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1.
Immunoinformatics (Amst) ; 8: 100020, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2095503

ABSTRACT

The Omicron (BA.1/B.1.1.529) variant of SARS-CoV-2 harbors an alarming 37 mutations on its spike protein, reducing the efficacy of current COVID-19 vaccines. In this study, we identified CD8+ and CD4+ T cell epitopes from SARS-CoV-2 S protein mutants. To identify the highest quality CD8 and CD4 epitopes from the Omicron variant, we selected epitopes with a high binding affinity towards both MHC I and MHC II molecules. We applied other clinical checkpoint predictors, including immunogenicity, antigenicity, allergenicity, instability and toxicity. Subsequently, we found eight Omicron (BA.1/B.1.1.529) specific CD8+ and eleven CD4+ T cell epitopes with a world population coverage of 76.16% and 97.46%, respectively. Additionally, we identified common epitopes across Omicron BA.1 and BA.2 lineages that target mutations critical to SARS-CoV-2 virulence. Further, we identified common epitopes across B.1.1.529 and other circulating SARS-CoV-2 variants, such as B.1.617.2 (Delta). We predicted CD8 epitopes' binding affinity to murine MHC alleles to test the vaccine candidates in preclinical models. The CD8 epitopes were further validated using our previously developed software tool PCOptim. We then modeled the three-dimensional structures of our top CD8 epitopes to investigate the binding interaction between peptide-MHC and peptide-MHC-TCR complexes. Notably, our identified epitopes are targeting the mutations on the RNA-binding domain and the fusion sites of S protein. This could potentially eliminate viral infections and form long-term immune responses compared to relatively short-lived mRNA vaccines and maximize the efficacy of vaccine candidates against the current pandemic and potential future variants.

2.
Struct Chem ; 33(6): 2243-2260, 2022.
Article in English | MEDLINE | ID: covidwho-2094729

ABSTRACT

Millions of lives have been infected since the SARS-CoV-2 outbreak in 2019. The high human-to-human transmission rate has warranted a need for a vaccine to protect people. Although some vaccines are in use, due to the high mutation rate in the SARS-CoV-2 multiple variants, the current vaccines may not be sufficient to immunize people against new variant threats. One of the emerging concern variants is B1.1.529 (Omicron), which carries ~ 30 mutations in the Spike protein (S) of SARS-CoV-2 and is predicted to evade antibody recognition even from vaccinated people. We used a structure-based approach and an epitope prediction server to develop a Multi-Epitope based Subunit Vaccine (MESV) involving SARS-CoV-2 B1.1.529 variant spike glycoprotein. The predicted epitope with better antigenicity and non-toxicity was used for designing and predicting vaccine construct features and structure models. In addition, the MESV construct In silico cloning in the pET28a expression vector predicted the construct to be highly translational. The proposed MESV vaccine construct was also subjected to immune simulation prediction and was found to be highly antigenic and elicit a cell-mediated immune response. Therefore, the proposed MESV in the present study has the potential to be evaluated further for vaccine production against the newly identified B1.1.529 (Omicron) variant of concern. Supplementary Information: The online version contains supplementary material available at 10.1007/s11224-022-02027-6.

3.
Comput Biol Med ; 150: 106128, 2022 Sep 25.
Article in English | MEDLINE | ID: covidwho-2093312

ABSTRACT

Epstein-Barr virus (EBV) is widely known due to its role in the etiology of infectious mononucleosis. However, it is the first oncovirus that was identified and has been implicated in the etiology of several types of cancers. Globally, EBV infection is associated with more than 200, 000 new cancer cases and 150, 000 deaths yearly. A prophylactic or therapeutic vaccine targeting tumors associated with EBV infection is currently lacking. Therefore, this study aimed to develop a multiepitope-based polyvalent vaccine against EBV-associated tumors using immunoinformatics approach. The latency-associated proteins (LAP) of three strains of the virus were used in this study. Potential epitopes predicted from the proteins were analyzed and selected based on several predicted properties. Thirty viable B-cell and T-cell epitopes were selected and conjugated using various linkers alongside beta-defensin 3 as an adjuvant and pan HLA DR-binding epitope (PADRE) sequence to improve the immunogenicity of the vaccine construct. Molecular docking studies of the vaccine construct against toll-like receptors (TLRs) showed it is capable of inducing immune response via recognition by TLRs while immune simulation studies showed it could induce both cellular and humoral immune responses. Furthermore, molecular dynamics study of the complex formed by the vaccine candidate and TLR-4 showed that the complex was stable. Ultimately, the designed vaccine showed desirable properties based on in silico evaluation; however, experimental studies are needed to validate the efficacy of the vaccine against EBV-associated tumors.

