Receptor-ligand based molecular interaction to discover adjuvant for immune cell TLRs to develop next-generation vaccine

Subtractive Proteomics and Reverse-Vaccinology Approaches for Novel Drug Target Identification and Chimeric Vaccine Development against Bartonella henselae Strain Houston-1

Bartonella henselae is a Gram-negative bacterium causing a variety of clinical symptoms, ranging from cat-scratch disease to severe systemic infections, and it is primarily transmitted by infected fleas. Its status as an emerging zoonotic pathogen and its capacity to persist within host erythrocytes and endothelial cells emphasize its clinical significance. Despite progress in understanding its pathogenesis, limited knowledge exists about the virulence factors and regulatory mechanisms specific to the B. henselae strain Houston-1. Exploring these aspects is crucial for targeted therapeutic strategies against this versatile pathogen. Using reverse-vaccinology-based subtractive proteomics, this research aimed to identify the most antigenic proteins for formulating a multi-epitope vaccine against the B. henselae strain Houston-1. One crucial virulent and antigenic protein, the PAS domain-containing sensor histidine kinase protein, was identified. Subsequently, the identification of B-cell and T-cell epitopes for the specified protein was carried out and the evaluated epitopes were checked for their antigenicity, allergenicity, solubility, MHC binding capability, and toxicity. The filtered epitopes were merged using linkers and an adjuvant to create a multi-epitope vaccine construct. The structure was then refined, with 92.3% of amino acids falling within the allowed regions. Docking of the human receptor (TLR4) with the vaccine construct was performed and demonstrated a binding energy of -1047.2 Kcal/mol with more interactions. Molecular dynamic simulations confirmed the stability of this docked complex, emphasizing the conformation and interactions between the molecules. Further experimental validation is necessary to evaluate its effectiveness against B. henselae.

Unraveling the Complexities of Toll-like Receptors: From Molecular Mechanisms to Clinical Applications

Toll-like receptors (TLRs) are vital components of the innate immune system, serving as the first line of defense against pathogens by recognizing a wide array of molecular patterns. This review summarizes the critical roles of TLRs in immune surveillance and disease pathogenesis, focusing on their structure, signaling pathways, and implications in various disorders. We discuss the molecular intricacies of TLRs, including their ligand specificity, signaling cascades, and the functional consequences of their activation. The involvement of TLRs in infectious diseases, autoimmunity, chronic inflammation, and cancer is explored, highlighting their potential as therapeutic targets. We also examine recent advancements in TLR research, such as the development of specific agonists and antagonists, and their application in immunotherapy and vaccine development. Furthermore, we address the challenges and controversies surrounding TLR research and outline future directions, including the integration of computational modeling and personalized medicine approaches. In conclusion, TLRs represent a promising frontier in medical research, with the potential to significantly impact the development of novel therapeutic strategies for a wide range of diseases.

DC-SIGN of Largemouth Bass (Micropterus salmoides) Mediates Immune Functions against Aeromonas hydrophila through Collaboration with the TLR Signaling Pathway

C-type lectins in organisms play an important role in the process of innate immunity. In this study, a C-type lectin belonging to the DC-SIGN class of Micropterus salmoides was identified. MsDC-SIGN is classified as a type II transmembrane protein. The extracellular segment of MsDC-SIGN possesses a coiled-coil region and a carbohydrate recognition domain (CRD). The key amino acid motifs of the extracellular CRD of MsDC-SIGN in Ca2+-binding site 2 were EPN (Glu-Pro-Asn) and WYD (Trp-Tyr-Asp). MsDC-SIGN-CRD can bind to four pathogen-associated molecular patterns (PAMPs), including lipopolysaccharide (LPS), glucan, peptidoglycan (PGN), and mannan. Moreover, it can also bind to Gram-positive, Gram-negative bacteria, and fungi. Its CRD can agglutinate microbes and displays D-mannose and D-galactose binding specificity. MsDC-SIGN was distributed in seven tissues of the largemouth bass, among which the highest expression was observed in the liver, followed by the spleen and intestine. Additionally, MsDC-SIGN was present on the membrane of M. salmoides leukocytes, thereby augmenting the phagocytic activity against bacteria. In a subsequent investigation, the expression patterns of the MsDC-SIGN gene and key genes associated with the TLR signaling pathway (TLR4, NF-κB, and IL10) exhibited an up-regulated expression response to the stimulation of Aeromonas hydrophila. Furthermore, through RNA interference of MsDC-SIGN, the expression level of the DC-SIGN signaling pathway-related gene (RAF1) and key genes associated with the TLR signaling pathway (TLR4, NF-κB, and IL10) was decreased. Therefore, MsDC-SIGN plays a pivotal role in the immune defense against A. hydrophila by modulating the TLR signaling pathway.

