International Journal of Molecular Sciences (Apr 2024)

Exploring the Anticancer Potential of Semisynthetic Derivatives of 7α-Acetoxy-6β-hydroxyroyleanone from <i>Plectranthus</i> sp.: An In Silico Approach

  • Anna Merecz-Sadowska,
  • Vera M. S. Isca,
  • Przemysław Sitarek,
  • Tomasz Kowalczyk,
  • Magdalena Małecka,
  • Karolina Zajdel,
  • Hanna Zielińska-Bliźniewska,
  • Mariusz Jęcek,
  • Patricia Rijo,
  • Radosław Zajdel

DOI
https://doi.org/10.3390/ijms25084529
Journal volume & issue
Vol. 25, no. 8
p. 4529

Abstract

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The diterpene 7α-acetoxy-6β-hydroxyroyleanone isolated from Plectranthus grandidentatus demonstrates promising antibacterial, anti-inflammatory and anticancer properties. However, its bioactivity may be enhanced via strategic structural modifications of such natural products through semisynthesis. The anticancer potential of 7α-acetoxy-6β-hydroxyroyleanone and five derivatives was analyzed in silico via the prediction of chemicals absorption, distribution, metabolism, excretion, and toxicity (ADMET), quantum mechanical calculations, molecular docking and molecular dynamic simulation. The protein targets included regulators of apoptosis and cell proliferation. Additionally, network pharmacology was used to identify potential targets and signaling pathways. Derivatives 7α-acetoxy-6β-hydroxy-12-O-(2-fluoryl)royleanone and 7α-acetoxy-6β-(4-fluoro)benzoxy-12-O-(4-fluoro)benzoylroyleanone achieved high predicted binding affinities towards their respective protein panels, with stable molecular dynamics trajectories. Both compounds demonstrated favorable ADMET parameters and toxicity profiles. Their stability and reactivity were confirmed via geometry optimization. Network analysis revealed their involvement in cancer-related pathways. Our findings justify the inclusion of 7α-acetoxy-6β-hydroxy-12-O-(2-fluoryl)royleanone and 7α-acetoxy-6β-(4-fluoro)benzoxy-12-O-(4-fluoro)benzoylroyleanone in in vitro analyses as prospective anticancer agents. Our binding mode analysis and stability simulations indicate their potential as selective inhibitors. The data will guide studies into their structure optimization, enhancing efficacy and drug-likeness.

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