in the form of alphavirus packaged Self-amplifying mRNA (SAM). Two combinations, PpSP15-LmSTI1 and LmSTI1-PpSP15 fusion forms, were analyzed for folding and minimum free energies of the mRNA. Conformational studies on 3D modeled fusion and native forms were performed, and the Root-Mean-Square-distance (RMSD) of the Cα atomic coordinates were calculated. Antigenicity and stability were predicted using bioinformatics tools. The coding sequences of PpSP15-LmSTI1 fusion, PpSP15, and LmSTI1 were cloned into an alphavirus-based vector and used to produce the SAM constructs. All the subcloned constructs were then subjected to packaging in the form of viral replicon particles (VRPs),and were evaluated for their ability to infect BHK-21 cells and express the recombinant fusion proteins. The in-silico analysis indicated that the PpSP15-LmSTI1 combination could be a promising candidate based on lower folding ΔG of mRNA, higher protein antigenicity and lower instability indexes, and less conformational changes compared to the native proteins and the LmSTI1-PpSP15 fusion form. Packaged SAM encoding fusion and native antigens are used for infection of mammalian cells and for recombinant protein expression. This is the first study on in silico designing and successful packaging of an alphavirus-derived SAM in the form of the VRPs to target leishmaniasis.

Prediction and evaluation of multi epitope based sub-unit vaccine against Salmonella typhimurium

Salmonella enteric serovar Typhimurium is the most common enteric pathogen in humans and animals. Consumption of contaminated food or water triggers inflammation that allows Salmonella to spread into the gut and causes gastrointestinal diseases. The infection spreads by intestinal invasion, phagocyte internalization and subsequent dissemination in many other patients. This research used TolA, a Salmonella typhimurium membrane protein, to computationally design a multi-epitope vaccine against the pathogen. Complete consistency of the candidate vaccine was checked In silico, and molecular dynamics simulations confirmed the vaccine's stability. According to docking report, the vaccine has a good affinity with toll-like receptors. In silico cloning and codon optimization techniques improved the vaccine's efficacy in Salmonella typhimurium manifestation process. The candidate vaccine induced an efficient immune response, as determined by In silico immune simulation. Computational studies revealed that the engineered multi-epitope vaccine is structurally stable, capable of eliciting particular immunological reactions, and therefore a candidate for a latent Salmonella typhimurium vaccine. However, wet lab studies and further investigations are required to confirm the results.

Designing multiepitope-based vaccine against Eimeria from immune mapped protein 1 (IMP-1) antigen using immunoinformatic approach

Drug resistance against coccidiosis has posed a significant threat to chicken welfare and productivity worldwide, putting daunting pressure on the poultry industry to reduce the use of chemoprophylactic drugs and live vaccines in poultry to treat intestinal diseases. Chicken coccidiosis, caused by an apicomplexan parasite of Eimeria spp., is a significant challenge worldwide. Due to the experience of economic loss in production and prevention of the disease, development of cost-effective vaccines or drugs that can stimulate defence against multiple Eimeria species is imperative to control coccidiosis. This study explored Eimeria immune mapped protein-1 (IMP-1) to develop a multiepitope-based vaccine against coccidiosis by identifying antigenic T-cell and B-cell epitope candidates through immunoinformatic techniques. This resulted in the design of 7 CD8⁺, 21 CD4⁺ T-cell epitopes and 6 B-cell epitopes, connected using AAY, GPGPG and KK linkers to form a vaccine construct. A Cholera Toxin B (CTB) adjuvant was attached to the N-terminal of the multiepitope construct to improve the immunogenicity of the vaccine. The designed vaccine was assessed for immunogenicity (8.59968), allergenicity and physiochemical parameters, which revealed the construct molecular weight of 73.25 kDa, theoretical pI of 8.23 and instability index of 33.40. Molecular docking simulation of vaccine with TLR-5 with binding affinity of - 151.893 kcal/mol revealed good structural interaction and stability of protein structure of vaccine construct. The designed vaccine predicts the induction of immunity and boosted host's immune system through production of antibodies and cytokines, vital in hindering surface entry of parasites into host. This is a very important step in vaccine development though further experimental study is still required to validate these results.

