Molecular modelling investigation for drugs and nutraceuticals against protease of SARS-CoV-2

• Main Authors: Kanchanok Kodchakorn, Yong Poovorawan, Kamol Suwannakarn, Prachya Kongtawelert
• Other Authors: Chulalongkorn University
• Format: Article
• Published: 2020
• Subjects: Chemistry; Computer Science; Materials Science
• Online Access: https://repository.li.mahidol.ac.th/handle/123456789/59033
• Institution: Mahidol University

© 2020 Elsevier Inc. The widespread problem of a 2019-novel coronavirus (SARS-CoV-2) strain outbreak in Wuhan, China has prompted a search for new drugs to protect against and treat this disease. It is necessary to immediately investigate this due to the mutation of the viral genome and there being no current protective vaccines or therapeutic drugs. Molecular modelling and molecular docking based on in silico screening strategies were employed to determine the potential activities of seven HIV protease (HIV-PR) inhibitors, two flu drugs, and eight natural compounds. The computational approach was carried out to discover the structural modes with a high binding affinity for these drugs on the homology structure of the Wuhan coronavirus protease (SARS-CoV-2 PR). From the theoretical calculations, all the drugs and natural compounds demonstrated various favorable binding affinities. An interesting finding was that the natural compounds tested had a higher potential binding activity with the pocket sites of SARS-CoV-2 PR compared to the groups of HIV-PR inhibitors. The binding modes of each complex illustrated between the drugs and compounds interacted with the functional group of amino acids in the binding pocket via hydrophilic, hydrophobic, and hydrogen bond interactions using the molecular dynamics simulation technique. This result supports the idea that existing protease inhibitors and natural compounds could be used to treat the new coronavirus. This report sought to provide fundamental knowledge as preliminary experimental data to propose an existing nutraceutical material against viral infection. Collectively, it is suggested that molecular modelling and molecular docking are suitable tools to search and screen for new drugs and natural compounds that can be used as future treatments for viral diseases.