4.
Vaccines (Basel) ; 10(11)2022 Oct 31.
Article in English | MEDLINE | ID: covidwho-2090409

ABSTRACT

After the outbreak of SARS-CoV-2 by the end of 2019, the vaccine development strategies became a worldwide priority. Furthermore, the appearances of novel SARS-CoV-2 variants challenge researchers to develop new pharmacological or preventive strategies. However, vaccines still represent an efficient way to control the SARS-CoV-2 pandemic worldwide. This review describes the importance of bioinformatic and immunoinformatic tools (in silico) for guide vaccine design. In silico strategies permit the identification of epitopes (immunogenic peptides) which could be used as potential vaccines, as well as nonacarriers such as: vector viral based vaccines, RNA-based vaccines and dendrimers through immunoinformatics. Currently, nucleic acid and protein sequential as well structural analyses through bioinformatic tools allow us to get immunogenic epitopes which can induce immune response alone or in complex with nanocarriers. One of the advantages of in silico techniques is that they facilitate the identification of epitopes, while accelerating the process and helping to economize some stages of the development of safe vaccines.

5.
Front Bioinform ; 1: 709951, 2021.
Article in English | MEDLINE | ID: covidwho-2089808

ABSTRACT

Development of vaccines and therapeutic antibodies to deal with infectious and other diseases are the most perceptible scientific interventions that have had huge impact on public health including that in the current Covid-19 pandemic. From inactivation methodologies to reverse vaccinology, vaccine development strategies of 21st century have undergone several transformations and are moving towards rational design approaches. These developments are driven by data as the combinatorials involved in antigenic diversity of pathogens and immune repertoire of hosts are enormous. The computational prediction of epitopes is central to these developments and numerous B-cell epitope prediction methods developed over the years in the field of immunoinformatics have contributed enormously. Most of these methods predict epitopes that could potentially bind to an antibody regardless of its type and only a few account for antibody class specific epitope prediction. Recent studies have provided evidence of more than one class of antibodies being associated with a particular disease. Therefore, it is desirable to predict and prioritize 'peptidome' representing B-cell epitopes that can potentially bind to multiple classes of antibodies, as an open problem in immunoinformatics. To address this, AbCPE, a novel algorithm based on multi-label classification approach has been developed for prediction of antibody class(es) to which an epitope can potentially bind. The epitopes binding to one or more antibody classes (IgG, IgE, IgA and IgM) have been used as a knowledgebase to derive features for prediction. Multi-label algorithms, Binary Relevance and Label Powerset were applied along with Random Forest and AdaBoost. Classifier performance was assessed using evaluation measures like Hamming Loss, Precision, Recall and F1 score. The Binary Relevance model based on dipeptide composition, Random Forest and AdaBoost achieved the best results with Hamming Loss of 0.1121 and 0.1074 on training and test sets respectively. The results obtained by AbCPE are promising. To the best of our knowledge, this is the first multi-label method developed for prediction of antibody class(es) for sequential B-cell epitopes and is expected to bring a paradigm shift in the field of immunoinformatics and immunotherapeutic developments in synthetic biology. The AbCPE web server is available at http://bioinfo.unipune.ac.in/AbCPE/Home.html.