Exploring structural engineering approach to formulate and characterize next-generation adjuvants

It is critical to emphasize the importance of vaccination as it protects us against harmful pathogens. Despite significant progress in vaccine development, there is an ongoing need to develop vaccines that are not only safe but also highly effective in protecting against severe infections. Subunit vaccines are generally safe, but they frequently fail to elicit strong immune responses. As a result, there is a need to improve vaccine effectiveness by combining them with adjuvants, which have the potential to boost the immune system many folds. The process of developing these adjuvants requires searching for molecules capable of activating the immune system, combining these promising compounds with an antigen, and then testing this combination using animal models before approving it for clinical use. Liposomal adjuvants work as delivery adjuvants and its activity depends on certain parameters such as surface charge, vesicle size, surface modification and route of administration. Self-assembly property of peptide adjuvants and discovery of hybrid peptides have widened the scope of peptides in vaccine formulations. Since most pathogenic molecules are not peptide based, phage display technique allows for screening peptide mimics for such pathogens that have potential as adjuvants. This chapter discusses about peptide and liposome-based adjuvants focusing on their properties imparting adjuvanticity along with the methods of formulating them. Methods of adjuvant characterization important for an adjuvant to be approved for clinical trials are also discussed. These include assays for cytotoxicity, T-lymphocyte proliferation, dendritic cell maturation, cytokine and antibody production, toll-like receptor dependent signaling and adjuvant half-life.

Riding the wave of innovation: immunoinformatics in fish disease control

The spread of infectious illnesses has been a significant factor restricting aquaculture production. To maximise aquatic animal health, vaccination tactics are very successful and cost-efficient for protecting fish and aquaculture animals against many disease pathogens. However, due to the increasing number of immunological cases and their complexity, it is impossible to manage, analyse, visualise, and interpret such data without the assistance of advanced computational techniques. Hence, the use of immunoinformatics tools is crucial, as they not only facilitate the management of massive amounts of data but also greatly contribute to the creation of fresh hypotheses regarding immune responses. In recent years, advances in biotechnology and immunoinformatics have opened up new research avenues for generating novel vaccines and enhancing existing vaccinations against outbreaks of infectious illnesses, thereby reducing aquaculture losses. This review focuses on understanding in silico epitope-based vaccine design, the creation of multi-epitope vaccines, the molecular interaction of immunogenic vaccines, and the application of immunoinformatics in fish disease based on the frequency of their application and reliable results. It is believed that it can bridge the gap between experimental and computational approaches and reduce the need for experimental research, so that only wet laboratory testing integrated with in silico techniques may yield highly promising results and be useful for the development of vaccines for fish.

Immunoinformatics aided designing of a next generation poly-epitope vaccine against uropathogenic Escherichia coli to combat urinary tract infections

