Dataset Information

The Inhibitory Potential of Ferulic Acid Derivatives against the SARS-CoV-2 Main Protease: Molecular Docking, Molecular Dynamics, and ADMET Evaluation.

ABSTRACT: The main protease (M^pro) of SARS-CoV-2 is an appealing target for the development of antiviral compounds, due to its critical role in the viral life cycle and its high conservation among different coronaviruses and the continuously emerging mutants of SARS-CoV-2. Ferulic acid (FA) is a phytochemical with several health benefits that is abundant in plant biomass and has been used as a basis for the enzymatic or chemical synthesis of derivatives with improved properties, including antiviral activity against a range of viruses. This study tested 54 reported FA derivatives for their inhibitory potential against M^pro by in silico simulations. Molecular docking was performed using Autodock Vina, resulting in comparable or better binding affinities for 14 compounds compared to the known inhibitors N3 and GC376. ADMET analysis showed limited bioavailability but significantly improved the solubility for the enzymatically synthesized hits while better bioavailability and druglikeness properties but higher toxicity were observed for the chemically synthesized ones. MD simulations confirmed the stability of the complexes of the most promising compounds with M^pro, highlighting FA rutinoside and compound e27 as the best candidates from each derivative category.

SUBMITTER: Antonopoulou I

PROVIDER: S-EPMC9329733 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:SARS-CoV-2 is the foremost culprit of the novel coronavirus disease 2019 (nCoV-19 and/or simply COVID-19) and poses a threat to the continued life of humans on the planet and create pandemic issue globally. The 3-chymotrypsin-like protease (MPRO or 3CLPRO) is the crucial protease enzyme of SARS-CoV-2, which directly involves the processing and release of translated non-structural proteins (nsps), and therefore involves the development of virus pathogenesis along with outbreak the forecasting of COVID-19 symptoms. Moreover, SARS-CoV-2 infections can be inhibited by plant-derived chemicals like amentoflavone derivatives, which could be used to develop an anti-COVID-19 drug. Our research study is designed to conduct an in silico analysis on derivatives of amentoflavone (isoginkgetin, putraflavone, 4''''''-methylamentoflavone, bilobetin, ginkgetin, sotetsuflavone, sequoiaflavone, heveaflavone, kayaflavone, and sciadopitysin) for targeting the non-structural protein of SARS-CoV-2, and subsequently further validate to confirm their antiviral ability. To conduct all the in silico experiments with the derivatives of amentoflavone against the MPRO protein, both computerized tools and online servers were applied; notably the software used is UCSF Chimera (version 1.14), PyRx, PyMoL, BIOVIA Discovery Studio tool (version 4.5), YASARA (dynamics simulator), and Cytoscape. Besides, as part of the online tools, the SwissDME and pKCSM were employed. The research study was proposed to implement molecular docking investigations utilizing compounds that were found to be effective against the viral primary protease (MPRO). MPRO protein interacted strongly with 10 amentoflavone derivatives. Every time, amentoflavone compounds outperformed the FDA-approved antiviral medicine that is currently underused in COVID-19 in terms of binding affinity (- 8.9, - 9.4, - 9.7, - 9.1, - 9.3, - 9.0, - 9.7, - 9.3, - 8.8, and - 9.0 kcal/mol, respectively). The best-selected derivatives of amentoflavone also possessed potential results in 100 ns molecular dynamic simulation (MDS) validation. It is conceivable that based on our in silico research these selected amentoflavone derivatives more precisely 4''''''-methylamentoflavone, ginkgetin, and sequoiaflavone have potential for serving as promising lead drugs against SARS-CoV-2 infection. In consequence, it is recommended that additional in vitro as well as in vivo research studies have to be conducted to support the conclusions of this current research study.

Project description:Background: Due to the constant mutation of virus and the lack of specific therapeutic drugs, the coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still poses a huge threat to the health of people, especially those with underlying diseases. Therefore, drug discovery against the SARS-CoV-2 remains of great significance. Methods: With the main protease of virus as the inhibitor target, 9,614 genistein derivatives were virtually screened by LeDock and AutoDock Vina, and the top 20 compounds with highest normalized scores were obtained. Molecular dynamics simulations were carried out for studying interactions between these 20 compounds and the target protein. The drug-like properties, activity, and ADMET of these compounds were also evaluated by DruLiTo software or online server. Results: Twenty compounds, including compound 11, were screened by normalized molecular docking, which could bind to the target through multiple non-bonding interactions. Molecular dynamics simulation results showed that compounds 2, 4, 5, 11, 13, 14, 17, and 18 had the best binding force with the target protein of SARS-CoV-2, and the absolute values of binding free energies all exceeded 50 kJ/mol. The drug-likeness properties indicated that a variety of compounds including compound 11 were worthy of further study. The results of bioactivity score prediction found that compounds 11 and 12 had high inhibitory activities against protease, which indicated that these two compounds had the potential to be further developed as COVID-19 inhibitors. Finally, compound 11 showed excellent predictive ADMET properties including high absorption and low toxicity. Conclusion: These in silico work results show that the preferred compound 11 (ZINC000111282222), which exhibited strong binding to SARS-CoV-2 main protease, acceptable drug-like properties, protease inhibitory activity and ADMET properties, has great promise for further research as a potential therapeutic agent against COVID-19.

Project description:The recent coronavirus outbreak has changed the world's economy and health sectors due to the high mortality and transmission rates. Because the development of new effective vaccines or treatments against the virus can take time, an urgent need exists for the rapid development and design of new drug candidates to combat this pathogen. Here, we obtained antiviral peptides obtained from the data repository of antimicrobial peptides (DRAMP) and screened their predicted tertiary structures for the ability to inhibit the main protease of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using multiple combinatorial docking programs, including PatchDock, FireDock, and ClusPro. The four best peptides, DRAMP00877, DRAMP02333, DRAMP02669, and DRAMP03804, had binding energies of -1125.3, -1084.5, -1005.2, and -924.2 Kcal/mol, respectively, as determined using ClusPro, and binding energies of -55.37, -50.96, -49.25, -54.81 Kcal/mol, respectively, as determined using FireDock, which were better binding energy values than observed for other peptide molecules. These peptides were found to bind with the active cavity of the SARS-CoV-2 main protease; at Glu166, Cys145, Asn142, Phe140, and Met165, in addition to the substrate-binding sites, Domain 2 and Domain 3, whereas fewer interactions were observed with Domain 1. The docking studies were further confirmed by a molecular dynamics simulation study, in which several descriptors, including the root-mean-square difference (RMSD), root-mean-square fluctuation (RMSF), solvent-accessible surface area (SASA), radius of gyration (Rg), and hydrogen bond formation, confirmed the stable nature of the peptide-main protease complexes. Toxicity and allergenicity studies confirmed the non-allergenic nature of the peptides. This present study suggests that these identified antiviral peptide molecules might inhibit the main protease of SARS-CoV-2, although further wet-lab experiments remain necessary to verify these findings.

Dataset Information

The Inhibitory Potential of Ferulic Acid Derivatives against the SARS-CoV-2 Main Protease: Molecular Docking, Molecular Dynamics, and ADMET Evaluation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets