Phytochemical Profile, Antioxidant, Enzyme Inhibition, Acute Toxicity, In Silico Molecular Docking and Dynamic Analysis of Apis mellifera Propolis as Antidiabetic Supplement

This study aims to identification of phytochemical profile of Apis mellifera propolis and explore potential of its anti-diabetic activity through inhibition on α-amylase (α-AE), α-glucosidase(α-GE) and finally identified the novel antidiabetic compounds from propolis. Apis mellifera propolis extract (AMPE) exhibited elevated polyphenol 33.26 ± 0.17 (mg GAE/g) and flavonoid (15.45 ± 0.13 mg RE/g), while its also indicated moderate strong antioxidant activity (EC50 793.09 ±1.94 µg/ml). This study found that AMPE displayed promising α-AE and α-GE inhibition through in vitro study. Based on LC-MS/MS screening, 18 unique AMPE compounds were identified, majorly belonging to anthraquinone and flavonoid compounds. In silico study determined that 8 compounds of AMPE compounds exhibited strong binding to α-AE, interacting to catalytic residue of ASP197. Moreover, 2 compounds exhibit potential inhibition of α-AG, by interacting to crucial amino acids of ARG315, ASP352, and ASP69. Finally, we suggested 2,7-Dihydroxy-1-(p-hydroxybenzyl)-4-methoxy-9,10-dihydrophenanthrene and 3(3-(3,4-Dihydroxybenzyl)-7-hydroxychroman-4-one as novel inhibitors of α-AE and α-GE. Notably, these compounds were initially discovered in Apis mellifera propolis, and molecular dynamic analysis confirmed their stable binding with both enzymes over 100 ns simulations. In vivo acute toxicity test reveals AMPE as a practically non-toxic product with LD50 value of 16050mg/kg.

Revealing Propolis Potential Activity on Inhibiting Estrogen Receptor and Heat Shock Protein 90 Overexpressed in Breast Cancer by Bioinformatics Approaches

Breast cancer is the most commonly diagnosed cancer globally, with the highest incidence of breast cancer occurring in Asian countries including Indonesia. Among the types of breast cancer, the estrogen receptor (ER)-positive subtype which is prominent with estrogen receptor alpha (ERα) and heat shock protein 90 (HSP90) overexpression genes becomes the most prevalent than the others, approximately 75% of all breast cancer cases. ERα and HSP90 play a role in breast cancer activities including breast tumor growth, invasion, and metastasis mechanism. Propolis, a natural bee product, has been explored for its anticancer activity. However, there is lack of studies that evaluated the potential inhibitor from propolis compounds to the ERα and HSP90 proteins. Therefore, this article focuses on examining the correlation between ERα and HSP90's role in breast cancer and investigating the potential of 93 unique propolis compositions in inhibiting these genes in breast cancer using in silico approaches. This study revealed the positive correlation between ERα and HSP90 genes in breast cancer disease development. Furthermore, we also found novel potential bioactive compounds of propolis against breast cancer through binding with ERα and HSP90; they were 3',4',7-trihydroxyisoflavone and baicalein-7-O-β-D glucopyranoside, respectively. Further research on these compounds is needed to elucidate deeper mechanisms and activity in the real biological system to develop new breast cancer drug treatments.

Revealing curcumin therapeutic targets on SRC, PPARG, MAPK8 and HSP90 as liver cirrhosis therapy based on comprehensive bioinformatic study

Cirrhosis naturally progresses through three stages: compensated, decompensated, and late decompensated, which carry an elevated risk of death. Although curcumin's anti-cirrhosis effects have been studied, underlying mechanism in preventing cirrhosis progression and the correlation between curcumin's action with upregulated genes remains insufficiently explored. In this study, we employed network pharmacology approach to construct a drug-target-disease network through bioinformatics and validate the findings with molecular docking and dynamic simulation. The curcumin-targeted liver cirrhosis network encompassed 54 nodes with 282 edges in protein-protein interactions (PPI) network. By utilizing network centrality analysis, we identified eight crucial genes. KEGG enrichment pathway revealed that these crucial genes are involved in pathway of cancer, endocrine resistance, estrogen signaling, chemical carcinogenesis-receptor activation, lipid metabolism, and atherosclerosis. Notably, these eight genes predominantly participate in cancer-related pathways. Further investigation revealed upregulation of four genes and downregulation of four others in hepatocellular carcinoma patients. These upregulated genes-MAPK8, SRC, PPARG, and HSP90AA1-strongly correlated with reduced survival probability in liver hepatocellular carcinoma patients with survival times approximately under 4000 days (∼11 years). Molecular docking and molecular dynamic results exhibited curcumin's superior binding affinities and stability compared to native ligands of MAPK8, SRC, PPARG, and HSP90AA1 within 50 ns simulations. Moreover, MM-GBSA analysis showed stronger binding energy of curcumin to MAPK8, SRC, and HSP90AA1 than native ligand. In conclusion, this study provides valuable insights into curcumin's potential mechanisms in preventing liver cirrhosis progression, specifically in HCC. These findings offer a theoretical basis for further pharmacological research into anti-HCC effect of curcumin.Communicated by Ramaswamy H. Sarma.

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.