Ability of Secondary Metabolites from Actinomadura sp. as COVID-19 Protease Inhibitor: In Silico Method

The pandemic of COVID-19 disease in the late of 2019 resulted in the massive screening for drug discovery purpose. However, there is still no reports about the ability of natural products from bacterial group of class Actinobacteria as COVID-19 inhibitor. The aim of this research is to identify the...

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Published inBiotropic : the journal of tropical biology Vol. 7; no. 2; pp. 25 - 34
Main Authors Eshananda, Yuriza, Wiraswati, Sri Martina, Lestari, Sri, Mariana, Afifah, Erfianti, Tia, Kusumaningrum, Hermin Pancasakti
Format Journal Article
LanguageEnglish
Published 31.08.2023
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Summary:The pandemic of COVID-19 disease in the late of 2019 resulted in the massive screening for drug discovery purpose. However, there is still no reports about the ability of natural products from bacterial group of class Actinobacteria as COVID-19 inhibitor. The aim of this research is to identify the potential ability of natural compounds from Actinomadura sp., the member of class Actinobacteria, against two receptors of COVID-19 protease with PDB ID 6LU7 and 5R7Y. The eleven natural compounds were docked using AutoDock Vina and the interaction between receptor and ligands were analysed using LIGPLOT. The most potential compound was simulated for its interaction stability using Yet Another Scientific Artificial Reality Application (YASARA) dynamics. The result of molecular docking by AutoDock Vina showed that Sagamilactam become the most potential inhibitor for viral protease as it had lower binding affinity (6LU7:-12 and 5R7Y:-10.4) compared to the both of  native ligand (6LU7:-11.4 and 5R7Y:-4.6). Furthermore, the interaction of the most potential ligand showed the low number of Root Mean Square Deviation (RMSD) deviation in molecular dynamic simulations. This result validated the docking method that used and indicated that secondary metabolites produced from rare actinobacteria of Actinomadura sp. have promising possibility to inhibit COVID-19 protease.
ISSN:2580-5029
2580-5029
DOI:10.29080/biotropic.v7i2.1926