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2000
Volume 21, Issue 5
  • ISSN: 1573-4099
  • E-ISSN: 1875-6697

Abstract

Background

Drug-resistant represents a substantial healthcare challenge worldwide, and its range of available therapeutic options continues to diminish progressively. Thus, this study aimed to identify potential inhibitors against FemA, a crucial protein involved in the cell wall biosynthesis of .

Materials and Methods

The screening process involved a comprehensive structure-based virtual screening on the StreptomDB database to identify ligands with potential inhibitory effects on FemA using AutoDock Vina. The most desirable ligands with the highest binding affinity and pharmacokinetic properties were selected. Two ligands with the highest number of hydrogen bonds and hydrophobic interactions were further analyzed by molecular dynamics (MD) using the GROMACS version 2018 simulation package.

Results

Six H-donor conserved residues were selected as protein active sites, including Arg-220, Tyr-38, Gln-154, Asn-73, Arg-74, and Thr-24. Through virtual screening, a total of nine compounds with the highest binding affinity to the FemA protein were identified. Frigocyclinone and CHNO exhibited the highest binding affinity and demonstrated favorable pharmacokinetic properties. Molecular dynamics analysis of the FemA-ligand complexes further indicated desirable stability and reliability of complexes, reinforcing the potential efficacy of these ligands as inhibitors of FemA protein.

Conclusion

Our findings suggest that Frigocyclinone and CHNO are promising inhibitors of FemA in . To further validate these computational results, experimental studies are planned to confirm the inhibitory effects of these compounds on various strains. Combining computational screening with experimental validation contributes valuable insights to the field of drug discovery in comparison to the classical drug discovery approaches.

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Repurposing of Compounds from Streptomyces spp. as Potential Inhibitors of Aminoacyltransferase FemA: An Essential Drug Target against Antibiotic-resistant Staphylococcus aureus
Curr. Computeraided Drug Des. 21, 708 (2025); https://doi.org/10.2174/0115734099297360240312043642
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  • Article Type:     Research Article
Keyword(s): drug discovery; drug repurposing; FemA; molecular dynamics; Staphylococcus aureus; structure-based virtual screening

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