Peptide vaccine against chikungunya virus: immuno-informatics combined with molecular docking approach

The Current Progress in the Quest for Vaccines Against the Semliki Forest Virus Complex

The Semliki Forest virus (SFV) complex comprises of arboviruses that are transmitted by arthropod vectors and cause acute febrile illness in humans. In the last seven decades, re-emergence of these viruses has resulted in numerous outbreaks globally, affecting regions including Africa, Americas, Asia, Europe and the Caribbean. These viruses are transmitted to humans by the bite of infected mosquitoes. Symptoms of infection include high fever, severe joint pain, skin rash, muscle pain and headache. Fatal cases were reported, and mortality rate increased during the epidemic of these viruses. There is therefore a need to control the spread of these emerging arboviruses. Given that vaccination is one of the most effective ways to protect populations against viral outbreaks, efforts have been made to develop and test potential vaccine candidates. However, there are still no licensed vaccines available against the medically important viruses in the SFV complex. This review first summarizes the current knowledge of the SFV complex disease pathogenesis. Next, seven strategies that have been applied in vaccine development against these viruses are reviewed, indicating the immune response and efficacies of these vaccine candidates in in vivo models of infection. Finally, the more promising candidates that have entered clinical trials are discussed and insights into the future development of vaccines for viruses of the SFV complex are given.

Revolutionizing Chikungunya Vaccines: mRNA Breakthroughs With Molecular and Immune Simulations

With the ability to cause massive epidemics that have consequences on millions of individuals globally, the Chikungunya virus (CHIKV) emerges as a severe menace. Developing an effective vaccine is urgent as no effective therapeutics are available for such viral infections. Therefore, we designed a novel mRNA vaccine against CHIKV with a combination of highly antigenic and potential MHC-I, MHC-II, and B-cell epitopes from the structural polyprotein. The vaccine demonstrated well-characterized physicochemical properties, indicating its solubility and potential functional stability within the body (GRAVY score of -0.639). Structural analyses of the vaccine revealed a well-stabilized secondary and tertiary structure (Ramachandran score of 82.8% and a Z-score of -4.17). Docking studies of the vaccine with TLR-2 (-1027.7 KJ/mol) and TLR-4 (-1212.4 KJ/mol) exhibited significant affinity with detailed hydrogen bond interactions. Molecular dynamics simulations highlighted distinct conformational dynamics among the vaccine, "vaccine-TLR-2" and "vaccine-TLR-4" complexes. The vaccine's ability to elicit both innate and adaptive immune responses, including the presence of memory B-cells and T-cells, persistent B-cell immunity for a year, and the activation of TH cells leading to the release of IFN-γ and IL-2, has significant implications for its potential effectiveness. The CHIKV vaccine developed in this study shows promise as a potential candidate for future vaccine production against CHIKV, suggesting its suitability for further clinical advancement, including in vitro and in vivo experiments.

An In Silico Design of a Vaccine against All Serotypes of the Dengue Virus Based on Virtual Screening of B-Cell and T-Cell Epitopes

Dengue virus poses a significant global health challenge, particularly in tropical and subtropical regions. Despite the urgent demand for vaccines in the control of the disease, the two approved vaccines, Dengvaxia and TV003/TV005, there are current questions regarding their effectiveness due to an increased risk of antibody-dependent enhancement (ADE) and reduced protection. These challenges have underscored the need for further development of improved vaccines for Dengue Virus. This study presents a new design using an in silico approach to generate a more effective dengue vaccine. Initially, our design process began with the collection of Dengue polyprotein sequences from 10 representative countries worldwide. And then conserved fragments of viral proteins were retrieved as the bases for epitope screening. The selection of epitopes was then carried out with criteria such as antigenicity, immunogenicity, and binding affinity with MHC molecules, while the exclusion criteria were according to their allergenicity, toxicity, and potential for antibody-dependent enhancement. We then constructed a core antigen with the selected epitopes and linked the outcomes with distinct adjuvant proteins, resulting in three candidate vaccines: PSDV-1, PSDV-2, and PSDV-3. Among these, PSDV-2 was selected for further validation due to its superior physicochemical and structural properties. Extensive simulations demonstrated that PSDV-2 exhibited strong binding to pattern recognition receptors, high stability, and robust immune induction, confirming its potential as a high-quality vaccine candidate. For its recombinant expression, a plasmid was subsequently designed. Our new vaccine design offers a promising additional option for Dengue virus protection. Further experimental validations will be conducted to confirm its protective efficacy and safety.

Uncovering chikungunya virus-encoded miRNAs and host-specific targeted genes associated with antiviral immune responses: an integrated bioinformatics approach

Chikungunya virus (CHIKV) is a single-stranded RNA virus belonging to the genus Alphavirus and is responsible for causing Chikungunya fever, a type of arboviral fever. Despite extensive research, the pathogenic mechanism of CHIKV within host cells remains unclear. In this study, an in-silico approach was used to predict that CHIKV produces micro-RNAs that target host-specific genes associated with host cellular regulatory pathways. Putative micro-RNAs of CHIKV were predicted using the miRNAFold and Vmir RNA structure web servers, and secondary structure prediction was performed using RNAfold. Host-specific target genes were then predicted, and hub genes were identified using CytoHubba and module selection through MCODE. Functional annotations of hub genes revealed their association with various pathways, including osteoclast differentiation, neuroactive ligand-receptor interaction, and mRNA surveillance. We used the freely available dataset GSE49985 to determine the level of expression of host-specific target genes and found that two genes, F-box and leucine-rich repeat protein 16 (FBXL16) and retinoic acid receptor alpha (RARA), were down-regulated, while four genes, RNA binding protein with serine-rich domain 1 (RNPS1), RNA helicase and ATPase (UPF1), neuropeptide S receptor 1 (NPSR1), and vasoactive intestinal peptide receptor 1 (VIPR1), were up-regulated. These findings provide insight into novel miRNAs and hub genes associated with CHIKV infection and suggest potential targets for therapeutic intervention. Further experimental validation of these targets could lead to the development of effective treatments for CHIKV-mediated diseases.

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

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

A Review: The Antiviral Activity of Cyclic Peptides

In the design and development of therapeutic agents, macromolecules with restricted structures have stronger competitive edges than linear biological entities since cyclization can overcome the limitations of linear structures. The common issues of linear peptides include susceptibility to degradation of the peptidase enzyme, off-target effects, and necessity of routine dosing, leading to instability and ineffectiveness. The unique conformational constraint of cyclic peptides provides a larger surface area to interact with the target at the same time, improving the membrane permeability and in vivo stability compared to their linear counterparts. Currently, cyclic peptides have been reported to possess various activities, such as antifungal, antiviral and antimicrobial activities. To date, there is emerging interest in cyclic peptide therapeutics, and increasing numbers of clinically approved cyclic peptide drugs are available on the market. In this review, the medical significance of cyclic peptides in the defence against viral infections will be highlighted. Except for chikungunya virus, which lacks specific antiviral treatment, all the viral diseases targeted in this review are those with effective treatments yet with certain limitations to date. Thus, strategies and approaches to optimise the antiviral effect of cyclic peptides will be discussed along with their respective outcomes. Apart from isolated naturally occurring cyclic peptides, chemically synthesized or modified cyclic peptides with antiviral activities targeting coronavirus, herpes simplex viruses, human immunodeficiency virus, Ebola virus, influenza virus, dengue virus, five main hepatitis viruses, termed as type A, B, C, D and E and chikungunya virus will be reviewed herein.