6.
Viruses ; 14(11)2022 Oct 24.
Article in English | MEDLINE | ID: covidwho-2081985

ABSTRACT

Reports on T-cell cross-reactivity against SARS-CoV-2 epitopes in unexposed individuals have been linked with prior exposure to the human common cold coronaviruses (HCCCs). Several studies suggested that cross-reactive T-cells response to live attenuated vaccines (LAVs) such as BCG (Bacillus Calmette-Guérin), OPV (Oral Polio Vaccine), and MMR (measles, mumps, and rubella) can limit the development and severity of COVID-19. This study aims to identify potential cross-reactivity between SARS-CoV-2, HCCCs, and LAVs in the context of T-cell epitopes peptides presented by HLA (Human Leukocyte Antigen) alleles of the Indonesian population. SARS-CoV-2 derived T-cell epitopes were predicted using immunoinformatics tools and assessed for their conservancy, variability, and population coverage. Two fully conserved epitopes with 100% similarity and nine heterologous epitopes with identical T-cell receptor (TCR) contact residues were identified from the ORF1ab fragment of SARS-CoV-2 and all HCCCs. Cross-reactive epitopes from various proteins of SARS-CoV-2 and LAVs were also identified (15 epitopes from BCG, 7 epitopes from MMR, but none from OPV). A majority of the identified epitopes were observed to belong to ORF1ab, further suggesting the vital role of ORF1ab in the coronaviruses family and suggesting it as a candidate for a potential universal coronavirus vaccine that protects against severe disease by inducing cell mediated immunity.


Subject(s)
COVID-19 , Common Cold , Middle East Respiratory Syndrome Coronavirus , Viral Vaccines , Humans , SARS-CoV-2/genetics , Epitopes, T-Lymphocyte , Middle East Respiratory Syndrome Coronavirus/genetics , Vaccines, Attenuated , COVID-19 Vaccines , COVID-19/prevention & control , Alleles , BCG Vaccine , Indonesia/epidemiology , Spike Glycoprotein, Coronavirus/genetics
7.
Vaccines (Basel) ; 10(10)2022 Oct 08.
Article in English | MEDLINE | ID: covidwho-2066630

ABSTRACT

In the growing field of vaccine design for COVID and cancer research, it is essential to predict accurate peptide binding affinity and immunogenicity. We developed a comprehensive machine learning method, 'IntegralVac,' by integrating three existing deep learning tools: DeepVacPred, MHCSeqNet, and HemoPI. IntegralVac makes predictions for single and multivalent cancer and COVID-19 epitopes without manually selecting epitope prediction possibilities. We performed several rounds of optimization before integration, then re-trained IntegralVac for multiple datasets. We validated the IntegralVac with 4500 human cancer MHC I peptides obtained from the Immune Epitope Database (IEDB) and with cancer and COVID epitopes previously selected in our laboratory. The other data referenced from existing deep learning tools served as a positive control to ensure successful prediction was possible. As evidenced by increased accuracy and AUC, IntegralVac improved the prediction rate of top-ranked epitopes. We also examined the compatibility between other servers' clinical checkpoint filters and IntegralVac. This was to ensure that the other servers had a means for predicting additional checkpoint filters that we wanted to implement in IntegralVac. The clinical checkpoint filters, including allergenicity, antigenicity, and toxicity, were used as additional predictors to improve IntegralVac's prediction accuracy. We generated immunogenicity scores by cross-comparing sequence inputs with each other and determining the overlap between each individual peptide sequence. The IntegralVac increased the immunogenicity prediction accuracy to 90.1% AUC and the binding affinity accuracy to 95.4% compared to the control NetMHCPan server. The IntegralVac opens new avenues for future in silico methods, by building upon established models for continued prediction accuracy improvement.

