Exploring SAR insights into royleanones for P-gp modulation

Area of Science:

• Pharmacology and Medicinal Chemistry
• Computational Chemistry
• Cancer Therapeutics

Background:

• Multidrug resistance (MDR) significantly limits chemotherapy efficacy, often due to P-glycoprotein (P-gp) upregulation.
• Plectranthus genus plants, including Plectranthus grandidentatus Gürke, possess compounds with anticancer properties.
• 7α-acetoxy-6β-hydroxyroyleanone (Roy) and its derivatives have shown promise in modulating P-gp activity.

Purpose of the Study:

• To construct a ligand-based pharmacophore model for P-gp modulation using existing in vitro data.
• To predict the P-gp modulating potential of five novel royleanone ester derivatives.
• To guide future development of anticancer agents overcoming MDR.

Main Methods:

• Utilized in vitro data on P-gp activity of known Roy derivatives.
• Developed a binary classification model based on in silico structure-activity relationship (SAR) studies.
• Generated and reduced Molecular Interaction Field (MIF) descriptors using DFT-optimized structures.

Main Results:

• A robust SAR model was established using 12 key descriptors and two latent variables.
• The model successfully differentiated active and inactive compounds.
• In silico predictions indicate a high likelihood of P-gp modulating activity for five novel royleanone derivatives.

Conclusions:

• The developed pharmacophore model provides critical insights into P-gp modulation.
• Novel royleanone derivatives demonstrate significant potential for overcoming P-gp mediated MDR.
• Future in vitro validation is planned to confirm the predicted biological activity.