Graphical Abstract

Identification of Lignan Compounds as New 6-Phosphogluconate Dehydrogenase Inhibitors for Lung Cancer

Targeting pentose phosphate pathway (PPP) enzymes has emerged as a promising strategy to combat cancer. 6-Phosphogluconate dehydrogenase (6-PGD), the third critical enzyme of the PPP, catalyzes oxidative decarboxylation of 6-phosphogluconate (6-PG) to produce ribulose-5-phosphate (Ru-5-P) and CO2. Overexpression of 6-PGD has been reported in multiple cancers and is recognized as a potential anticancer drug target. The current study is focused on the utilization of indispensable virtual screening tools for structure-based drug discovery. During the study, 17,000 natural compounds were screened against the 3-phosphoglycerate (3-PG) binding site of 6-PGD through a molecular operating environment (MOE), which revealed 115 inhibitors with higher selectivity and binding affinity. Out of the 115 best-fit compounds within the 6-PGD binding cavity, 15 compounds were selected and optimized through stringent in silico ADMET assessment models that justified the desirable pharmacokinetic, pharmacodynamic and physicochemical profiles of 5 ligands. Further protein−ligand stability assessment through molecular dynamics (MD) simulation illustrated three potential hits, secoisolariciresinol, syringaresinol and cleomiscosin A, with stable confirmation. Moreover, 6-PGD inhibitor validation was performed by an in vitro enzymatic assay using human erythrocytes purified 6-PGD protein and A549 cell lysate protein. The results of the in vitro assays supported the in silico findings. In order to gain insight into the anticancer activity of the aforementioned compounds, they were subjected to CLC-Pred, an in silico cytotoxicity browsing tool, which proved their anticancer activity against several cancer cell lines at Pa > 0.5. Additionally, a confirmation for in silico cytotoxicity was made by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay for commercially available hits syringaresinol and cleomiscosin A against lung cancer (A549) cells. The results demonstrated that syringaresinol has an IC50 value of 36.9 μg/mL, while cleomiscosin A has an IC50 value of 133 μg/mL. After MTT, flow cytometry analysis confirmed that compounds induced apoptosis in A549 cells in a dose-dependent manner. This study suggested that the respective lignan compounds can serve as lead candidates for lung cancer therapy via 6-PGD inhibition. Furthermore, in vivo experiments need to be conducted to confirm their efficacy.

Designing a multi-epitope vaccine against coxsackievirus B based on immunoinformatics approaches

Coxsackievirus B (CVB) is one of the major viral pathogens of human myocarditis and cardiomyopathy without any effective preventive measures; therefore, it is necessary to develop a safe and efficacious vaccine against CVB. Immunoinformatics methods are both economical and convenient as in-silico simulations can shorten the development time. Herein, we design a novel multi-epitope vaccine for the prevention of CVB by using immunoinformatics methods. With the help of advanced immunoinformatics approaches, we predicted different B-cell, cytotoxic T lymphocyte (CTL), and helper T lymphocyte (HTL) epitopes, respectively. Subsequently, we constructed the multi-epitope vaccine by fusing all conserved epitopes with appropriate linkers and adjuvants. The final vaccine was found to be antigenic, non-allergenic, and stable. The 3D structure of the vaccine was then predicted, refined, and evaluated. Molecular docking and dynamics simulation were performed to reveal the interactions between the vaccine with the immune receptors MHC-I, MHC-II, TLR3, and TLR4. Finally, to ensure the complete expression of the vaccine protein, the sequence of the designed vaccine was optimized and further performed in-silico cloning. In conclusion, the molecule designed in this study could be considered a potential vaccine against CVB infection and needed further experiments to evaluate its safety and efficacy.

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.

mRNA Vaccine Designing Using Chikungunya Virus E Glycoprotein through Immunoinformatics-Guided Approaches

Chikungunya virus is an alphavirus transmitted by mosquitos that develops into chikungunya fever and joint pain in humans. This virus’ name originated from a Makonde term used to describe an illness that changes the joints and refers to the posture of afflicted patients who are affected by excruciating joint pain. There is currently no commercially available drug or vaccine for chikungunya virus infection and the treatment is performed by symptom reduction. Herein, we have developed a computationally constructed mRNA vaccine construct featuring envelope glycoprotein as the target molecule to aid in the treatment process. We have utilized the reverse vaccinology approach to determine epitopes that would generate adaptive immune reactions. The resulting T and B lymphocytes epitopes were screened by various immunoinformatic tools and a peptide vaccine construct was designed. It was validated by proceeding to docking and MD simulation studies. The following design was then back-translated in nucleotide sequence and codons were optimized according to the expression host system (H. sapiens). Various sequences, including 3′ and 5′ UTR regions, Kozak sequence, poly (A) tail, etc., were introduced into the sequence for the construction of the final mRNA vaccine construct. The secondary structure was generated for validation of the mRNA vaccine construct sequence. Additionally, in silico cloning was also performed to design a vector for proceeding towards in vitro experimentation. The proposed designed vaccine construct may proceed with experimental testing for further efficacy verification and the final development of a vaccine against chikungunya virus infection.

In silico designing of a novel epitope-based candidate vaccine against Streptococcus pneumoniae with introduction of a new domain of PepO as adjuvant

BACKGROUND

Streptococcus pneumoniae is the leading reason for invasive diseases including pneumonia and meningitis, and also secondary infections following viral respiratory diseases such as flu and COVID-19. Currently, serotype-dependent vaccines, which have several insufficiency and limitations, are the only way to prevent pneumococcal infections. Hence, it is plain to need an alternative effective strategy for prevention of this organism. Protein-based vaccine involving conserved pneumococcal protein antigens with different roles in virulence could provide an eligible alternative to existing vaccines.

METHODS

In this study, PspC, PhtD and PsaA antigens from pneumococcus were taken to account to predict B-cell and helper T-cell epitopes, and epitope-rich regions were chosen to build the construct. To enhance the immunogenicity of the epitope-based vaccine, a truncated N-terminal fragment of pneumococcal endopeptidase O (PepO) was used as a potential TLR2/4 agonist which was identified by molecular docking studies. The ultimate construct was consisted of the chosen epitope-rich regions, along with the adjuvant role (truncated N-PepO) and suitable linkers.