8.
Vaccines (Basel) ; 10(10)2022 Oct 03.
Article in English | MEDLINE | ID: covidwho-2066620

ABSTRACT

INTRODUCTION: The ongoing coronavirus disease 2019 (COVID-19), which emerged in December 2019, is a serious health concern throughout the world. Despite massive COVID-19 vaccination on a global scale, there is a rising need to develop more effective vaccines and drugs to curb the spread of coronavirus. METHODOLOGY: In this study, we screened the amino acid sequence of the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 (the causative agent of COVID-19) for the identification of B and T cell epitopes using various immunoinformatic tools. These identified potent B and T cell epitopes with high antigenicity scores were linked together to design the multi-epitope vaccine construct. The physicochemical properties, overall quality, and stability of the designed vaccine construct were confirmed by suitable bioinformatic tools. RESULTS: After proper in silico prediction and screening, we identified 3 B cell, 18 CTL, and 10 HTL epitopes from the RdRp protein sequence. The screened epitopes were non-toxic, non-allergenic, and highly antigenic in nature as revealed by appropriate servers. Molecular docking revealed stable interactions of the designed multi-epitope vaccine with human TLR3. Moreover, in silico immune simulations showed a substantial immunogenic response of the designed vaccine. CONCLUSIONS: These findings suggest that our designed multi-epitope vaccine possessing intrinsic T cell and B cell epitopes with high antigenicity scores could be considered for the ongoing development of peptide-based novel vaccines against COVID-19. However, further in vitro and in vivo studies need to be performed to confirm our in silico observations.

9.
Comput Biol Chem ; 101: 107754, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2049073

ABSTRACT

The current COVID-19 pandemic, an infectious disease caused by the novel coronavirus (SARS-CoV-2), poses a threat to global health because of its high rate of spread and death. Currently, vaccination is the most effective method to prevent the spread of this disease. In the present study, we developed a novel multiepitope vaccine against SARS-CoV-2 containing Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (BA.1) variants. To this end, we performed a robust immunoinformatics approach based on multiple epitopes of the four structural proteins of SARS-CoV-2 (S, M, N, and E) from 475 SARS-CoV-2 genomes sequenced from the regions with the highest number of registered cases, namely the United States, India, Brazil, France, Germany, and the United Kingdom. To investigate the best immunogenic epitopes for linear B cells, cytotoxic T lymphocytes (CTL), and helper T lymphocytes (HTL), we evaluated antigenicity, allergenicity, conservation, immunogenicity, toxicity, human population coverage, IFN-inducing, post-translational modifications, and physicochemical properties. The tertiary structure of a vaccine prototype was predicted, refined, and validated. Through docking experiments, we evaluated its molecular coupling to the key immune receptor Toll-Like Receptor 3 (TLR3). To improve the quality of docking calculations, quantum mechanics/molecular mechanics calculations (QM/MM) were used, with the QM part of the simulations performed using the density functional theory formalism (DFT). Cloning and codon optimization were performed for the successful expression of the vaccine in E. coli. Finally, we investigated the immunogenic properties and immune response of our SARS-CoV-2 multiepitope vaccine. The results of the simulations show that administering our prototype three times significantly increases the antibody response and decreases the amount of antigens. The proposed vaccine candidate should therefore be tested in clinical trials for its efficacy in neutralizing SARS-CoV-2.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , SARS-CoV-2/genetics , COVID-19 Vaccines , Pandemics/prevention & control , Vaccinology , COVID-19/prevention & control , Escherichia coli , Epitopes, B-Lymphocyte , Epitopes, T-Lymphocyte , Immunogenicity, Vaccine , Molecular Docking Simulation , Vaccines, Subunit/chemistry
10.
J Genet Eng Biotechnol ; 20(1): 136, 2022 Sep 20.
Article in English | MEDLINE | ID: covidwho-2039148

ABSTRACT

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the ongoing coronavirus disease 2019 (COVID-19) pandemic which has brought a great challenge to public health. After the first emergence of novel coronavirus SARS-CoV-2 in the city of Wuhan, China, in December 2019. As of March 2020, SARS-CoV-2 was first reported in Bangladesh and since then the country has experienced a steady rise in infections, resulting in 13,355,191 cases and 29,024 deaths as of 27 February 2022. Bioinformatics techniques are used to predict B cell and T cell epitopes from the new SARS-CoV-2 spike glycoprotein in order to build a unique multiple epitope vaccine. The immunogenicity, antigenicity scores, and toxicity of these epitopes were evaluated and chosen based on their capacity to elicit an immune response. RESULT: The best multi-epitope of the possible immunogenic property was created by combining epitopes. EAAAK, AAY, and GPGPG linkers were used to connect the epitopes. In several computer-based immune response analyses, this vaccine design was found to be efficient, as well as having high population coverage. CONCLUSION: This research is entirely reliant on the development of epitope-based vaccines, and these in silico findings would represent a major step forward in the development of a vaccine that might eradicate SARS-CoV-2 in Bangladeshi patients.

11.
J Biomol Struct Dyn ; : 1-13, 2022 Sep 20.
Article in English | MEDLINE | ID: covidwho-2037153

ABSTRACT

Recently the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a pervasive threat to generic health. The SARS-CoV-2 spike (S) glycoprotein plays a fundamental role in binds and fusion to the angiotensin-converting enzyme 2 (ACE2). The multi-epitope peptide vaccines would be able to elicit both long-lasting humoral and cellular immune responses, resulting the eliminating SARS-CoV-2 infections as asymptomatic patients are in large numbers. Recently, the omicron variant of the SARS-CoV-2 became a variant of concern that contained just 15-point mutations in the receptor-binding domain of the spike protein. In order to eliminate new evidence on coronavirus variants of concern detected through epidemic intelligence, the conserved epitopes of the receptor-binding domain (RBD) and spike cleavage site is the most probable target for vaccine development to inducing binds and fusion inhibitors neutralizing antibodies respectively. In this study, we utilized bioinformatics tools for identifying and analyzing the spike (S) glycoprotein sequence, e.g. the prediction of the potential linear B-cell epitopes, B-cell multi­epitope design, secondary and tertiary structures, physicochemical properties, solubility, antigenicity, allergenicity, the molecular docking and molecular dynamics simulation for the promising vaccine candidate against all variant of concern of SARS-CoV-2. Among the epitopes of the RBD region are surface-exposed epitopes SVYAWNRKRISNCV and ATRFASVYAWNRKR as the conserved sequences in all variants of concern can be a good candidate to induce an immune response. Communicated by Ramaswamy H. Sarma.

12.
Vaccinology and Methods in Vaccine Research ; : 31-55, 2022.
Article in English | Scopus | ID: covidwho-2035542

ABSTRACT

Vaccinology is a relatively recent discipline involving vaccine development and use. It includes immunology and infectious illnesses, epidemiology, public health, and pediatrics among other specialties of medicine. The experimental, preclinical, clinical, manufacturing, quality control, regulatory review, and approval stages are all involved in the vaccine development process. Vaccines are primarily intended to activate the immune system: separated into innate and adaptive subsystems. Anatomic barriers, physiological barriers, the complement pathway, the inflammatory response, and pattern recognition receptors are all part of the innate system. In the adaptive immune system, B and T lymphocytes are responsible for humoral and cell-mediated defense respectively. Immunoinformatics is extremely useful in contemporary vaccines development, because of the advancements in genomics and proteomics. It involves the use of software, computational tools, and databases to predict immunogenicity, antigenicity, and epitopes for the CD8, CD4, and B cells. This novel technology aided the swiftness in COVID-19 vaccines development. © 2022 Elsevier Inc. All rights reserved.

13.
Proteins ; 2022 Sep 18.
Article in English | MEDLINE | ID: covidwho-2034972

ABSTRACT

Understanding how MHC class II (MHC-II) binding peptides with differing lengths exhibit specific interaction at the core and extended sites within the large MHC-II pocket is a very important aspect of immunological research for designing peptides. Certain efforts were made to generate peptide conformations amenable for MHC-II binding and calculate the binding energy of such complex formation but not directed toward developing a relationship between the peptide conformation in MHC-II structures and the binding affinity (BA) (IC50 ). We present here a machine-learning approach to calculate the BA of the peptides within the MHC-II pocket for HLA-DRA1, HLA-DRB1, HLA-DP, and HLA-DQ allotypes. Instead of generating ensembles of peptide conformations conventionally, the biased mode of conformations was created by considering the peptides in the crystal structures of pMHC-II complexes as the templates, followed by site-directed peptide docking. The structural interaction fingerprints generated from such docked pMHC-II structures along with the Moran autocorrelation descriptors were trained using a random forest regressor specific to each MHC-II peptide lengths (9-19). The entire workflow is automated using Linux shell and Perl scripts to promote the utilization of MHC2AffyPred program to any characterized MHC-II allotypes and is made for free access at https://github.com/SiddhiJani/MHC2AffyPred. The MHC2AffyPred attained better performance (correlation coefficient [CC] of .612-.898) than MHCII3D (.03-.594) and NetMHCIIpan-3.2 (.289-.692) programs in the HLA-DRA1, HLA-DRB1 types. Similarly, the MHC2AffyPred program achieved CC between .91 and .98 for HLA-DP and HLA-DQ peptides (13-mer to 17-mer). Further, a case study on MHC-II binding 15-mer peptides of severe acute respiratory syndrome coronavirus-2 showed very close competency in computing the IC50 values compared to the sequence-based NetMHCIIpan v3.2 and v4.0 programs with a correlation of .998 and .570, respectively.

14.
Journal of Kerman University of Medical Sciences ; 29(4):368-377, 2022.
Article in English | EMBASE | ID: covidwho-2010569

ABSTRACT

Background: The COVID-19 pandemic is a red alarm for global health, so researchers around the world are working on it to design an effective vaccine against it. Protein is one of the candidates for vaccine development which plays an important role in virus pathogenesis. Accordingly, this study was done to evaluate the critical characteristic of this protein as a vaccine candidate using in-silico analysis. Methods: The sequence of SARS-CoV-2-associated E protein was recruited from NCBI and subjected to the IEDB software to evaluate the most potent epitopes. The capacity of the interactions of HLA-I and HLA-II molecules with selective peptides was studied using IEBD tool kit. The E protein sequence was subjected to B cell and T cell tests to realize the most promising peptides that could act as COVID-19 vaccine. Results: Among the tested peptides for the T cell-test, this study found two interesting epitopes: VSEETGTLI and LTALRLCAY that exhibit high binding affinity as a strong indicator to HLA-I and HLA-II alleles together. The results of the analysis demonstrated that some epitopes in the E protein have a relatively higher immunogenicity score based on interaction with HLA-II, such as SEETGTLIVNSVLLF, TLIVNSVLLFLAFVV, LAFVVFLLVTLAILT, LAILTALRLCAYCCN, and SVLLFLAFVVFLLVT. Furthermore, two sequences (FVSEET and PSFYVYSRVKNLNSSRVP) were reported as the selective linear epitopes for B cell, on the surface of SARS-CoV-2 E protein and being Immunogenic. Conclusion: Since E protein can stimulate favorable immune responses, T and B-cell responses, its evaluation in patients with COVID-19 is of a great importance.

15.
SAR QSAR Environ Res ; 33(9): 649-675, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-2008373

ABSTRACT

The pandemic of COVID-19 caused by SARS-CoV-2 has made a worldwide health emergency. Despite the fact that current vaccines are readily available, several SARSCoV-2 variants affecting the existing vaccine are to be less effective due to the mutations in the structural proteins. Furthermore, the appearance of the new variants cannot be easily predicted in the future. Therefore, the attempts to construct new vaccines or to modify the current vaccines are still pivotal works for preventing the spread of the virus. In the present investigation, the computational analysis through immunoinformatics, molecular docking, and molecular dynamics (MD) simulation is employed to construct an effective vaccine against SARS-CoV2. The structural proteins of SARS-CoV2 are utilized to create a multiepitope-based vaccine (MEV). According to our findings presented by systematic procedures in the current investigation, the MEV construct may be able to trigger a strong immunological response against the virus. Therefore, the designed MEV could be a potential vaccine candidate against SARS-CoV-2, and also it is expected to be effective for other variants.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/prevention & control , COVID-19 Vaccines , Epitopes, B-Lymphocyte/chemistry , Epitopes, B-Lymphocyte/genetics , Epitopes, T-Lymphocyte/chemistry , Epitopes, T-Lymphocyte/genetics , Humans , Immunogenicity, Vaccine , Molecular Docking Simulation , Molecular Dynamics Simulation , Quantitative Structure-Activity Relationship , RNA, Viral , Vaccines, Subunit/chemistry
16.
Microb Pathog ; 171: 105736, 2022 Oct.
Article in English | MEDLINE | ID: covidwho-1996428

