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.

Computational Study of Asian Propolis Compounds as Potential Anti-Type 2 Diabetes Mellitus Agents by Using Inverse Virtual Screening with the DIA-DB Web Server, Tanimoto Similarity Analysis, and Molecular Dynamic Simulation.

Propolis contains a wide range of pharmacological activities because of their various bioactive compounds. The beneficial effect of propolis is interesting for treating type-2 diabetes mellitus (T2DM) owing to dysregulation of multiple metabolic processes. In this study, 275 of 658 Asian propolis compounds were evaluated as potential anti-T2DM agents using the DIA-DB web server towards 18 known anti-diabetes protein targets. More than 20% of all compounds could bind to more than five diabetes targets with high binding affinity (<−9.0 kcal/mol). Filtering with physicochemical and pharmacokinetic properties, including ADMET parameters, 12 compounds were identified as potential anti-T2DM with favorable ADMET properties. Six of those compounds, (2R)-7,4'-dihydroxy-5-methoxy-8-methylflavone; (RR)-(+)-3'-senecioylkhellactone; 2',4',6'-trihydroxy chalcone; alpinetin; pinobanksin-3-O-butyrate; and pinocembrin-5-methyl ether were first reported as anti-T2DM agents. We identified the significant T2DM targets of Asian propolis, namely retinol-binding protein-4 (RBP4) and aldose reductase (AKR1B1) that have important roles in insulin sensitivity and diabetes complication, respectively. Molecular dynamic simulations showed stable interaction of selected propolis compounds in the active site of RBP4 and AKR1B1. These findings suggest that Asian propolis compound may be effective for treatment of T2DM by targeting RBP4 and AKR1B1.

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.