RESULTS

The epitope-based vaccine was assessed as regards physicochemical properties, allergenicity, antigenicity, and toxicity. The 3D structure of the engineered construct was modeled, refined, and validated. Molecular docking and simulation of molecular dynamics (MD) indicated the proper and stable interactions between the vaccine and TLR2/4 throughout the simulation periods.

CONCLUSIONS

For the first time this work presents a novel vaccine consisting of epitopes of PspC, PhtD, and PsaA antigens which is adjuvanted with a new truncated domain of PepO. The computational outcomes revealed that the suggested vaccine could be deemed an efficient therapeutic vaccine for S. pneumoniae; nevertheless, in vitro and in vivo examinations should be performed to prove the potency of the candidate vaccine.

Vaccinomics to Design a Multi-Epitopes Vaccine for Acinetobacter baumannii

Antibiotic resistance (AR) is the result of microbes' natural evolution to withstand the action of antibiotics used against them. AR is rising to a high level across the globe, and novel resistant strains are emerging and spreading very fast. Acinetobacter baumannii is a multidrug resistant Gram-negative bacteria, responsible for causing severe nosocomial infections that are treated with several broad spectrum antibiotics: carbapenems, β-lactam, aminoglycosides, tetracycline, gentamicin, impanel, piperacillin, and amikacin. The A. baumannii genome is superplastic to acquire new resistant mechanisms and, as there is no vaccine in the development process for this pathogen, the situation is more worrisome. This study was conducted to identify protective antigens from the core genome of the pathogen. Genomic data of fully sequenced strains of A. baumannii were retrieved from the national center for biotechnological information (NCBI) database and subjected to various genomics, immunoinformatics, proteomics, and biophysical analyses to identify potential vaccine antigens against A. baumannii. By doing so, four outer membrane proteins were prioritized: TonB-dependent siderphore receptor, OmpA family protein, type IV pilus biogenesis stability protein, and OprD family outer membrane porin. Immuoinformatics predicted B-cell and T-cell epitopes from all four proteins. The antigenic epitopes were linked to design a multi-epitopes vaccine construct using GPGPG linkers and adjuvant cholera toxin B subunit to boost the immune responses. A 3D model of the vaccine construct was built, loop refined, and considered for extensive error examination. Disulfide engineering was performed for the stability of the vaccine construct. Blind docking of the vaccine was conducted with host MHC-I, MHC-II, and toll-like receptors 4 (TLR-4) molecules. Molecular dynamic simulation was carried out to understand the vaccine-receptors dynamics and binding stability, as well as to evaluate the presentation of epitopes to the host immune system. Binding energies estimation was achieved to understand intermolecular interaction energies and validate docking and simulation studies. The results suggested that the designed vaccine construct has high potential to induce protective host immune responses and can be a good vaccine candidate for experimental in vivo and in vitro studies.

Expression, Purification, and Refolding of Chikungunya Virus Full-Length Envelope E2 Protein along with B-Cell and T-Cell Epitope Analyses Using Immuno-Informatics Approaches

Chikungunya virus (CHIKV) is a mosquito-transmitted alphavirus, which causes severe illness in humans and is responsible for epidemic outbreaks in Africa, Asia, North and South America, and Europe. Despite its increased global prevalence, no licensed vaccines are available to date for treating or preventing CHIKV infection. The envelope E2 protein is one of the promising subunit vaccine candidates against CHIKV. In this study, we describe successful cloning, expression, and purification of CHIKV E2 full-length (E2-FL) and truncated (E2-ΔC and E2-ΔNC) proteins in the Escherichia coli expression system. The recombinant E2 proteins were purified from inclusion bodies using Ni-NTA chromatography. Further, we describe a detailed refolding procedure for obtaining the CHIKV E2-FL protein in native conformation, which was confirmed using circular dichroism and Fourier transform infrared spectroscopy. BALB/c mice immunized with the three different E2 proteins exhibited increased E2-specific antibody titers compared to sham-immunized controls, suggesting induction of strong humoral immune response. On analyzing the E2-specific antibody response generated in immunized mice, the CHIKV E2-FL protein was observed to be the most immunogenic among the three different CHIKV E2 antigens used in the study. Our B-cell and T-cell epitope mapping results indicate that the presence of specific immunogenic peptides located in the N-terminal and C-terminal regions of the CHIKV E2-FL protein may contribute to its increased immunogenicity, compared to truncated CHIKV E2 proteins. In summary, our study provides a detailed protocol for expressing, purifying, and refolding of the CHIKV E2-FL protein and provides an understanding of its immunogenic epitopes, which can be exploited for the development of novel multiepitope-based anti-CHIKV vaccine strategies.

Chikungunya Virus Vaccine Development: Through Computational Proteome Exploration for Finding of HLA and cTAP Binding Novel Epitopes as Vaccine Candidates

Chikungunya virus is a major arbovirus of great public health concern in the whole world, but no vaccine is yet available, still advance therapeutic treatment and effective vaccines are in progress. The present multistep screening and structural binding analysis with CHIKV proteome exploration can be crucial in the development phase of CHIKV epitope based vaccine. The approach employed in two phases (i) Sequence based screening of peptides through propred and IEDB Server (ii) Structure based study through autodocking and NAMD VMD simulation analysis. Among all 29 extracted peptides, only two peptides ²LLANTTFPC¹⁰ of protein E3 and ⁹⁸VNSVAIPLL¹⁰⁶ of protein nsP3 were observed most prominent over all consider parameters such as peptide conserve nature, supertype population coverage, TAP binding, docking and simulation study. During docking interaction study, the best peptide and allele docked complexes such as ²LLANTTFPC¹⁰–B*0702 allele and ⁹⁸VNSVAIPLL¹⁰⁶–A*0301 allele exhibited best binding energy of − 3.13 kcal/mol and − 3.19 kcal/mol, respectively, with stable bonding patterns and their motion during NAMD simulation which confirm conserve peptide and allele stable interaction. The current study also exhibited the good docking interaction of both peptides ²LLANTTFPC¹⁰ and ⁹⁸VNSVAIPLL¹⁰⁶ with c TAP1 protein (1jj7 -PDB ID) cavity which confirm as a channel passageway to peptide transport through the cytoplasm to lumen of ER during antigen processing and presentation. Overall, this multistep screening and crosscheck structural binding analysis with an exploration of the complete proteome of CHIKV can be a novel step in the development of CHIKV epitope based vaccine as well as diagnostic development with aspect of time, cost and side effects.

Identification of immunodominant epitopes in allelic variants VK210 and VK247 of Plasmodium Vivax Circumsporozoite immunogen

Plasmodium vivax-induced malaria is among the leading causes of morbidity and mortality in sub-tropical and tropical regions and infect 2.85 billion people globally. The continual rise and propagation of resistance against anti-malarial drugs is a prerequisite to develop a potent vaccine candidate for Plasmodium vivax (P. vivax). Circumsporozoite protein (CSP) is an important immunogen of malaria parasite that has the conserved CSP structure as an immune dominant B-cell epitope. In current study, we focused on designing multi-epitope vaccines (MEVs) using various immunoinformatics tools against Pakistani based allelic variants VK210 and VK247 of P. vivax CSP (PvCSP) gene. Antigenicity, allergic potential and physicochemical parameters of both PvCSP variants were assessed for the designed MEVs and they were within acceptable range suitable for post experimental investigations. The three-dimensional structures of both MEVs have been predicted ab initio, optimized, and validated by using different online servers. The both MEVs candidates were stable and free from aggregation-prone regions. The stability of both MEVs had been improved by a disulfide engineering approach. To estimate the binding energy and stability of the MEVs, molecular docking simulation and binding free energy calculations with TLR-4 immune receptor have been conducted. The docking score of PvCSP210 and PvCSP247 for TLR-4 was -6.34 kJ/mol and - 2.3 kJ/mol, respectively. For PvCSP210-TLR4 system, mean RMSD was 4.96 Å while PvCSP247-TLR4 system, average RMSD was 4.49 Å. The binding free energy of PvCSP210-TLR4 complex and PvCSP247-TLR4 complex was -50.49/-117.15 kcal/mol (MMGBSA/MMPSA) and -52.94/-96.26 kcal/mol (MMGBSA/MMPSA), respectively. The expression of both MEVs produced in Escherichia coli K12 expression system by in silico cloning was significant. Immune simulation revealed that the proposed MEVs induce strong humoral and cellular immunological responses, in addition to significant production of interleukins and cytokines. In conclusions, we believed that the MEVs proposed in current research, using combine approach of immunoinformatics, structural biology and biophysical approaches, could induce protective and effective immune responses against P. vivax and the experimental validation of our findings could contribute to the development of potential malaria vaccine.

In Silico Identification of Chikungunya Virus B- and T-Cell Epitopes with High Antigenic Potential for Vaccine Development

Reverse vaccinology is an outstanding strategy to identify antigens with high potential for vaccine development. Different parameters of five prediction programs were used to assess their sensitivity and specificity to identify B-cell epitopes of Chikungunya virus (CHIKV) strains reported in the IEDB database. The results, based on the use of 15 to 20 mer epitopes and the polyproteins to which they belong, were compared to establish the best parameters to optimize the prediction of antigenic peptides of the Mexican strain CHIKV AJV21562.1. LBtope showed the highest specificity when we used the reported epitopes and polyproteins but the worst sensitivity with polyproteins; ABCpred had similar specificity to LBtope only with the epitopes reported and showed moderate specificity when we used polyproteins for the predictions. Because LBtope was more reliable in predicting true epitopes, it was used as a reference program to predict and select six novel epitopes of the Mexican strain of CHIKV according to prediction frequency, viral genome localization, and non-homology with the human proteome. On the other hand, six bioinformatics programs were used with default parameters to predict T-cell epitopes in the CHIKV strains AJV21562.1 and AJV21561.1. The sequences of the polyproteins were analyzed to predict epitopes present in the more frequent HLA alleles of the Mexican population: DQA1*03011, DQA1*0401, DQA1*0501, DQB1*0201, DQB1*0301, DQB1*0302, and DQB1*0402. Fifteen predicted epitopes in the non-structural and 15 predicted epitopes in the structural polyprotein (9- to 16-mers) with the highest scores of each allele were compared to select epitopes with at least 80% identity. Next, the epitopes predicted with at least two programs were aligned to the human proteome, and 12 sequences without identity with the human proteome were identified as potential antigenic candidates. This strategy would be useful to evaluate vaccine candidates against other viral diseases affecting the countries of the Americas and to increase knowledge about these diseases.

A Comprehensive Computer Aided Vaccine Design Approach to Propose a Multi-Epitopes Subunit Vaccine against Genus Klebsiella Using Pan-Genomics, Reverse Vaccinology, and Biophysical Techniques

Klebsiella is a genus of nosocomial bacterial pathogens and is placed in the most critical list of World Health Organization (WHO) for development of novel therapeutics. The pathogens of the genus are associated with high mortality and morbidity. Owing to their strong resistance profile against different classes of antibiotics and nonavailability of a licensed vaccine, urgent efforts are required to develop a novel vaccine candidate that can tackle all pathogenic species of the Klebsiella genus. The present study aims to design a broad-spectrum vaccine against all species of the Klebsiella genus with objectives to identify the core proteome of pathogen species, prioritize potential core vaccine proteins, analyze immunoinformatics of the vaccine proteins, construct a multi-epitopes vaccine, and provide its biophysical analysis. Herein, we investigated all reference species of the genus to reveal their core proteome. The core proteins were then subjected to multiple reverse vaccinology checks that are mandatory for the prioritization of potential vaccine candidates. Two proteins (TonB-dependent siderophore receptor and siderophore enterobactin receptor FepA) were found to fulfill all vaccine parameters. Both these proteins harbor several potent B-cell-derived T-cell epitopes that are antigenic, nonallergic, nontoxic, virulent, water soluble, IFN-γ producer, and efficient binder of DRB*0101 allele. The selected epitopes were modeled into a multi-epitope peptide comprising linkers and Cholera Toxin B adjuvant. For docking with innate immune and MHC receptors and afterward molecular dynamics simulations and binding free energy analysis, the vaccine structure was modeled for tertiary structure and refined for structural errors. To assess the binding affinity and presentation of the designed vaccine construct, binding mode and interactions analysis were performed using molecular docking and molecular dynamics simulation techniques. These biophysical approaches illustrated the vaccine as a good binder to the immune receptors and revealed robust interactions energies. The vaccine sequence was further translated to nucleotide sequence and cloned into an appropriate vector for expressing it at high rate in Escherichia coli K12 strain. In addition, the vaccine was illustrated to generate a good level of primary, secondary, and tertiary immune responses, proving good immunogenicity of the vaccine. Based on the reported results, the vaccine can be a good candidate to be evaluated for effectiveness in wet laboratory validation studies.