ABSTRACT

From December 2019, the outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was started as a cluster of pneumonia cases in Wuhan, Hubei Province, China. The disturbing statistics of SARS-CoV-2 promoted scientists to develop an effective vaccine against this infection. NOM protein is a multi-epitope protein that designed based on Nucleocapsid, ORF3a, and Membrane proteins of SARS-CoV-2. Flagellin is a structural protein that binds to the Toll-like receptor 5 and can enhance the immune response to a particular antigen. In this study, NOM protein as vaccine candidate was linked to the carboxyl and amino terminals of flagellin adjuvant derived from Salmonella enterica subsp. enterica serovar Dublin. Then, informatics evaluations were performed for both NOM protein and NOM protein linked to flagellin (FNOM). The interaction between the NOM and FNOM proteins with the TLR5 were assessed using docking analysis. The FNOM protein, which compared to the NOM protein, had a more suitable 3D structure and a stronger interaction with TLR5, was selected for experimental study. The FNOM and Spike (S) proteins expressed and then purified by Ni-NTA column as vaccine candidates. For analysis of immune response, anti-FNOM and anti-S proteins total IgG and IFN-γ, TNF-α, IL-6, IL-10, IL-22 and IL-17 cytokines were evaluated after vaccination of mice with vaccine candidates. The results indicated that the specific antisera (Total IgG) raised in mice that received FNOM protein formulated with S protein were higher than mice that received FNOM and S proteins alone. Also, IFN-γ and TNF-α levels after the spleen cells stimulation were significantly increased in mice that received the FNOM protein formulated with S protein compared to other groups. Immunogenic evaluations showed that, the FNOM chimeric protein could simultaneously elicit humoral and cell-mediated immune responses. Finally, it could be concluded that the FNOM protein formulated with S protein could be considered as potential vaccine candidate for protection against SARS-CoV-2 in the near future.


Subject(s)
COVID-19 , Viral Vaccines , Adjuvants, Immunologic , Animals , Antibodies, Viral , COVID-19/prevention & control , Epitopes , Flagellin/genetics , Immune Sera , Immunoglobulin G , Interleukin-10 , Interleukin-17 , Interleukin-6 , Mice , Recombinant Fusion Proteins , SARS-CoV-2 , Spike Glycoprotein, Coronavirus , Toll-Like Receptor 5 , Tumor Necrosis Factor-alpha
17.
Polymers (Basel) ; 14(16)2022 Aug 10.
Article in English | MEDLINE | ID: covidwho-1979341

ABSTRACT

To effectively counter the evolving threat of SARS-CoV-2 variants, modifications and/or redesigning of mRNA vaccine construct are essentially required. Herein, the design and immunoinformatic assessment of a candidate novel mRNA vaccine construct, DOW-21, are discussed. Briefly, immunologically important domains, N-terminal domain (NTD) and receptor binding domain (RBD), of the spike protein of SARS-CoV-2 variants of concern (VOCs) and variants of interest (VOIs) were assessed for sequence, structure, and epitope variations. Based on the assessment, a novel hypothetical NTD (h-NTD) and RBD (h-RBD) were designed to hold all overlapping immune escape variations. The construct sequence was then developed, where h-NTD and h-RBD were intervened by 10-mer gly-ala repeat and the terminals were flanked by regulatory sequences for better intracellular transportation and expression of the coding regions. The protein encoded by the construct holds structural attributes (RMSD NTD: 0.42 Å; RMSD RBD: 0.15 Å) found in the respective domains of SARS-CoV-2 immune escape variants. In addition, it provides coverage to the immunogenic sites of the respective domains found in SARS-CoV-2 variants. Later, the nucleotide sequence of the construct was optimized for GC ratio (56%) and microRNA binding sites to ensure smooth translation. Post-injection antibody titer was also predicted (~12000 AU) to be robust. In summary, the construct proposed in this study could potentially provide broad spectrum coverage in relation to SARS-CoV-2 immune escape variants.

18.
In Silico Pharmacol ; 10(1): 12, 2022.
Article in English | MEDLINE | ID: covidwho-1959193

ABSTRACT

Despite the availability of COVID-19 vaccines, additional more potent vaccines are still required against the emerging variations of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In the present investigation, we have identified a promising vaccine candidate against the Omicron (B.1.1.529) using immunoinformatics approaches. Various available tools like, the Immune Epitope Database server resource, and NetCTL-1.2, have been used for the identification of the promising T-cell and B-cell epitopes. The molecular docking was performed to check the interaction of TLR-3 receptors and validated 3D model of vaccine candidate. The codon optimization was done followed by cloning using SnapGene. Finally, In-silico immune simulation profile was also checked. The identified T-cell and B-cell epitopes have been selected based on their antigenicity (VaxiJen v2.0) and, allergenicity (AllerTOP v2.0). The identified epitopes with antigenic and non-allergenic properties were fused with the specific peptide linkers. In addition, the 3D model was constructed by the PHYRE2 server and validated using ProSA-web. The validated 3D model was further docked with the Toll-like receptor 3 (TLR3) and showed good interaction with the amino acids which indicate a promising vaccine candidate against the Omicron variant of SARS-CoV-2. Finally, the codon optimization, In-silico cloning and immune simulation profile was found to be satisfactory. Overall, the designed vaccine candidate has a potential against variant of SARS-Cov-2. However, further experimental studies are required to confirm.

19.
J Genet Eng Biotechnol ; 20(1): 60, 2022 Apr 20.
Article in English | MEDLINE | ID: covidwho-1951426

ABSTRACT

BACKGROUND: The novel coronavirus (SARS-CoV-2) caused lethal infections worldwide during an unprecedented pandemic. Identification of the candidate viral epitopes is the first step in the design of vaccines against the viral infection. Several immunoinformatic approaches were employed to identify the SARS-CoV-2 epitopes that bind specifically with the major histocompatibility molecules class I (MHC-I). We utilized immunoinformatic tools to analyze the whole viral protein sequences, to identify the SARS-CoV-2 epitopes responsible for binding to the most frequent human leukocyte antigen (HLA) alleles in the Egyptian population. These alleles were also found with high frequency in other populations worldwide. RESULTS: Molecular docking approach showed that using the co-crystallized MHC-I and T cell receptor (TCR) instead of using MHC-I structure only, significantly enhanced docking scores and stabilized the conformation, as well as the binding affinity of the identified SARS-CoV-2 epitopes. Our approach directly predicts 7 potential vaccine subunits from the available SARS-CoV-2 spike and ORF1ab protein sequence. This prediction has been confirmed by published experimentally validated and in silico predicted spike epitope. On the other hand, we predicted novel epitopes (RDLPQGFSA and FCLEASFNY) showing high docking scores and antigenicity response with both MHC-I and TCR. Moreover, antigenicity, allergenicity, toxicity, and physicochemical properties of the predicted SARS-CoV-2 epitopes were evaluated via state-of-the-art bioinformatic approaches, showing high efficacy of the proposed epitopes as a vaccine candidate. CONCLUSION: Our predicted SARS-CoV-2 epitopes can facilitate vaccine development to enhance the immunogenicity against SARS-CoV-2 and provide supportive data for further experimental validation. Our proposed molecular docking approach of exploiting both MHC and TCR structures can be used to identify potential epitopes for most microbial pathogens, provided the crystal structure of MHC co-crystallized with TCR.

20.
Vaccines (Basel) ; 10(7)2022 Jul 19.
Article in English | MEDLINE | ID: covidwho-1939066

ABSTRACT

Zoonotic coronaviruses (CoV) have emerged twice and have caused severe respiratory diseases in humans. Due to the frequent outbreaks of different human coronaviruses (HCoVs), the development of a pan-HCoV vaccine is of great importance. Various conserved epitopes shared by HCoVs are reported to induce cross-reactive T-cell responses. Therefore, this study aimed to design a multi-epitope vaccine, targeting the HCoV spike protein. Genetic analysis revealed that the spike region is highly conserved among SARS-CoV-2, bat SL-CoV, and SARS-CoV. By employing the immunoinformatic approach, we prioritized 20 MHC I and 10 MHCII conserved epitopes to design a multi-epitope vaccine. This vaccine candidate is anticipated to strongly elicit both humoral and cell-mediated immune responses. These results warrant further development of this vaccine into real-world application.

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