Immunoinformatic design of a COVID-19 subunit vaccine using entire structural immunogenic epitopes of SARS-CoV-2

Abstract

Coronavirus disease 2019 (COVID-19) is an acute pneumonic disease, with no prophylactic or specific therapeutical solution. Effective and rapid countermeasure against the spread of the disease’s associated virus, SARS-CoV-2, requires to incorporate the computational approach. In this study, we employed various immunoinformatics tools to design a multi-epitope vaccine polypeptide with the highest potential for activating the human immune system against SARS-CoV-2. The initial epitope set was extracted from the whole set of viral structural proteins. Potential non-toxic and non-allergenic T-cell and B-cell binding and cytokine inducing epitopes were then identified through a priori prediction. Selected epitopes were bound to each other with appropriate linkers, followed by appending a suitable adjuvant to increase the immunogenicity of the vaccine polypeptide. Molecular modelling of the 3D structure of the vaccine construct, docking, molecular dynamics simulations and free energy calculations confirmed that the vaccine peptide had high affinity for Toll-like receptor 3 binding, and that the vaccine-receptor complex was highly stable. As our vaccine polypeptide design captures the advantages of structural epitopes and simultaneously integrates precautions to avoid relevant side effects, it is suggested to be promising for elicitation of an effective and safe immune response against SARS-CoV-2 in vivo.

Bioinformatic prediction of immunodominant regions in spike protein for early diagnosis of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)

“…To date, several studies using predictive algorithms to analyze SARS-CoV-2 have been reported ( Alam et al, 2020 ; Behmard et al, 2020 ; Can et al, 2020 ; Chen et al, 2020a ; Dong et al, 2020 ; Poran et al, 2020 ; Saha, Ghosh & Burra, 2021 ; Sohail et al, 2021 ). However, most of these bioinformatics analyses against SARS-CoV-2 intended to develop effective vaccines to prevent infection and the identified sequences possess high homology with other viruses, especially SARS-CoV ( Bhattacharya et al, 2020 ; Chen et al, 2020a ; Robson, 2020 ).…”

Nano-Enabled COVID-19 Vaccines: Meeting the Challenges of Durable Antibody Plus Cellular Immunity and Immune Escape

“… 3 , 30 , 64 , 99 , 103 The ability to design new peptide-based vaccines has received a major boost from the availability of epitope-mapping tools such as the immune epitope database (IEDB) for predicting B- and T-cell epitope sequences ( Table 3 ). 106 , 107 In addition, a number of immunoinformatics approaches have emerged to facilitate the prediction-making process for multiepitope vaccine design, 30 , 64 , 65 , 94 , 100 , 102 , 104 , 108 including computational tools that predict epitope binding to diverse HLA alleles ( e.g ., the IEDB population coverage tool). 107 It is also possible to use HLA ligandome analysis for calculating the probability of peptide interactions with consensus motifs, including 3D predictions for viral peptide docking to cytokine-inducing receptors ( e.g ., TLR2 and TLR4).…”

“… 109 Collectively, these tools now enable multiepitope vaccine design to test the feasibility of obtaining cooperative B- and T-cell interactions, as well as possibly soliciting specific CD4 + and CD8 + T-cell responses (discussed in a later section). 30 , 64 , 65 , 102 , 104 , 108 , 110 …”

“… 154 The selection of potentially synergistic epitope combinations will benefit from the use immunoinformatics tools, as described above. 65 , 94 , 99 , 100 , 102 , 104 , 109 This approach could include the use of tools that enable the design of appropriate linker and codon adjustment strategies for minigene design. 64 , 102 Ultimately, it should be possible to use suitably designed nanocarriers to deliver multiepitope peptide sequences or minigene nucleic acid constructs to the host immune system for antigen presentation.…”

In-Silico Design of Envelope based Multi-epitope Vaccine Candidate Against Kyasanur Forest Disease Virus

“…These epitopes contains short amino acid sequence that can induce more direct and specific immune response, which overcome the disadvantages of live attenuated vaccines 11 . In-silico based epitope prediction methods have reduced the time consumption and money spent on false epitope candidates and this tools has been employed to develop multiepitope vaccine against several diseases such as Dengue, SARS-CoV-2, Mycobacterium tuberculosis, Steaphylococcus aureus etc [12][13][14][15][16][17] . Hence, the present investigation has adapted this approach for rational design of epitope-based vaccine against KFDV.…”