Design of Monovalent and Chimeric Tetravalent Dengue Vaccine Using an Immunoinformatics Approach

An immunoinformatics technique was used to predict a monovalent amide immunogen candidate capable of producing therapeutic antibodies as well as a potent immunogen candidate capable of acting as a universal vaccination against all dengue fever virus serotypes. The capsid protein is an attractive goal for anti-DENV due to its position in the dengue existence cycle. The widely accessible immunological data, advances in antigenic peptide prediction using reverse vaccinology, and the introduction of molecular docking in immunoinformatics have directed vaccine manufacturing. The C-proteins of DENV-1-4 serotypes were known as antigens to assist with logical design. Binding epitopes for TC cells, TH cells, and B cells is predicted from structural dengue virus capsid proteins. Each T cell epitope of C-protein integrated with a B cell as a templet was used as a vaccine and produce antibodies in contrast to serotype of the dengue virus. A chimeric tetravalent vaccine was created by combining four vaccines, each representing four dengue serotypes, to serve as a standard vaccine candidate for all four Sero groups. The LKRARNRVS, RGFRKEIGR, KNGAIKVLR, and KAINVLRGF from dengue 1, dengue 2, dengue 3, and dengue 4 epitopes may be essential immunotherapeutic representatives for controlling outbreaks.

Immunoinformatics Approach to Design Multi-Epitope- Subunit Vaccine against Bovine Ephemeral Fever Disease

Bovine ephemeral fever virus (BEFV) is an overlooked pathogen, recently gaining widespread attention owing to its associated enormous economic impacts affecting the global livestock industries. High endemicity with rapid spread and morbidity greatly impacts bovine species, demanding adequate attention towards BEFV prophylaxis. Currently, a few suboptimum vaccines are prevailing, but were confined to local strains with limited protection. Therefore, we designed a highly efficacious multi-epitope vaccine candidate targeted against the geographically distributed BEFV population. By utilizing immunoinformatics technology, all structural proteins were targeted for B- and T-cell epitope prediction against the entire allele population of BoLA molecules. Prioritized epitopes were adjoined by linkers and adjuvants to effectively induce both cellular and humoral immune responses in bovine. Subsequently, the in silico construct was characterized for its physicochemical parameters, high immunogenicity, least allergenicity, and non-toxicity. The 3D modeling, refinement, and validation of ligand (vaccine construct) and receptor (bovine TLR7) then followed molecular docking and molecular dynamic simulation to validate their stable interactions. Moreover, in silico cloning of codon-optimized vaccine construct in the prokaryotic expression vector (pET28a) was explored. This is the first time HTL epitopes have been predicted using bovine datasets. We anticipate that the designed construct could be an effective prophylactic remedy for the BEF disease that may pave the way for future laboratory experiments.

Structural basis of UDP-N-acetylglucosamine pyrophosphorylase and identification of promising terpenes to control Aedes aegypti

According to the world health organization (WHO) 2020 report, vector borne diseases account for 17 % of all infections with reported 700 thousand death each year. They are of considerable importance to health professionals as they are posing a serious health threat and include dengue fever, Zika fever, chikungunya, yellow fever, and other disease agents. Aedes aegypti serve as a vector for transmitting several of these tropical fevers. In the present study, UDP-N-acetylglucosamine pyrophosphorylase enzyme (Aa-UAP) of A. aegypti which plays a significant contribution in chitin metabolism is targeted with natural terpenes to propose an eco-friendly and novel candidates for the development of new insecticides. The three dimensional Aa-UAP structure was constructed via a comparative homology approach and validated, followed by structure-based virtual screening against 1000 terpenes collected from natural MDP3 and NPACT databases. Top hits were subjected to molecular dynamics (MD) simulations and binding free energies analysis to elucidate complex intermolecular stability and affinity over simulated time. The results demonstrated that Aa-UAP possesses a homodimer state and its active site residues are well conserved. Three compounds (NPACT00138, NPACT00452, and NPACT00839) were prioritized as they are establishing conserved and stable interactions with the active binding-site residues of Aa-UAP. Conclusively, the reported Aa-UAP specific terpenes could serve as promising leads in order to develop potential insecticides. Importantly, the FDA approved drug NPACT00839 (Paclitaxel) could be used further in the fast-track experimental testing pipeline for biological optimization.

Immunoinformatic approach to design a multiepitope vaccine targeting non-mutational hotspot regions of structural and non-structural proteins of the SARS CoV2

BACKGROUND

The rapid Severe Acute Respiratory Syndrome Coronavirus 2 (SARS CoV2) outbreak caused severe pandemic infection worldwide. The high mortality and morbidity rate of SARS CoV2 is due to the unavailability of vaccination and mutation in this virus. The present article aims to design a potential vaccine construct VTC3 targeting the non-mutational region of structural and non-structural proteins of SARS CoV2.

METHODS

In this study, vaccines were designed using subtractive proteomics and reverse vaccinology. To target the virus adhesion and evasion, 10 different structural and non-structural proteins have been selected. Shortlisted proteins have been screened for B cell, T cell and IFN gamma interacting epitopes. 3D structure of vaccine construct was modeled and evaluated for its physicochemical properties, immunogenicity, allergenicity, toxicity and antigenicity. The finalized construct was implemented for docking and molecular dynamics simulation (MDS) with different toll-like receptors (TLRs) and human leukocyte antigen (HLA). The binding energy and dissociation construct of the vaccine with HLA and TLR was also calculated. Mutational sensitivity profiling of the designed vaccine was performed, and mutations were reconfirmed from the experimental database. Antibody production, clonal selection, antigen processing, immune response and memory generation in host cells after injection of the vaccine was also monitored using immune simulation.

RESULTS

Subtractive proteomics identified seven (structural and non-structural) proteins of this virus that have a role in cell adhesion and infection. The different epitopes were predicted, and only extracellular epitopes were selected that do not have similarity and cross-reactivity with the host cell. Finalized epitopes of all proteins with minimum allergenicity and toxicity were joined using linkers to designed different vaccine constructs. Docking different constructs with different TLRs and HLA demonstrated a stable and reliable binding affinity of VTC3 with the TLRs and HLAs. MDS analysis further confirms the interaction of VTC3 with HLA and TLR1/2 complex. The VTC3 has a favorable binding affinity and dissociation constant with HLA and TLR. The VTC3 does not have similarities with the human microbiome, and most of the interacting residues of VTC3 do not have mutations. The immune simulation result showed that VTC3 induces a strong immune response. The present study designs a multiepitope vaccine targeting the non-mutational region of structural and non-structural proteins of the SARS CoV2 using an immunoinformatic approach, which needs to be experimentally validated.

Immuno-Informatics Analysis of Pakistan-Based HCV Subtype-3a for Chimeric Polypeptide Vaccine Design

Hepatitis C virus (HCV) causes chronic and acute hepatitis infections. As there is extreme variability in the HCV genome, no approved HCV vaccine has been available so far. An effective polypeptide vaccine based on the functionally conserved epitopes will be greatly helpful in curing disease. For this purpose, an immuno-informatics study is performed based on the published HCV subtype-3a from Pakistan. First, the virus genome was translated to a polyprotein followed by a subsequent prediction of T-cell epitopes. Non-allergenic, IFN-γ producer, and antigenic epitopes were shortlisted, including 5 HTL epitopes and 4 CTL, which were linked to the final vaccine by GPGPG and AAY linkers, respectively. Beta defensin was included as an adjuvant through the EAAAK linker to improve the immunogenicity of the polypeptide. To ensure its safety and immunogenicity profile, antigenicity, allergenicity, and various physiochemical attributes of the polypeptide were evaluated. Molecular docking was conducted between TLR4 and vaccine to evaluate the binding affinity and molecular interactions. For stability assessment and binding of the vaccine-TLR4 docked complex, molecular dynamics (MD) simulation and MMGBSA binding free-energy analyses were conducted. Finally, the candidate vaccine was cloned in silico to ensure its effectiveness. The current vaccine requires future experimental confirmation to validate its effectiveness. The vaccine construct produced might be useful in providing immune protection against HCV-related infections.

Therapeutic Potential of Umbilical Cord Stem Cells for Liver Regeneration

The liver is a vital organ for life and the only internal organ that is capable of natural regeneration. Although the liver has high regeneration capacity, excessive hepatocyte death can lead to liver failure. Various factors can lead to liver damage including drug abuse, some natural products, alcohol, hepatitis, and autoimmunity. Some models for studying liver injury are APAP-based model, Fas ligand (FasL), D-galactosamine/endotoxin (Gal/ET), Concanavalin A, and carbon tetrachloride-based models. The regeneration of the liver can be carried out using umbilical cord blood stem cells which have various advantages over other stem cell types used in liver transplantation. UCB-derived stem cells lack tumorigenicity, have karyotype stability and high immunomodulatory, low risk of graft versus host disease (GVHD), low risk of transmitting somatic mutations or viral infections, and low immunogenicity. They are readily available and their collection is safe and painless. This review focuses on recent development and modern trends in the use of umbilical cord stem cells for the regeneration of liver fibrosis.

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

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

Epitope-Based Potential Vaccine Candidate for Humoral and Cell-Mediated Immunity to Combat Severe Acute Respiratory Syndrome Coronavirus 2 Pandemic

The emergence of severe acute respiratory syndrome from novel Coronavirus (SARS-CoV-2) has put an immense pressure worldwide where vaccination is believed to be an efficient way for developing hard immunity. Herein, we employ immunoinformatic tools to identify B-cell, T-cell epitopes associated with the spike protein of SARS-CoV-2, which is important for genome release. The results showed that the highly immunogenic epitopes located at the stalk part are mostly conserved compared to the receptor binding domain (RDB). Further, two vaccine candidates were computationally modeled from the linear B-cell, T-cell epitopes. Molecular docking reveals the crucial interactions of the vaccines with immune-receptors, and their stability is assessed by MD simulation studies. The chimeric vaccines showed remarkable binding affinity toward the immune cell receptors computed by the MM/PBSA method. van der Waals and electrostatic interactions are found to be the dominant factors for the stability of the complexes. The molecular-level interaction obtained from this study may provide deeper insight into the process of vaccine development against the pandemic of COVID-19.

Design and optimization of a subunit vaccine targeting COVID-19 molecular shreds using an immunoinformatics framework

COVID-19 has been declared as a global health emergency and exposed the world to a deadly virus, which has dramatically changed the lives of humans for an unknown period of time. In the battleground with the virus, we have employed an immunoinformatics framework to design a robust vaccine as an insurance plan for the future. The pathogenic sequence with cryptic epitope taken from patients in Wuhan, China, was harnessed to design a promiscuous cytotoxic T-lymphocyte, helper T-lymphocyte, and B-cell epitope based subunit vaccine, engineered with adjuvants and conformational linkers. The reported vaccine has high antigenicity and immunogenicity profiles with potential TAP affinity, which ensures elevated antigen processing capability. It has strong binding with major histocompatibility complex (MHC) receptors (MHC-1 and MHC-2) and virus-specific membrane receptor TLR-2, with scores of -1010.7, -1035.7, and -1076.3 kcal mol-1, respectively. Molecular dynamics simulation analysis was used to assess the stable binding with TLR-2 with minimal atomic motions through a deformation plot, covariance matrix, and elastic network. Importantly, an in silico immunization assay showed the reliable elicitation of key players in terms of immune cells together with memory cells to evoke adaptive immune responses upon administration of the construct. In view of favorable outcomes, we also propose a plausible vaccine mechanism to elicit an immune response to fight coronavirus.

Reverse vaccinology assisted designing of multiepitope-based subunit vaccine against SARS-CoV-2

BACKGROUND

Coronavirus disease 2019 (COVID-19) linked with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cause severe illness and life-threatening pneumonia in humans. The current COVID-19 pandemic demands an effective vaccine to acquire protection against the infection. Therefore, the present study was aimed to design a multiepitope-based subunit vaccine (MESV) against COVID-19.

METHODS

Structural proteins (Surface glycoprotein, Envelope protein, and Membrane glycoprotein) of SARS-CoV-2 are responsible for its prime functions. Sequences of proteins were downloaded from GenBank and several immunoinformatics coupled with computational approaches were employed to forecast B- and T- cell epitopes from the SARS-CoV-2 highly antigenic structural proteins to design an effective MESV.

RESULTS

Predicted epitopes suggested high antigenicity, conserveness, substantial interactions with the human leukocyte antigen (HLA) binding alleles, and collective global population coverage of 88.40%. Taken together, 276 amino acids long MESV was designed by connecting 3 cytotoxic T lymphocytes (CTL), 6 helper T lymphocyte (HTL) and 4 B-cell epitopes with suitable adjuvant and linkers. The MESV construct was non-allergenic, stable, and highly antigenic. Molecular docking showed a stable and high binding affinity of MESV with human pathogenic toll-like receptors-3 (TLR3). Furthermore, in silico immune simulation revealed significant immunogenic response of MESV. Finally, MEV codons were optimized for its in silico cloning into the Escherichia coli K-12 system, to ensure its increased expression.

CONCLUSION

The MESV developed in this study is capable of generating immune response against COVID-19. Therefore, if designed MESV further investigated experimentally, it would be an effective vaccine candidate against SARS-CoV-2 to control and prevent COVID-19.

Study of combining virtual screening and antiviral treatments of the Sars-CoV-2 (Covid-19)

The recent epidemic outbreak of a novel human coronavirus called SARS-CoV-2 and causing the respiratory tract disease COVID-19 has reached worldwide resonance and a global effort is being undertaken to characterize the molecular features and evolutionary origins of this virus. Therefore, rapid and accurate identification of pathogenic viruses plays a vital role in selecting appropriate treatments, saving people's lives and preventing epidemics. Additionally, general treatments, coronavirus-specific treatments, and antiviral treatments useful in fighting COVID-19 are addressed. This review sets out to shed light on the SARS-CoV-2 and host receptor recognition, a crucial factor for successful virus infection and taking immune-informatics approaches to identify B- and T-cell epitopes for surface glycoprotein of SARS-CoV-2. A variety of improved or new approaches also have been developed. It is anticipated that this will assist researchers and clinicians in developing better techniques for timely and effective detection of coronavirus infection. Moreover, the genomic sequence of the virus responsible for COVID-19, as well as the experimentally determined three-dimensional structure of the Main protease (Mpro) is available. The reported structure of the target Mpro was described in this review to identify potential drugs for COVID-19 using virtual high throughput screening.

Bioinformatics analysis of epitope-based vaccine design against the novel SARS-CoV-2

Background

An outbreak of infection caused by SARS-CoV-2 recently has brought a great challenge to public health. Rapid identification of immune epitopes would be an efficient way to screen the candidates for vaccine development at the time of pandemic. This study aimed to predict the protective epitopes with bioinformatics methods and resources for vaccine development.

Methods

The genome sequence and protein sequences of SARS-CoV-2 were retrieved from the National Center for Biotechnology Information (NCBI) database. ABCpred and BepiPred servers were utilized for sequential B-cell epitope analysis. Discontinuous B-cell epitopes were predicted via DiscoTope 2.0 program. IEDB server was utilized for HLA-1 and HLA-2 binding peptides computation. Surface accessibility, antigenicity, and other important features of forecasted epitopes were characterized for immunogen potential evaluation.

Results

A total of 63 sequential B-cell epitopes on spike protein were predicted and 4 peptides (Spike_315–324, Spike_333–338, Spike_648–663, Spike_1064–1079) exhibited high antigenicity score and good surface accessibility. Ten residues within spike protein (Gly⁴⁹⁶, Glu⁴⁹⁸, Pro⁴⁹⁹, Thr⁵⁰⁰, Leu¹¹⁴¹, Gln¹¹⁴², Pro¹¹⁴³, Glu¹¹⁴⁴, Leu¹¹⁴⁵, Asp¹¹⁴⁶) are forecasted as components of discontinuous B-cell epitopes. The bioinformatics analysis of HLA binding peptides within nucleocapsid protein produced 81 and 64 peptides being able to bind MHC class I and MHC class II molecules respectively. The peptides (Nucleocapsid_66–75, Nucleocapsid_104–112) were predicted to bind a wide spectrum of both HLA-1 and HLA-2 molecules.

Conclusions

B-cell epitopes on spike protein and T-cell epitopes within nucleocapsid protein were identified and recommended for developing a protective vaccine against SARS-CoV-2.

Exploring HCV genome to construct multi-epitope based subunit vaccine to battle HCV infection: Immunoinformatics based approach

Hepatitis C Virus (HCV) infection is a major cause of chronic liver disease, hepatocellular carcinoma, and the single most common indication for liver transplantation. HCV vaccines eliciting specific T-cell responses, have been considered as potent method to prevent HCV infection. Despite several reports on progress of vaccine, these vaccine failed in mediating clinical relevance activity against HCV in humans. In this study we integrated both immunoinformatic and molecular docking approach to present a multiepitope vaccine against HCV by designating 17 conserved epitopes from eight viral proteins such as Core protein, E1, E2, NS2, NS34A, NS4B, NS5A, and NS5B. The epitopes were prioritized based on conservation among epitopes of T cell, B cell and IFN-γ that were then scanned for non-homologous to host and antigenicity. The prioritized epitopes were then linked together by AAY linker and adjuvant (β-defensin) were attached at N-terminal to enhance immunogenic potential. The construct thus formed were subjected to structural modeling and physiochemical characteristics. The modeled structure were successfully docked to antigenic receptor TLR-3 and In-silico cloning confers the authenticity of its expression efficiency. However, the proposed construct need to be validate experimentally to ensure its safety and immunogenic profile.

Epitope-based peptide vaccines predicted against novel coronavirus disease caused by SARS-CoV-2

•

Linear B-cell epitopes in RBD of S protein predicted against SARS-CoV-2.

•

Discontinuous B-cell epitopes from S protein predicted against SARS-CoV-2.

•

T-cell epitopes from S, M and N protein predicted against SARS-CoV-2.

The outbreak of the 2019 novel coronavirus (SARS-CoV-2) has infected millions of people with a large number of deaths across the globe. The existing therapies are limited in dealing with SARS-CoV-2 due to the sudden appearance of the virus. Therefore, vaccines and antiviral medicines are in desperate need. We took immune-informatics approaches to identify B- and T-cell epitopes for surface glycoprotein (S), membrane glycoprotein (M) and nucleocapsid protein (N) of SARS-CoV-2, followed by estimating their antigenicity and interactions with the human leukocyte antigen (HLA) alleles. Allergenicity, toxicity, physiochemical properties analysis and stability were examined to confirm the specificity and selectivity of the epitope candidates. We identified a total of five B cell epitopes in RBD of S protein, seven MHC class-I, and 18 MHC class-II binding T-cell epitopes from S, M and N protein which showed non-allergenic, non-toxic and highly antigenic features and non-mutated in 55,179 SARS-CoV-2 virus strains until June 25, 2020. The epitopes identified here can be a potentially good candidate repertoire for vaccine development.

Immunoinformatics and Structural Analysis for Identification of Immunodominant Epitopes in SARS-CoV-2 as Potential Vaccine Targets

A new coronavirus infection, COVID-19, has recently emerged, and has caused a global pandemic along with an international public health emergency. Currently, no licensed vaccines are available for COVID-19. The identification of immunodominant epitopes for both B- and T-cells that induce protective responses in the host is crucial for effective vaccine design. Computational prediction of potential epitopes might significantly reduce the time required to screen peptide libraries as part of emergent vaccine design. In our present study, we used an extensive immunoinformatics-based approach to predict conserved immunodominant epitopes from the proteome of SARS-CoV-2. Regions from SARS-CoV-2 protein sequences were defined as immunodominant, based on the following three criteria regarding B- and T-cell epitopes: (i) they were both mapped, (ii) they predicted protective antigens, and (iii) they were completely identical to experimentally validated epitopes of SARS-CoV. Further, structural and molecular docking analyses were performed in order to understand the binding interactions of the identified immunodominant epitopes with human major histocompatibility complexes (MHC). Our study provides a set of potential immunodominant epitopes that could enable the generation of both antibody- and cell-mediated immunity. This could contribute to developing peptide vaccine-based adaptive immunotherapy against SARS-CoV-2 infections and prevent future pandemic outbreaks.

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

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

Prediction of Epitope-Based Peptide Vaccine Against the Chikungunya Virus by Immuno-informatics Approach

BACKGROUND

Chikungunya is an arthropod-borne viral disease characterized by abrupt onset of fever frequently accompanied by joint pain, which has been identified in over 60 countries in Africa, the Americas, Asia, and Europe.

