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Metabolomic profile, anti-trypanosomal potential and molecular docking studies of Thunbergia grandifolia

  • Heba A. S. El-Nashar
  • , Ahmed M. Sayed
  • , Hany A. M. El-Sherief
  • , Mostafa E. Rateb
  • , Lina Akil
  • , Ibrahim Khadra
  • , Taghreed A. Majrashi
  • , Sara T. Al-Rashood
  • , Faizah A. Binjubair
  • , Mahmoud A. El Hassab
  • , Wagdy M. Eldehna
  • , Usama Ramadan Abdelmohsen*
  • , Nada M. Mostafa*
  • *Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

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    Abstract

    Trypanosomiasis is a protozoan disease transmitted via Trypanosoma brucei. This study aimed to examine the metabolic profile and anti-trypanosomal effect of methanol extract of Thunbergia grandifolia leaves. The liquid chromatography-high resolution electrospray ionisation mass spectrometry (LC-HRESIMS) revealed the identification of fifteen compounds of iridoid, flavonoid, lignan, phenolic acid, and alkaloid classes. The extract displayed a promising inhibitory activity against T. brucei TC 221 with MIC value of 1.90 μg/mL within 72 h. A subsequent in silico analysis of the dereplicated compounds (i.e. inverse docking, molecular dynamic simulation, and absolute binding free energy) suggested both rhodesain and farnesyl diphosphate synthase as probable targets for two compounds among those dereplicated ones in the plant extract (i.e. diphyllin and avacennone B). The absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiling of diphyllin and avacennone were calculated accordingly, where both compounds showed acceptable drug-like properties. This study highlighted the antiparasitic potential of T. grandifolia leaves.
    Original languageEnglish
    Article number2199950
    Number of pages9
    JournalJournal of Enzyme Inhibition and Medicinal Chemistry
    Volume38
    Issue number1
    Early online date20 Apr 2023
    DOIs
    Publication statusPublished - 31 Dec 2023

    Keywords

    • Trypanosoma brucei
    • Thunbergia grandifolia
    • LC-MS
    • in silico
    • inverse docking

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