In silico molecular analysis of novel L-specific dehalogenase from Rhizobium sp. RC1

Aims: This study presents the first structural model and proposed the identity of four important key amino acid residues,Asp13, Arg51, Ser131 and Asp207 for the stereospecific haloalkanoic acid dehalogenase from Rhizobium sp. RC1. Methodology and results: The enzyme was built using a homology modeling technique; the structure of crystallized LDEX YL from Pseudomonas sp. strain YL as a template. Model validation was performed using PROCHECK to generate the Ramachandran plot. The results showed 80.4% of its residues were located in the most favoured regions suggested that the model is acceptable. Molecular dynamics simulation of the model protein was performed in water for 10 nanoseconds in which Na+ was added to neutralize the negative charge and achieved energy minimization. The energy value and RMSD fluctuation of Cα backbone of the model were computed and confirmed the stability of the model protein. Conclusion, significance and impact of study: In silico or computationally based function prediction is important to complement with future empirical approaches. L-haloacid dehalogenase (DehL), previously isolated from Rhizobium sp. RC1 was known to degrade halogenated environmental pollutants. However, its structure and functions are still unknown. This structural information of DehL provides insights for future work in the rational design of stereospecific haloalkanoic acid dehalogenase

Ekstrak Etanol Kulit Buah Manggis Sebagai Masker Gel Peel-Off Berantioksidan

Peel off gel masks have become a trend in the field of beauty as a facial skin care. Utilization of mangosteen rind extract is thought to be able to provide more function on the mask as its high levels of antioxidant. This study discusses the optimum formulation of antioxidant peel off gel mask with mangosteen rind ethanol extract. Mangosteen rind was obtained from the market in the South Tangerang area and then extracted using 96% ethanol as the solvent by maceration. Peel off gel mask preparation is formulated with extract concentrations of 1%, 2% and 4%. Stability test in the form of analysis of pH, viscosity, dry time, and homogenation was carried out for four weeks. Antioxidant analysis was carried out to detect flavonoid, saponins and tannins. The results showed that the extract contained flavonoids, saponins and tannins with free radical scavenging values ​​of 16.10%. The optimum formulation of peel off gel mask is with 2% extract because it has an acidic pH, a viscosity value of 8025 cps, a thick texture, and has a drying time of about 14 minutes

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