Urinary tract infections (UTIs) are the second most prevalent bacterial infections and uropathogenic Escherichia coli (UPEC) stands among the primary causative agents of UTIs. The usage of antibiotics is the routine therapy being used in various countries to treat UTIs but becoming ineffective because of increasing antibiotic resistance among UPEC strains. Thus, there must be the development of some alternative treatment strategies such as vaccine development against UPEC. In the following study, pan-genomics along with reverse vaccinology approaches is used under the framework of bioinformatics for the identification of core putative vaccine candidates, employing 307 UPEC genomes (complete and draft), available publicly. A total of nine T-cell epitopes (derived from B-cells) of both MHC classes (I and II), were prioritized among three potential protein candidates. These epitopes were then docked together by using linkers (GPGPG and AAY) and an adjuvant (Cholera Toxin B) to form a poly-valent vaccine construct. The chimeric vaccine construct was undergone by molecular modelling, further refinement and energy minimization. We predicted positive results of the vaccine construct in immune simulations with significantly high levels of immune cells. The protein-protein docking analysis of vaccine construct with toll-like receptors predicted efficient binding, which was further validated by molecular dynamics simulation of vaccine construct with TLR-2 and TLR-4 at 120 ns, resulting in stable complexes' conformation throughout the simulation run. Overall, the vaccine construct demonstrated positive antigenic response. In future, this chimeric vaccine construct or the identified epitopes could be experimentally validated for the development of UPEC vaccines against UTIs.Communicated by Ramaswamy H. Sarma.

Multi-pathogen based chimeric vaccine to fight against COVID-19 and concomitant coinfections

BACKGROUND

COVID-19 has proved to be a fatal disease of the year 2020, due to which thousands of people globally have lost their lives, and still, the infection cases are at a high rate. Experimental studies suggested that SARS-CoV-2 interacts with various microorganisms, and this coinfection is accountable for the augmentation of infection severity.

METHODS AND RESULTS

In this study, we have designed a multi-pathogen vaccine by involving the immunogenic proteins from S. pneumonia, H. influenza, and M. tuberculosis, as they are dominantly associated with SARS-CoV-2. A total of 8 antigenic protein sequences were selected to predict B-cell, HTL, and CTL epitopes restricted to the most prevalent HLA alleles. The selected epitopes were antigenic, non-allergenic, and non-toxic and were linked with adjuvant and linkers to make the vaccine protein more immunogenic, stable, and flexible. The tertiary structure, Ramachandran plot, and discontinuous B-cell epitopes were predicted. Docking and MD simulation study has shown efficient binding of the chimeric vaccine with the TLR4 receptor.

CONCLUSION

The in silico immune simulation analysis has shown a high level of cytokines and IgG after a three-dose injection. Hence, this strategy could be a better way to decrease the disease's severity and could be used as a weapon to prevent this pandemic.

Structural vaccinology-based design of multi-epitopes vaccine against Streptococcus gordonii and validation using molecular modeling and immune simulation approaches

Streptococcus gordonii is an oral bacterium colonizing the dental cavity and leading to plaque formation. This pervasive colonizer is also the etiologic agent of bacterial endocarditis and has a major role in infective endocarditis. The bacteria reach the heart through oral bleeding, leading to inflammation of cardiovascular valves. Over the past 50 years, it has shown a significant pathogenic role in immunocompromised and neutropenic patients. Since antibiotic resistance has created prophylaxis failure towards infective endocarditis, a potent therapeutic candidate is needed. Therefore, multi-epitopes vaccine offers advantages over the other approaches. Thus, herein, numerous molecular-omics tools were exploited to mine immunogenic peptides, i.e., T-cell and B-cell epitopes, and construct a vaccine sequence. Our findings revealed a total of 24 epitopes, including CTL, HTL, and B-cell are responsible for imparting immune responses, which were combined with the help of different linkers, and MEVC was constructed. Multifactorial validation of the candidate vaccine was performed to minimize the risk factors. The final sequence was docked with TLR2 to validate its conformation compatibility with receptor and long-term interactions stability. Our analysis revealed that the vaccine construct is immunogenic and non-allergenic. The construct also established various contacts with the immune receptor. Finally, the vaccine sequence was reverse-translated, optimized for codon usage, and analyzed for expression in the Escherichia coli K12 strain. Maximum expression was noted with a CAI score of 0.95. In silico immune simulation revealed that the antigen was neutralized on the 3rd day after injection. In conclusion, the current study warrants validation of the vaccine construct both in in vitro and in vivo models for accurate therapeutic intervention.