METHODS

Regardless of the availability of molecular knowledge of this virus, no definite vaccine or other remedial agents have been developed yet. In the present study, a combination of B-cell and T-cell epitope predictions, followed by molecular docking simulation approach has been carried out to design a potential epitope-based peptide vaccine, which can trigger a critical immune response against the viral infections.

RESULTS

A total of 52 sequences of E1 glycoprotein from the previously reported isolates of Chikungunya outbreaks were retrieved and examined through in silico methods to identify a potential B-cell and T-cell epitope. From the two separate epitope prediction servers, five potential B-cell epitopes were selected, among them "NTQLSEAHVEKS" was found highly conserved across strains and manifests high antigenicity with surface accessibility, flexibility, and hydrophilicity. Similarly, two highly conserved, non-allergenic, non-cytotoxic putative T-cell epitopes having maximum population coverage were screened to bind with the HLA-C 12*03 molecule. Molecular docking simulation revealed potential T-cell based epitope "KTEFASAYR" as a vaccine candidate for this virus.

CONCLUSION

A combination of these B-cell and T-cell epitope-based vaccine can open up a new skyline with broader therapeutic application against Chikungunya virus with further experimental and clinical investigation.

Design of a Multiepitope-Based Peptide Vaccine against the E Protein of Human COVID-19: An Immunoinformatics Approach

Background

A new endemic disease has spread across Wuhan City, China, in December 2019. Within few weeks, the World Health Organization (WHO) announced a novel coronavirus designated as coronavirus disease 2019 (COVID-19). In late January 2020, WHO declared the outbreak of a “public-health emergency of international concern” due to the rapid and increasing spread of the disease worldwide. Currently, there is no vaccine or approved treatment for this emerging infection; thus, the objective of this study is to design a multiepitope peptide vaccine against COVID-19 using an immunoinformatics approach.

Method

Several techniques facilitating the combination of the immunoinformatics approach and comparative genomic approach were used in order to determine the potential peptides for designing the T-cell epitope-based peptide vaccine using the envelope protein of 2019-nCoV as a target.

Results

Extensive mutations, insertion, and deletion were discovered with comparative sequencing in the COVID-19 strain. Additionally, ten peptides binding to MHC class I and MHC class II were found to be promising candidates for vaccine design with adequate world population coverage of 88.5% and 99.99%, respectively.

Conclusion

The T-cell epitope-based peptide vaccine was designed for COVID-19 using the envelope protein as an immunogenic target. Nevertheless, the proposed vaccine rapidly needs to be validated clinically in order to ensure its safety and immunogenic profile to help stop this epidemic before it leads to devastating global outbreaks.

Structural basis of SARS-CoV-2 3CLpro and anti-COVID-19 drug discovery from medicinal plants

The recent pandemic of coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 has raised global health concerns. The viral 3-chymotrypsin-like cysteine protease (3CL^pro) enzyme controls coronavirus replication and is essential for its life cycle. 3CL^pro is a proven drug discovery target in the case of severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV). Recent studies revealed that the genome sequence of SARS-CoV-2 is very similar to that of SARS-CoV. Therefore, herein, we analysed the 3CL^pro sequence, constructed its 3D homology model, and screened it against a medicinal plant library containing 32,297 potential anti-viral phytochemicals/traditional Chinese medicinal compounds. Our analyses revealed that the top nine hits might serve as potential anti- SARS-CoV-2 lead molecules for further optimisation and drug development process to combat COVID-19.

•

SARS-CoV-2 3CL^pro is conserved, share 99.02% sequence identity with SARS-CoV 3CL^pro and together with 12 point-mutations.

•

Mutations disrupt important hydrogen bonds and alter the receptor binding site of SARS-CoV-2 3CL^pro.

•

Medicinal plants phytochemicals were proved potential anti-COVID-19 druggable candidates.

Immunoinformatics guided rational design of a next generation multi epitope based peptide (MEBP) vaccine by exploring Zika virus proteome

Zika virus (ZIKV) is an RNA virus that has spread through mosquito sting. Currently, no vaccine and antiviral medication available so far against ZIKV. Therefore, it has fostered a study to design MEBP vaccine enabling effective prevention against the ZIKV infection. In this study combination of immuno-informatics and molecular docking approach was used to constitute a MEBP vaccine. The ZIKV proteome was used for prediction of B-cell, T-cell (HTL & CTL) and IFN-γ epitopes. After prediction, highly antigenic and overlapping epitopes have been shortlisted which includes 14 CTL and 11 HTL epitopes that have been linked to the final peptide through AAY and GPGPG linkers respectively. An adjuvant at the N-end of the vaccine was added to improve the immunogenicity of the vaccine through the EAAAK linker. The final construct constitutes 435 amino acids after the addition of linkers and adjuvant. The existence of B-cell and IFN-γ epitopes affirms the humoral and cell-mediated immune responses acquired by the construct. Allergenicity, antigenicity and different physiochemical attributes of the vaccine were evaluated to assure its safety and immunogenicity profile. In fact, the construct was antigenic and non-allergenic. Docking was performed among vaccine and TLR-3 to evaluate the binding affinity and the molecular interaction. Finally, the construct was subjected to In silico cloning to confers the authenticity of its expression efficiency. However, the proposed construct need to be validate experimentally to ensure its safety and immunogenic profile.

Epitope-based peptide vaccine design and target site depiction against Middle East Respiratory Syndrome Coronavirus: an immune-informatics study

Background

Middle East Respiratory Syndrome Coronavirus (MERS-COV) is the main cause of lung and kidney infections in developing countries such as Saudi Arabia and South Korea. This infectious single-stranded, positive (+) sense RNA virus enters the host by binding to dipeptidyl-peptide receptors. Since no vaccine is yet available for MERS-COV, rapid case identification, isolation, and infection prevention strategies must be used to combat the spreading of MERS-COV infection. Additionally, there is a desperate need for vaccines and antiviral strategies.

Methods

The present study used immuno-informatics and computational approaches to identify conserved B- and T cell epitopes for the MERS-COV spike (S) protein that may perform a significant role in eliciting the resistance response to MERS-COV infection.

Results

Many conserved cytotoxic T-lymphocyte epitopes and discontinuous and linear B-cell epitopes were predicted for the MERS-COV S protein, and their antigenicity and interactions with the human leukocyte antigen (HLA) B7 allele were estimated. Among B-cell epitopes, QLQMGFGITVQYGT displayed the highest antigenicity-score, and was immensely immunogenic. Among T-cell epitopes, MHC class-I peptide YKLQPLTFL and MHC class-II peptide YCILEPRSG were identified as highly antigenic. Furthermore, docking analyses revealed that the predicted peptides engaged in strong bonding with the HLA-B7 allele.

Conclusion

The present study identified several MERS-COV S protein epitopes that are conserved among various isolates from different countries. The putative antigenic epitopes may prove effective as novel vaccines for eradication and combating of MERS-COV infection.

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.