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2000
Volume 29, Issue 14
  • ISSN: 1381-6128
  • E-ISSN: 1873-4286

Abstract

Background: Nowadays, the emergence of methicillin-resistant (MRSA) and vancomycin-resistant (VRSA) strains has dramatically restricted the treatment options against this microorganism. Aim: In this study, we aimed to discover new drug targets and inhibitors against . Methods: This study consists of two major sections. In the upstream evaluation, after a comprehensive coreproteome analysis, essential cytoplasmic proteins with no similarity to the human proteome were selected. Then the metabolome-specific proteins were selected, and novel drug targets were identified using the DrugBank database. In the downstream analysis, a structure-based virtual screening approach was performed to reveal potential hit compounds against adenine N1 (m1A22)-tRNA methyltransferase (TrmK) using the StreptomeDB library and AutoDock Vina software. The compounds with a binding affinity > -9 kcal/mol were analyzed based on ADMET properties. Finally, the hit compounds were selected based on Lipinski’s rule of five (RO5). Results: Three proteins, including glycine glycosyltransferase (FemA), TrmK, and heptaprenyl pyrophosphate synthase subunit A (HepS1), were selected as feasible and promising drug targets based on PDB file availability and their essential role in the survival of the . Finally, seven hit compounds, including Nocardioazine_ A, Geninthiocin_D, Citreamicin_delta, Quinaldopeptin, Rachelmycin, Di-AFN_A1 and Naphthomycin_ K were introduced against the binding cavity of TrmK, as a feasible drug target. Conclusion: The results of this study provided three feasible drug targets against . In the following, seven hit compounds were introduced as potential inhibitors of TrmK, and Geninthiocin_D was identified as the most desirable agent. However, in vivo and in vitro investigations are needed to confirm the inhibitory effect of these agents on .

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/content/journals/cpd/10.2174/1381612829666230428105643
2023-04-01
2025-09-25
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  • Article Type:
    Research Article
Keyword(s): ADMET; Quinaldopeptin; Staphylococcus aureus; structure-based virtual screening; TrmK; VRSA
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