In silico designing of vaccine candidate against Clostridium difficile

Clostridium difficile is a spore-forming gram-positive bacterium, recognized as the primary cause of antibiotic-associated nosocomial diarrhoea. Clostridium difficile infection (CDI) has emerged as a major health-associated infection with increased incidence and hospitalization over the years with high mortality rates. Contamination and infection occur after ingestion of vegetative spores, which germinate in the gastro-intestinal tract. The surface layer protein and flagellar proteins are responsible for the bacterial colonization while the spore coat protein, is associated with spore colonization. Both these factors are the main concern of the recurrence of CDI in hospitalized patients. In this study, the CotE, SlpA and FliC proteins are chosen to form a multivalent, multi-epitopic, chimeric vaccine candidate using the immunoinformatics approach. The overall reliability of the candidate vaccine was validated in silico and the molecular dynamics simulation verified the stability of the vaccine designed. Docking studies showed stable vaccine interactions with Toll‐Like Receptors of innate immune cells and MHC receptors. In silico codon optimization of the vaccine and its insertion in the cloning vector indicates a competent expression of the modelled vaccine in E. coli expression system. An in silico immune simulation system evaluated the effectiveness of the candidate vaccine to trigger a protective immune response.

Designing of a Novel Fusion Protein Vaccine Candidate Against Human Visceral Leishmaniasis (VL) Using Immunoinformatics and Structural Approaches

Leishmaniasis is caused by an obligate intracellular protozoan parasite. The clinical forms of leishmaniasis differ from cutaneous leishmaniasis, mucocutaneous leishmaniasis and visceral leishmaniasis (VL) which depend on the parasite species and the host's immune responses. There are significant challenges to the available anti-leishmanial drug therapy, particularly in severe forms of disease, and the rise of drug resistance has made it more difficult. Currently, no licensed vaccines have been introduced to the market for the control and elimination of VL. A potential target for use in candidate vaccines against leishmaniasis has been shown to be leishmania Kinetoplastid membrane protein-11 (KMP-11) antigen. In this study, we chose KMP-11 antigen as target antigen in our vaccine construct. In addition, B-type flagellin (fliC) was used as an adjuvant for enhancing vaccine immunogenicity. The GSGSGSGSGSG linker was applied to link the KMP-11 antigen and fliC (KMP-11-fliC) to construct our fusion protein. Bioinformatics approaches such as; 3D homology modeling, CTL, B-cell, MHC class I and II epitopes prediction, allergenicity, antigenicity evaluations, molecular docking, fast simulations of flexibility of docked complex and in silico cloning were employed to analysis and evaluation of various properties of the designed fusion construct. Computational results showed that our engineered structure has the potential for proper stimulation of cellular and humoral immune responses against VL. Consequently, it could be proposed as a candidate vaccine against VL according to these data and after verifying the efficacy of the candidate vaccine through in vivo and in vitro immunological tests.

Immunoinformatics analysis to design novel epitope based vaccine candidate targeting the glycoprotein and nucleoprotein of Lassa mammarenavirus (LASMV) using strains from Nigeria

Lassa mammarenavirus (LASMV) is responsible for a specific type of acute viral hemorrhagic fever known as Lassa fever. Lack of effective treatments and counter-measures against the virus has resulted in a high mortality rate in its endemic regions. Therefore, in this study, a novel epitope-based vaccine has been designed using the methods of immunoinformatics targeting the glycoprotein and nucleoprotein of the virus. After numerous robust analyses, two CTL epitopes, eight HTL epitopes and seven B-cell epitopes were finally selected for constructing the vaccine. All these most promising epitopes were found to be antigenic, non-allergenic, nontoxic and non-human homolog, which made them suitable for designing the subunit vaccine. Furthermore, the selected T-cell epitopes which were found to be fully conserved across different isolates of the virus, were also considered for final vaccine construction. After that, numerous validation experiments, i.e. molecular docking, molecular dynamics simulation and immune simulation were conducted, which predicted that our designed vaccine should be stable within the biological environment and effective in combating the LASMV infection. In the end, codon adaptation and in silico cloning studies were performed to design a recombinant plasmid for producing the vaccine industrially. However, further in vitro and in vivo assessments should be done on the constructed vaccine to finally confirm its safety and efficacy.Communicated by Ramaswamy H. Sarma.

Engineering a novel subunit vaccine against SARS-CoV-2 by exploring immunoinformatics approach

As the number of infections and deaths caused by the recent COVID-19 pandemic is increasing dramatically day-by-day, scientists are rushing towards developing possible countermeasures to fight the deadly virus, SARS-CoV-2. Although many efforts have already been put forward for developing potential vaccines; however, most of them are proved to possess negative consequences. Therefore, in this study, immunoinformatics methods were exploited to design a novel epitope-based subunit vaccine against the SARS-CoV-2, targeting four essential proteins of the virus i.e., spike glycoprotein, nucleocapsid phosphoprotein, membrane glycoprotein, and envelope protein. The highly antigenic, non-allergenic, non-toxic, non-human homolog, and 100% conserved (across other isolates from different regions of the world) epitopes were used for constructing the vaccine. In total, fourteen CTL epitopes and eighteen HTL epitopes were used to construct the vaccine. Thereafter, several in silico validations i.e., the molecular docking, molecular dynamics simulation (including the RMSF and RMSD studies), and immune simulation studies were also performed which predicted that the designed vaccine should be quite safe, effective, and stable within the biological environment. Finally, in silico cloning and codon adaptation studies were also conducted to design an effective mass production strategy of the vaccine. However, more in vitro and in vivo studies are required on the predicted vaccine to finally validate its safety and efficacy.

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.

Blueprint of epitope-based multivalent and multipathogenic vaccines: targeted against the dengue and zika viruses

Both dengue virus (DENV) and zika virus (ZIKV) belong to the highly infectious Flaviviridae family that has already caused several outbreaks and epidemics in many countries. DENV and ZIKV cause two of the most wide spread mosquito-borne viral diseases in the world, dengue fever (DENF) and zika fever (ZIKF), respectively. In many regions around the world, both of these diseases can outbreak together and can be lethal as well as life-threatening. Unfortunately, there is no functional and satisfactory vaccine available to combat these viruses. Therefore, in this study, we have attempted to design a blue print of potential multivalent and multipathogenic vaccines using immunoinformatics approach, which can combat both the DENV and ZIKV infections, simultaneously. Initially, three vaccines were designed; containing highly antigenic, non-allergenic, and non-toxic epitopes of T-cell (100% conserved) and B-cell from all the four DENV serotypes and ZIKV. In total, nine cytotoxic T-lymphocytic (CTL), nine helper T-lymphocytic (HTL), and seven B-cell lymphocytic (BCL) epitopes were used to construct three vaccines using three different adjuvants, designated as 'V1', 'V2', and 'V3'. Later, V3 was found to be the best vaccine construct, determined by molecular docking analysis. Thereafter, several in silico validation studies including molecular dynamics simulation and immune simulation were performed which indicated that V3 might be quite stable and should generate substantial immune response in the biological environment. However, further in vivo and in vitro validation might be required to finally confirm the safety and efficacy of our suggested vaccine constructs.Communicated by Ramaswamy H. Sarma.

