Immunoinformatics Study: Multi-Epitope Based Vaccine Design from SARS-CoV-2 Spike Glycoprotein.

The coronavirus disease 2019 outbreak has become a huge challenge in the human sector for the past two years. The coronavirus is capable of mutating at a higher rate than other viruses. Thus, an approach for creating an effective vaccine is still needed to induce antibodies against multiple variants with lower side effects. Currently, there is a lack of research on designing a multiepitope of the COVID-19 spike protein for the Indonesian population with comprehensive immunoinformatic analysis. Therefore, this study aimed to design a multiepitope-based vaccine for the Indonesian population using an immunoinformatic approach. This study was conducted using the SARS-CoV-2 spike glycoprotein sequences from Indonesia that were retrieved from the GISAID database. Three SARS-CoV-2 sequences, with IDs of EIJK-61453, UGM0002, and B.1.1.7 were selected. The CD8+ cytotoxic T-cell lymphocyte (CTL) epitope, CD4+ helper T lymphocyte (HTL) epitope, B-cell epitope, and IFN-γ production were predicted. After modeling the vaccines, molecular docking, molecular dynamics, in silico immune simulations, and plasmid vector design were performed. The designed vaccine is antigenic, non-allergenic, non-toxic, capable of inducing IFN-γ with a population reach of 86.29% in Indonesia, and has good stability during molecular dynamics and immune simulation. Hence, this vaccine model is recommended to be investigated for further study.

In silico investigation of potential inhibitors to main protease and spike protein of SARS-CoV-2 in propolis.

Docking analysis of propolis's natural compound was successfully performed against SARS-CoV-2 main protease (Mpro) and spike protein subunit 2 (S2). Initially, the propolis's protein was screened using chromatography analysis and successfully identified 22 compounds in the propolis. Four compounds were further investigated, i.e., neoblavaisoflavone, methylophiopogonone A, 3'-Methoxydaidzin, and genistin. The binding affinity of 3'-Methoxydaidzin was -7.7 kcal/mol, which is similar to nelfinavir (control), while the others were -7.6 kcal/mol. However, we found the key residue of Glu A:166 in the methylophiopogonone A and genistin, even though the predicted binding energy slightly higher than nelfinavir. In contrast, the predicted binding affinity of neoblavaisoflavone, methylophiopogonone A, 3'-Methoxydaidzin, and genistin against S2 were -8.1, -8.2, -8.3, and -8.3 kcal/mol, respectively, which is far below of the control (pravastatin, -7.3 kcal/mol). Instead of conventional hydrogen bonding, the π bonding influenced the binding affinity against S2. The results reveal that this is the first report about methylophiopogonone A, 3'-Methoxydaidzin, and genistin as candidates for anti-viral agents. Those compounds can then be further explored and used as a parent backbone molecule to develop a new supplementation for preventing SARS-CoV-2 infections during COVID-19 outbreaks.