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Volume 21, Issue 17
  • ISSN: 1570-1808
  • E-ISSN: 1875-628X

Abstract

Background

In recent years, computational approaches have tremendously guided computational medicinal chemists and research scientists to analyze protein structures, kinetics, functions, and molecular interactions of the administered drugs.

Objective

This study aimed to identify a novel inhibitor against SARS-CoV-2 using human CD26 and modeled spike protein through suitable approaches.

Methods

In this work, molecular docking and molecular dynamics simulation experiments were conducted to gain insights into the binding affinity and stability, respectively. The docked complex of CD26 with modeled spike protein showed higher binding affinity than the complex of CD26 with resolved spike protein due to the existence of strong interactions with the crucial amino acid residues of the target proteins.

Results

The results of the molecular dynamics simulation demonstrated that CD26 with the modeled spike protein docked complex showed good stability when compared with the resolved protein.

Conclusion

From this computational finding, it was also suggested that the structure was stable and would rapidly guide the discovery of potential inhibitors against COVID-19.

© 2024 Bentham Science Publishers
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2024-08-19
2025-06-27

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Computational Design of a Novel Inhibitor against COVID
Letters in Drug Design & Discovery 21, 3934 (2024); https://doi.org/10.2174/0115701808322637240722052915
/content/journals/lddd/10.2174/0115701808322637240722052915
/content/journals/lddd/10.2174/0115701808322637240722052915
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  • Article Type:     Research Article
Keyword(s): CD26; Computational design; COVID; homology modeling; molecular docking; molecular dynamics simulation

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