A candidate multi-epitope vaccine against SARS-CoV-2

In the past two decades, 7 coronaviruses have infected the human population, with two major outbreaks caused by SARS-CoV and MERS-CoV in the year 2002 and 2012, respectively. Currently, the entire world is facing a pandemic of another coronavirus, SARS-CoV-2, with a high fatality rate. The spike glycoprotein of SARS-CoV-2 mediates entry of virus into the host cell and is one of the most important antigenic determinants, making it a potential candidate for a vaccine. In this study, we have computationally designed a multi-epitope vaccine using spike glycoprotein of SARS-CoV-2. The overall quality of the candidate vaccine was validated in silico and Molecular Dynamics Simulation confirmed the stability of the designed vaccine. Docking studies revealed stable interactions of the vaccine with Toll-Like Receptors and MHC Receptors. The in silico cloning and codon optimization supported the proficient expression of the designed vaccine in E. coli expression system. The efficiency of the candidate vaccine to trigger an effective immune response was assessed by an in silico immune simulation. The computational analyses suggest that the designed multi-epitope vaccine is structurally stable which can induce specific immune responses and thus, can be a potential vaccine candidate against SARS-CoV-2.

Exploiting the reverse vaccinology approach to design novel subunit vaccines against Ebola virus

Ebola virus is a highly pathogenic RNA virus that causes the Ebola haemorrhagic fever in human. This virus is considered as one of the dangerous viruses in the world with very high mortality rate. To date, no epitope-based subunit vaccine has yet been discovered to fight against Ebola although the outbreaks of this deadly virus took many lives in the past. In this study, approaches of reverse vaccinology were utilized in combination with different tools of immunoinformatics to design subunit vaccines against Ebola virus strain Mayinga-76. Three potential antigenic proteins of this virus i.e., matrix protein VP40, envelope glycoprotein and nucleoprotein were selected to construct the subunit vaccine. The MHC class-I, MHC class-II and B-cell epitopes were determined initially and after some robust analysis i.e., antigenicity, allergenicity, toxicity, conservancy and molecular docking study, EV-1, EV-2 and EV-3 were constructed as three potential vaccine constructs. These vaccine constructs are also expected to be effective on few other strains of Ebola virus since the highly conserved epitopes were used for vaccine construction. Thereafter, molecular docking study was conducted on these vaccines and EV-1 emerged as the best vaccine construct. Afterward, molecular dynamics simulation study revealed the good performances and stability of the intended vaccine protein. Finally, codon adaptation and in silico cloning were carried out to design a possible plasmid (pET-19b plasmid vector was used) for large scale production of the EV-1 vaccine. However, further in vitro and in vivo studies might be required on the predicted vaccines for final validation.

Bioinformatics Analysis of Domain 1 of HCV-Core Protein: Iran

Hepatitis C virus (HCV) infection is a serious global health problem and a cause of chronic hepatitis, liver cirrhosis, and hepatocellular carcinoma (HCC). Bioinformatics software has been an effective tool to study the HCV genome as well as core domains. Our research was based on employing several bioinformatics software applications to find important mutations in domain 1 of core protein in Iranian HCV infected samples from 2006 to 2017, and an investigation of general properties, B-cell and T-cell epitopes, modification sites, and structure of domain 1. Domain 1 sequences of 188 HCV samples isolated from 2006 to 2017, Iran, were retrieved from NCBI gene bank. Using several tools, all sequences were analyzed for determination of mutations, physicochemical analysis, B-cell epitopes prediction, T-cell and CTL epitopes prediction, post modification, secondary and tertiary structure prediction. Our analysis determined several mutations in some special positions (70, 90, 91, and 110) that are associated with HCC and hepatocarcinogenesis, efficacy of triple therapy and sustained virological response, and interaction between core and CCR6. Several B-cell, T-cell, and CTL epitopes were recognized. Secondary and tertiary structures were mapped fordomain1 and core proteins. Our study, as a first report, offered inclusive data about frequent mutation in HCV-core gene domain 1 in Iranian sequences that can provide helpful analysis on structure and function of domain 1 of the core gene.