A subunit vaccine against pneumonia: targeting Streptococcus pneumoniae and Klebsiella pneumoniae

Community-acquired pneumonia is primarily caused by Streptococcus pneumoniae and Klebsiella pneumoniae, two pathogens that have high morbidity and mortality rates. This is largely due to bacterial resistance development against current antibiotics and the lack of effective vaccines. The objective of this work was to develop an immunogenic multi-epitope subunit vaccine capable of eliciting a robust immune response against S. pneumoniae and K. pneumoniae. The targeted proteins were the pneumococcal surface proteins (PspA and PspC) and choline-binding protein (CbpA) of S. pneumoniae and the outer membrane proteins (OmpA and OmpW) of K. pneumoniae. Different computational approaches and various immune filters were employed for designing a vaccine. The immunogenicity and safety of the vaccine were evaluated by utilizing many physicochemical and antigenic profiles. To improve structural stability, disulfide engineering was applied to a portion of the vaccine structure with high mobility. Molecular docking was performed to examine the binding affinities and biological interactions at the atomic level between the vaccine and Toll-like receptors (TLR2 and 4). Further, the dynamic stabilities of the vaccine and TLRs complexes were investigated by molecular dynamics simulations. While the immune response induction capability of the vaccine was assessed by the immune simulation study. Vaccine translation and expression efficiency was determined through an in silico cloning experiment utilizing the pET28a(+) plasmid vector. The obtained results revealed that the designed vaccine is structurally stable and able to generate an effective immune response to combat pneumococcal infection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13721-023-00416-3.

Hydrogel-guided strategies to stimulate an effective immune response for vaccine-based cancer immunotherapy

Cancer vaccines have attracted widespread interest in tumor therapy because of the potential to induce an effective antitumor immune response. However, many challenges including weak immunogenicity, off-target effects, and immunosuppressive microenvironments have prevented their broad clinical translation. To overcome these difficulties, effective delivery systems have been designed for cancer vaccines. As carriers in cancer vaccine delivery systems, hydrogels have gained substantial attention because they can encapsulate a variety of antigens/immunomodulators and protect them from degradation. This enables hydrogels to simultaneously reverse immunosuppression and stimulate the immune response. Meanwhile, the controlled release properties of hydrogels allow for precise temporal and spatial release of loads in situ to further enhance the immune response of cancer vaccines. Therefore, this review summarizes the classification of cancer vaccines, highlights the strategies of hydrogel-based cancer vaccines, and provides some insights into the future development of hydrogel-based cancer vaccines.

Vaccinomics-Aided Development of a Next-Generation Chimeric Vaccine against an Emerging Threat: Mycoplasma genitalium

Mycoplasma genitalium, besides urethritis, causes a number of other sexually transmitted diseases, posing a significant health threat to both men and women, particularly in developing countries. In light of the rapid appearance of multidrug-resistant strains, M. genitalium is regarded as an emerging threat and has been placed on the CDC's "watch list". Hence, a protective vaccine is essential for combating this pathogen. In this study, we utilized reverse vaccinology to develop a chimeric vaccine against M. genitalium by identifying vaccine targets from the reference proteome (Strain G-37) of this pathogen. A multiepitope vaccine was developed using proteins that are non-toxic, non-allergic, and non-homologous to human proteins. Several bioinformatic tools identified linear and non-linear B-cell epitopes, as well as MHC epitopes belonging to classes I and II, from the putative vaccine target proteins. The epitopes that showed promiscuity among the various servers were shortlisted and subsequently selected for further investigation based on an immunoinformatic analysis. Using GPGPG, AAY, and KK linkers, the shortlisted epitope sequences were assembled to create a chimeric construct. A GPI anchor protein immunomodulating adjuvant was adjoined to the vaccine construct's N-terminus through the EAAK linker so as to improve the overall immunogenicity. For further investigations of the designed construct, various bioinformatic tools were employed to study the physicochemical properties, immune profile, solubility, and allergenicity profile. A tertiary chimeric design was computationally modeled using I-TASSER and Robetta and was subsequently refined through GalaxyRefine. ProSA-Web was exploited to corroborate the quality of the construct by detecting errors and the Ramachandran plot was used to identify possible quality issues. Simulation studies of the molecular dynamics demonstrated the robustness and flexibility of the designed construct. Following the successful docking of the designed model to the immune receptors, the construct was computationally cloned into Escherichia coli plasmids to affirm the efficient expression of the designed construct in a biological system.

Vaccinomics to Design a Multiepitope Vaccine against Legionella pneumophila

Legionella pneumophila is found in the natural aquatic environment and can resist a wide range of environmental conditions. There are around fifty species of Legionella, at least twenty-four of which are directly linked to infections in humans. L. pneumophila is the cause of Legionnaires' disease, a potentially lethal form of pneumonia. By blocking phagosome-lysosome fusion, L. pneumophila lives and proliferates inside macrophages. For this disease, there is presently no authorized multiepitope vaccine available. For the multi-epitope-based vaccine (MEBV), the best antigenic candidates were identified using immunoinformatics and subtractive proteomic techniques. Several immunoinformatics methods were utilized to predict B and T cell epitopes from vaccine candidate proteins. To construct an in silico vaccine, epitopes (07 CTL, 03 HTL, and 07 LBL) were carefully selected and docked with MHC molecules (MHC-I and MHC-II) and human TLR4 molecules. To increase the immunological response, the vaccine was combined with a 50S ribosomal adjuvant. To maximize vaccine protein expression, MEBV was cloned and reverse-translated in Escherichia coli. To prove the MEBV's efficacy, more experimental validation is required. After its development, the resulting vaccine is greatly hoped to aid in the prevention of L. pneumophila infections.

In silico design of multi-epitope-based peptide vaccine against SARS-CoV-2 using its spike protein

SARS-CoV-2 has been efficient in ensuring that many countries are brought to a standstill. With repercussions ranging from rampant mortality, fear, paranoia, and economic recession, the virus has brought together countries to look at possible therapeutic countermeasures. With prophylactic interventions possibly months away from being particularly effective, a slew of measures and possibilities concerning the design of vaccines are being worked upon. We attempted a structure-based approach utilizing a combination of epitope prediction servers and Molecular dynamic (MD) simulations to develop a multi-epitope-based subunit vaccine that involves the two subunits of the spike glycoprotein of SARS-CoV-2 (S1 and S2) coupled with a substantially effective chimeric adjuvant to create stable vaccine constructs. The designed constructs were evaluated based on their docking with Toll-Like Receptor (TLR) 4. Our findings provide an epitope-based peptide fragment that can be a potential candidate for the development of a vaccine against SARS-CoV-2. Recent experimental studies based on determining immunodominant regions across the spike glycoprotein of SARS-CoV-2 indicate the presence of the predicted epitopes included in this study.Communicated by Ramaswamy H. Sarma.

Engineering a multi epitope vaccine against SARS-CoV-2 by exploiting its non structural and structural proteins

SARS-CoV-2, the causative agent behind the ongoing pandemic exhibits an enhanced potential for infection when compared to its related family members- the SARS-CoV and MERS-CoV; which have caused similar disease outbreaks in the past. The severity of the global health burden, increasing mortality rate and the emergent economic crisis urgently demands the development of next generation vaccines. Amongst such emergent next generation vaccines are the multi-epitope subunit vaccines, which hold promise in combating deadly pathogens. In this study we have exploited immunoinformatics applications to delineate a vaccine candidate possessing multiple B and T cells epitopes by utilizing the SARS-CoV-2 non structural and structural proteins. The antigenicity potential, safety, structural stability and the production feasibility of the designed construct was evaluated computationally. Furthermore, due to the known role of human TLR-3 immune receptor in viral sensing, which facilitates host cells activation for an immune response, the vaccine construct was examined for its binding efficiency using molecular docking and molecular dynamics simulation studies, which resulted in strong and stable interactions. Finally, the immune simulation studies suggested an effective immune response on vaccine administration. Overall, the immunoinformatics analysis advocates that the proposed vaccine candidate is safe and immunogenic and therefore can be pushed as a lead for in vitro and in vivo investigations.Communicated by Ramaswamy H. Sarma.

Design of a Multi-epitope Vaccine Against Acinetobacter baumannii Using Immunoinformatics Approach

Acinetobacter baumannii is one of the most successful pathogens causing nosocomial infections and has significantly multidrug-resistant. So far, there are no certain treatments to protect against infection with A. baumannii, therefore an effective A. baumannii vaccine needed. The purpose of this study was to predict antigenic epitopes of CarO protein for designing the A. baumannii vaccine using immunoinformatics analysis. CarO protein is one of the most important factors in the resistance against the antibiotic Carbapenem. In this study, T and B-cell epitopes of CarO protein were predicted and screened based on the antigenicity, toxicity, allergenicity features. The epitopes were linked by suitable linkers. Four different adjuvants were attached to the vaccine constructs which among them, vaccine construct 3 was chosen to predict the secondary and the 3D structure of the vaccine. The refinement process was performed to improve the quality of the 3D model structure; the validation process is performed using the Ramachandran plot and ProSA z-score. The designed vaccine's binding affinity to six various HLA molecules and TLR 2 and TLR4 were evaluated by molecular docking. Finally, in silico gene cloning was performed in the pET28a (+) vector. The findings suggest that the vaccine may be a promising vaccine to prevent A. baumannii infection.

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.

Multiple epitope-based vaccine prediction against SARS-CoV-2 spike glycoprotein

The global emergence of novel coronavirus disease and its rapid global expansion over a short span of time require effective countermeasures to combat it. Development of a specific vaccine can induce an optimal antibody response, thus providing immunity against it. Our study proposes a detailed and comprehensive immunoinformatic approach that can be applied to the currently available coronavirus protein data in the online server for vaccine candidate development. We have identified the receptor binding domain (RBD) of structural spike protein (S1) as a potential target for immunity against COVID- 19 infection. Epitope prediction illustrated cytotoxic T-cell epitopes, helper T-cell epitopes, and B-cell epitopes associated with the target protein. These were joined through specific linkers along with adjuvant beta-defensin located at the N-terminal to create a multi epitope subunit vaccine (MESV). The specificity in the binding of the devised vaccine candidate to the TLR-3 immune cell receptor was evaluated via molecular docking interaction studies. Good docking score combined with robust interactions in the binding cavity certified the stringency of the engineered vaccine. Molecular dynamics simulation data showed minimal variation of the root-mean square deviations (RMSDs) and root-mean-square fluctuations (RMSFs) which confirmed the interaction stability. These results obtained from various in-silico experiments indicate the potency of this vaccine candidate as a probable therapeutic agent against COVID-19. Vaccination strategies targeting conserved epitope-based immune response would be beneficial in providing cross protection across beta-coronaviruses, and such vaccines would be resistant to the ever-evolving viruses.Communicated by Ramaswamy H. Sarma.

High throughput and comprehensive approach to develop multiepitope vaccine against minacious COVID-19

The ongoing enigmatic COVID-19 outbreak, first reported from Wuhan, China, on last day of the year 2019, which has spread to 213 countries, territories/areas till 28th April 2020, threatens hundreds of thousands human souls. This devastating viral infection has stimulated the urgent development of viable vaccine against COVID-19 across the research institutes around the globe. The World Health Organization (WHO) has also confirmed that the recent pandemic is causing Public Health Emergency of International apprehension. Moreover, the earlier two pathogenic SARS-CoV and MERS-CoV and many others yet to be identified pose a universal menace. Here, in this piece of work, we have utilized an in silico structural biology and advanced immunoinformatic strategies to devise a multi-epitope subunit vaccine against ongoing COVID-19 infection. The engineered vaccine sequence is adjuvanted with ß-3 defensin and comprised of B-cell epitopes, HTL epitopes and CTL epitopes. This is very likely that the vaccine will be able to elicit the strong immune response. Further, specific binding of the engineered vaccine and immune cell receptor TLR3 was estimated by molecular interaction studies. Strong interaction in the binding groove as well as good docking scores affirmed the stringency of engineered vaccine. The interaction is stable with minimal deviation in root-mean square deviation and root-mean-square fluctuation was confirmed by the molecular dynamics simulation experiment. The immune-simulation by C-ImmSim server, which mimics the natural immune environment, yielded more potent immune response data of B-cells, Th cells, Tc cells and IgG for vaccine. The encouraging data obtained from the various in-silico works indicated this vaccine as an effective therapeutic against COVID-19.