Hansa Regar

Bio: Hansa Regar is an academic researcher from Central University of Rajasthan. The author has contributed to research in topics: Immune receptor & Adjuvant. The author has an hindex of 1, co-authored 1 publications receiving 10 citations.

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

Abstract: 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.

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

Abstract: Coronavirus disease 2019 (COVID-19) associated pneumonia caused by severe acute respiratory coronavirus 2 (SARS-COV-2) was first reported in Wuhan, China in December 2019. Till date, no vaccine or completely effective drug is available for the cure of COVID-19. Therefore, an effective vaccine against SARS-COV-2 is needed to be design. This study was conducted to design an effective multi-epitope vaccine (MEV) against SARS-COV-2. Seven antigenic proteins were taken as a target and epitopes (B cell, IFN-γ and T cell) were predicted. Highly antigenic and overlapping epitopes were shortlisted. Selected T cell epitopes indicated significant interactions with the HLA-binding alleles and 99.29% coverage of the world’s population. Finally, 505 amino acids long MEV was designed by connecting sixteen MHC class I and twelve MHC class II epitopes with suitable linkers and adjuvant. Linkers and adjuvant were added to enhance the immunogenicity response of the vaccine. The allergenicity, physiochemical properties, antigenicity and structural details of MEV were analyzed in order to ensure safety and immunogenicity. MEV construct was non-allergenic and antigenic. Molecular docking demonstrated a stable and strong binding affinity of MEV with TLR3 and TLR8. Codon optimization and in silico cloning ensured increased expression in the Escherichia coli K-12 system. However, to ensure its safety and immunogenic profile, the proposed vaccine needs to be experimentally validated.

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

Abstract: 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.

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

Abstract: 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.