Pharmacophore analysis of monoterpene Melaleuca leucadendra as an inhibitor for 3 CLPro of the SARS-CoV-2

The monoterpene compound has been reported to have antiviral activities . This study aimed to test the monoterpene compound in Melaleuca leucadendra to inhibit the SARS-CoV-2 virus. The monoterpenes tested were a-Pinene, beta-Pinene, Linalool, a-Terpineol, and Terpinene-4-Ol. The method used was computational through pharmacophore analysis. The indicator for the quality of the compound was the fit score. A fit score of more than 50% indicates a good-quality compound, while a fit score of less than that indicates a poor-quality compound. Based on the analysis results, the monoterpene compound in Melaleuca leucadendra can potentially inhibit the SARS-CoV-2 virus directly through the inhibition of 3C-like protease. The linalool showed a fit score of 55% with interactions of hydrophobic, electrostatic, and hydrogen bonds. All the compounds did not inhibit the metabolic process and were safe, possibly having no side effects based on ADMET analysis.

Mini Studio: an Online Learning Solution

Face-to-face learning cannot be carried out during a pandemic. Changes in student learning styles from face-to-face to online learning suddenly resulted in several new problems, one of which was a decrease in student understanding of lecture material. To overcome this, we are trying to overcome these problems by designing a mini studio that is used to carry out the online learning process. This study aims to determine the effectiveness of the mini studio in improving students' conceptual mastery of the material presented by the lecturer. Using a pre-experimental method, this study involved 132 biology education students at Universitas Pasundan. The results showed an increase in student concept mastery (N-gain = 0.49) in the medium category. Thus, we can conclude that the mini studio is quite effective in increasing students' mastery of concepts. Mini studios can be used as a face-to-face replacement solution for online learning, although it is necessary to increase the learning support devices used in mini studios.

Molecular Docking Analysis of Tetradodecanoic from Coix Essential Oil as Potential ACE2 Inhibitors for SARS-CoV-2 Anti-Viral

ACE2 an enzyme is the functional receptor to SARS-CoV-2, the virus responsible for the Covid-19 pandemic. Besides having antibacterial activity, Coix essential oil is also reported to have antiviral activity. There is at the moment no effective treatment for this disease. It is of interest to use a structure-based virtual screening approach for the identification of potential ACE2 inhibitors of the main receptor of SARS-CoV-2 from tetradodecanoic of Coix phytochemical compound used to treat other influenza virus infection. The crystallographic structure with PDB ID: 1R4L of ACE2 in complex with the inhibitor XX5 was used as a model in the virtual screening of tetradodecanoic collected from the GCMS analysis of Coix essential oil. Molecular docking analysis was performed using the standard AutoDock vina protocol followed by ranking and selection of compounds based on their binding affinity. This analysis reported the optimal binding features of tetradodecanoic to the active site of the ACE2 for further consideration as potential SARS-CoV-2 antiviral. © 2022 American Institute of Physics Inc.. All rights reserved.

Optimizing Convolutional Neural Network by Using Genetic Algorithm for COVID-19 Detection in Chest X-Ray Image

Coronavirus Diseases 19 (COVID-19) first appeared in the city of Wuhan, China, at the end of 2019 and spread to several countries at a very fast rate. An early diagnosis of COVID-19 is needed to prevent further spread, reduce the number of deaths. Reverse Transcription Polymerase Chain Reaction (RT-PCR) is one of the methods used to detect COVID-19. However, this method takes a long time so another faster method is required. As the alternative, Chest X-rays image can be used to detect specific symptoms related to COVID-19 by automating the diagnosis. Convolutional Neural Network (CNN) is widely used for disease detection based on computer-aided medical images. In this study, we proposed classification model for the detection of COVID-19 by using CNN method, in which the synaptic weight is optimized by genetic algorithm. The genetic algorithm is known for its popularity that is very good to be used in terms of optimization problem because it offers an optimum solution that retains the model performance and there is no stochastic drop of performance. The result shows that, CNN optimized by genetic algorithm with Adam optimizer gives best performance for accuracy, F1-Score and Area Under Curve (AUC) with value 87.5%, 85.1 % and 86.8% respectively. © 2021 IEEE.

Molecular modelling on SARS-CoV-2 papain-like protease: an integrated study with homology modelling, molecular docking, and molecular dynamics simulations.

SARS-CoV-2 PLpro was investigated as a therapeutic target for potent antiviral drugs due to its essential role in not only viral replication but also in regulating the inborn immune response. Several computational approaches, including homology modelling, molecular docking, and molecular dynamics (MD) studies, were employed to search for promising drugs in treating SARS-CoV-2. Eighty-one compounds, sub-structurally similar to the antiviral drug, were used as potential inhibitors of PLpro. From our results, three complexes containing the ligands with Pubchem IDs: 153012995, 12149203, and 123608715 showed lower binding energies than the control (Ritonavir), indicating that they may become promising inhibitors for PLpro. MD was performed in a water solvent to validate the stability of the three complexes. All complexes achieved stable structure during the simulation as no significant fluctuations were observed in the validation parameters. Moreover, the binding energy for each complex was estimated using the MM-GBSA method. Complex 1 was the most stable structure based on the lowest binding energy score and its structure remained in a similar cavity with the docket snapshot. Based on our studies, three ligands were assumed to be potential inhibitors. The ligand of complex 1 may become the most promising antiviral drug against SARS-CoV-2 targeting PLpro.

Strengthening The Economy Of Desa Adat Based On Local Resources: Strategy And Regulation Context

This study aims to see the economic growth of traditional villages in Bali with the potential local resources owned by traditional villages. The problem of economic growth in Bali during the Covid-19 pandemic slowed down which had an impact on slowing down economic growth in traditional village, which led to the decline in the welfare of traditional village manner. Therefore, it is necessary to study the regulatory and growth aspects of economic growth strategies in customary villages based on local resources. This is a socio-legal research with a regulatory approach and data, which is the result of observation or social data. This study shows that the regulatory aspect of accelerating economic growth in traditional village Law 10 of 2009 on Tourism, Law 23 of 2014 on Regional Government, Bali Provincial Regulation 4 of 2019 concerning Implementing Regulations for Regional Regulation 4 of 2019 about Traditional Villages in Bali and also the strategy can be used by traditional villages in accelerating economic growth is the strategy with the Penta Helix model, which is a model for developing a synergy of 5 (five) elements, namely the Government, traditional village, academics, entrepreneurs, and the media © 2021, Journal of Legal, Ethical and Regulatory Issues. All Rights reserved