Design and statistical optimisation of emulsomal nanoparticles for improved anti-SARS-CoV-2 activity of N-(5-nitrothiazol-2-yl)-carboxamido candidates: in vitro and in silico studies

Abstract

In this article, emulsomes (EMLs) were fabricated to encapsulate the N-(5-nitrothiazol-2-yl)-carboxamido derivatives (3a–3g) in an attempt to improve their biological availability and antiviral activity. Next, both cytotoxicity and anti-SARS-CoV-2 activities of the examined compounds loaded EMLs (F3a–g) were assessed in Vero E6 cells via MTT assay to calculate the CC₅₀ and inhibitory concentration 50 (IC₅₀) values. The most potent 3e-loaded EMLs (F3e) elicited a selectivity index of 18 with an IC₅₀ value of 0.73 μg/mL. Moreover, F3e was selected for further elucidation of a possible mode of action where the results showed that it exhibited a combination of virucidal (>90%), viral adsorption (>80%), and viral replication (>60%) inhibition. Besides, molecular docking and MD simulations towards the SARS-CoV-2 Mpro were performed. Finally, a structure–activity relationship (SAR) study focussed on studying the influence of altering the size, type, and flexibility of the α-substituent to the carboxamide in addition to compound contraction on SARS-CoV-2 activity.

Highlights

• Emulsomes (EMLs) were fabricated to encapsulate the N-(5-nitrothiazol-2-yl)-carboxamido derivatives (3a–3g).

• The most potent 3e-loaded EMLs (F3e) showed an IC₅₀ value of 0.73 μg/mL against SARS-CoV-2.

• F3e exhibited a combination of virucidal (>90%), viral adsorption (>80%), and viral replication (>60%) inhibition.

• Molecular docking, molecular dynamics (MD) simulations, and MM-GBSA calculations were performed.

• Structure–activity relationship (SAR) study was discussed to study the influence of altering the size, type, and flexibility of the α-substituent to the carboxamide on the anti-SARS-CoV-2 activity.

GRAPHICAL ABSTRACT

Keywords:

• N-(5-nitrothiazol-2-yl)-carboxamide
• emulsomes
• anti-SARS-CoV-2
• mechanistic study
• SAR

Acknowledgements

The authors acknowledge financial support from the Researchers Supporting Project number (RSP-2023/103), King Saud University, Riyadh, Saudi Arabia. Also, the authors acknowledge the HPC, University of Cape Town, for using supercomputing facilities.

Author contributions

Conceptualisation: A.A.A-K; formal analysis: A.A.A-K., D.S.E-G., R.E-S., M.S., R.A-n., O.K., Y.M., M.E-a., S.T.A-R., F.A.B., W.M.E-d., A.M.N., and M.Y.Z.; funding acquisition: S.T.A-R., F.A.B., and W.M.E-d.; methodology: A.A.A-K., D.S.E-G., R.E-S., M.S., R.A-N., M.E-A., O.K., Y.M., A.M.N., and M.Y.Z.; project administration: A.A.A-K. and M.Y.Z.; software: A.A.A-K., R.E-S., M.S., R.A-N., and M.Y.Z.; supervision: A.A.A-K.; validation: A.A.A-K., M.S., R.A-N., and M.Y.Z.; writing – original draft: A.A.A-K., D.S.E-G., R.E-S., M.S., R.A-n., W.M.E-d., A.M.N., and M.Y.Z.; writing – review and editing: all authors revised and approved the final version of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The authors acknowledge financial support from the Researchers Supporting Project number [RSP-2023/103], King Saud University, Riyadh, Saudi Arabia.