Dataset Information

Interaction of selected terpenoids with two SARS-CoV-2 key therapeutic targets: An in silico study through molecular docking and dynamics simulations.

ABSTRACT: The outbreak of COVID-19 disease caused by SARS-CoV-2, along with the lack of targeted medicaments, forced the scientific world to search for new antiviral formulations. In the current emergent situation, drug repurposing of well-known traditional and/or approved drugs could be the most effective strategy. Herein, through computational approaches, we aimed to screen 14 natural compounds from limonoids and terpenoids class for their ability to inhibit the key therapeutic target proteins of SARS-CoV-2. Among these, some limonoids, namely deacetylnomilin, ichangin and nomilin, and the terpenoid β-amyrin provided good interaction energies with SARS-CoV-2 3CL hydrolase (Mpro) in molecular dynamic simulation. Interestingly, deacetylnomilin and ichangin showed direct interaction with the catalytic dyad of the enzyme so supporting their potential role in preventing SARS-CoV-2 replication and growth. On the contrary, despite the good affinity with the spike protein RBD site, all the selected phytochemicals lose contact with the amino acid residues over the course of 120ns-long molecular dynamics simulations therefore suggesting they scarcely can interfere in SARS-CoV-2 binding to the ACE2 receptor. The in silico analyses of docking score and binding energies, along with predicted pharmacokinetic profiles, indicate that these triterpenoids might have potential as inhibitors of SARS-CoV-2 Mpro, recommending further in vitro and in vivo investigations for a complete understanding and confirmation of their inhibitory potential.

SUBMITTER: Giofre SV

PROVIDER: S-EPMC8186839 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The repurposing of FDA approved drugs is presently receiving attention for COVID-19 drug discovery. Previous studies revealed the binding potential of several FDA-approved drugs towards specific targets of SARS-CoV-2; however, limited studies are focused on the structural and molecular basis of interaction of these drugs towards multiple targets of SARS-CoV-2. The present study aimed to predict the binding potential of six FDA drugs towards fifteen protein targets of SARS-CoV-2 and propose the structural and molecular basis of the interaction by molecular docking and dynamic simulation. Based on the literature survey, fifteen potential targets of SARS-CoV-2, and six FDA drugs (Chloroquine, Hydroxychloroquine, Favipiravir, Lopinavir, Remdesivir, and Ritonavir) were selected. The binding potential of individual drug towards the selected targets was predicted by molecular docking in comparison with the binding of the same drugs with their usual targets. The stabilities of the best-docked conformations were confirmed by molecular dynamic simulation and energy calculations. Among the selected drugs, Ritonavir and Lopinavir showed better binding towards the prioritized targets with minimum binding energy (kcal/mol), cluster-RMS, number of interacting residues, and stabilizing forces when compared with the binding of Chloroquine, Favipiravir, and Hydroxychloroquine, later drugs demonstrated better binding when compared to the binding with their usual targets. Remdesvir showed better binding to the prioritized targets in comparison with the binding of Chloroquine, Favipiravir, and Hydroxychloroquine, but showed lesser binding potential when compared to the interaction between Ritonavir and Lopinavir and the prioritized targets. The structural and molecular basis of interactions suggest that the FDA drugs can be repurposed towards multiple targets of SARS-CoV-2, and the present computational models provide insights on the scope of repurposed drugs against COVID-19.

Dataset Information

Interaction of selected terpenoids with two SARS-CoV-2 key therapeutic targets: An in silico study through molecular docking and dynamics simulations.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets