Uji Efek Inhibitorik Komponen Bioaktif Bawang Putih (Allium sativum) terhadap Lanosterol 14α-demethylase pada Candida albicans melalui Studi In Silico

Candida albicans is a unicellular fungi which causes candidiasis in human and livestock animals especially chicken. Candidiasis could reduce productivity significantly by early culling and causing a great deficit in the farm. Allium sativum or garlic is widely known as herbal which has an inhibitory effect in fungi’s growth. This research’s aim is to prove the effectivity of bioactive compound in Allium sativum to lanosterol 14α-demethylase which plays a role in ergosterol synthesis as a basic structure in fungi’s cell membrane. The ligand sheet retrieved from PubChem database and for the receptor in Protein Data Bank database. Molecular docking conducted by using Autodock Vina and then ligand-receptor complex is visualized with PyMOL and Ligplot+. From compounds that we have been analyzed, Gallic Acid has the most negative binding energy than other compounds have and it has the same amino acid residue with control. In conclusion of that, Gallic Acid in Allium sativum has potential as anti-candidiasis drug.

Can miRNAs Serve as Potential Markers in Thermal Burn Injury: An In Silico Approach

Burn injury has been a major cause of morbidity at global levels. They can occur by multiple agents, such as thermal radiation and chemicals. Among all, thermal burn is predominant and may require specialized treatment in some patients. Although various biomarkers are reportedly used in thermal burn for understanding the pathophysiology of the injury, their limitations prompt for the search of suitable markers that can address the depth and severity of the burn. MicroRNAs (miRNAs) are conserved noncoding molecules that seem to be the promising marker due to their role in multiple pathways and participation in different physiological processes of the body. The present review highlights the role of miRNAs in the repair of the wound and their interaction with specific genes in response to burn stress. Key miR candidates include miR-21, miR-29a, miR-378a-5p, miR-100, miR-27b, miR-200c, miR-150, miR-499-5p, miR-92a, miR-194, and miR-146b, which are identified for their respective targets involved in wound repair. Furthermore, bioinformatics and computational tools were used to confirm the miRNAs and their specific targets. Gene and miRNA expression data sets were downloaded from Research Collaboratory for Structural Bioinformatics Protein Data Bank Database and RNAComposer, respectively, and docked by PatchDock. The possible implications of the identified miRNAs could be in understanding the mechanism of burn injury. These can also be studied with the available drugs being used for burn injury. Apart from that, new intended molecules may also be tested for their effect on these miRNAs.

In silico study of ginsenoside analogues as possible BACE1 inhibitors involved in Alzheimer's disease

Background: Neurodegenerative disorders such as Alzheimer's disease show an alarming prevalence in the population, with around 50 million affected individuals worldwide, and is associated with the development of dementia, mainly affecting the elderly population. Currently, the treatments used are based on slowing the progression of the clinical symptoms of Alzheimer’s; however, no specific treatment has been found that induces reversion of the disease. Natural products may induce a wide range of palliative effects, such as ginseng (Panax ginseng), which produces secondary metabolites called ginsenosides, which have multiple therapeutic applications, including for neurodegenerative diseases such as Alzheimer’s. Methods: A virtual screening was carried out, using the CHEMBL database to find analogs of ginsenosides based on the ginsenoside Rg1 (CHEMBL501637). Next, the molecules were optimized and their format modified. The structure of BACE1 was downloaded from the Protein Data Bank database (ID: 1FKN) and prepared for the development of molecular docking using the PyRx software. A database of the ligands was created and molecular docking experiments were carried out, obtaining affinity energy values ​​in Kcal/mol. Results: Of the 27 analogues studied, it was found that the molecules CHEMBL451292, CHEMBL510371 and CHEMBL503302 showed considerable affinity with BACE1 when compared with the reference molecules (verubecestat and donepezil). These affinity energy values for CHEMBL451292, CHEMBL510371 and CHEMBL503302 ​​were -9.6, -8.1 and -7.6 Kcal/mol, respectively. Likewise, the binding site of the ligands to BACE1 were identified, with the main interactions being van der Waals and hydrogen bonding. Conclusions: Three ginsenoside analogues showed a similar binding energy with BACE1 compared to the reference drugs. The residues involved in the inhibitory activity of BACE1 and the type of predominant interactions were identified, which agreed with previous reports.

MOLECULAR DOCKING STUDIES OF ISOLATED FLAVONOIDS COMPOUNDS FROM AMARANTHUS TRISTIS LINN. AS ALPHA-AMYLASE AND ALPHA-GLUCOSIDASE ACTIVATORS

Aim: Aim of this work on in silico approach to used to access the use of flavonids compounds of nutritionally enriched plant Amaranthus tristis Linn.Methods: Bioflavonoids of rutin isolated from A. tristis Linn. and active agents receptor such as alpha-amylase (1SMD) and alpha-glucosidase (3wy1) activators. Three-dimensional structure of receptors was obtained from protein data bank database and biocomponents such as isoflavones and flavonones of A. tristis were downloaded from database like USDA. Docking studies of insulin receptor with A. tristis biocomponents for isoflavones and flavonones were performed using AutoDock - 1.5.6 software.Results: Compounds from A. tristis Linn. showed better binding features with the alpha-amylase and alpha-glycosidase. Thus, these compounds can be effectively used as drugs for treating diabetes which is predicted on the basis of docking scores.Conclusion: The insights gained in this work can be further used in experimental studies for designing antidiabetic drugs with novel targets and mode of action.

Statistical dependence of protein secondary structure on amino acid bigrams

The statistical dependence of protein secondary structure on amino acid bigram frequencies was studied. Proteins in the PDBSELECT subset of the Protein Data Bank database were investigated. Protein secondary structures were determined using DSSP software. The conditional probabilities of protein secondary structures were calculated and presented. The results on bigrams show the frequencies of all the possible bigrams in all secondary structure types. These results elucidate some factors important for the prediction of the secondary structures of proteins based on the amino acid sequence.