A computational study of cardiac glycosides from Vernonia amygdalina as PI3K inhibitors for targeting HER2 positive breast cancer.

Journal: Journal of computer-aided molecular design
Published Date: Jul 6, 2025

Abstract

The PI3K/Akt pathway plays a crucial role in regulating a broad network of proteins involved in the proliferation of HER2-positive breast cancer. The ethyl acetate fraction of Vernonia amygdalina, which contains cardiac glycosides, has been shown to reduce the expression of PI3K and mTOR. However, the specific cardiac glycoside compounds with significant potential as PI3K inhibitors have yet to be clearly identified. This study employs machine learning to perform virtual screening of cardiac glycosides from V. amygdalina against the p110 subunit of PI3K. Initially, Lipinski's Rule of Five was used to filter the PIK3CA inhibitor database via KNIME software. Subsequently, QSAR modeling was conducted using KNIME's machine learning platform, employing six different algorithms. Cardiac glycosides from V. amygdalina were then evaluated using the best-performing QSAR model. The top three compounds identified underwent molecular docking and molecular dynamics simulations. The random forest algorithm was selected as the primary predictive model, which identified Vernoamyosides A (VG-1), Vernoniamyosides D (VG-8), and Vernoniosides A4 (VG-10) as the compounds with the highest confidence levels. Molecular docking results indicated that these three compounds exhibited stronger and more stable interactions with the PIK3CA receptor compared to alpelisib, a known PIK3CA inhibitor. Furthermore, molecular dynamics simulations revealed that VG-10 had the lowest binding free energy, as determined by MM-GBSA analysis. The findings of this study provide a foundational basis for preclinical and clinical investigations aimed at developing PI3K inhibitors derived from cardiac glycosides of V. amygdalina for the treatment of HER2+ breast cancer.

Authors

  • Ahmad Syauqy Tafrihani
    Master of Pharmaceutical Science Student, Monash University, Australia 381 Royal Parade, Parkville, VIC, 3052, Australia.
  • Naufa Hanif
    Doctor of Pharmaceutical Sciences Student, Sekolah Farmasi Institut Teknologi Bandung, ITB Kampus Ganesha. Jl. Ganesa No. 10. Coblong, Kota Bandung, Jawa Barat, 40132, Indonesia.
  • I Made Bayu Kresna Yoga
    Laboratory of Macromolecular Engineering, Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Sekip Utara II, Yogyakarta, 55281, Indonesia.
  • Irmasari Irmasari
    Laboratory of Macromolecular Engineering, Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Sekip Utara II, Yogyakarta, 55281, Indonesia.
  • Taufik Muhammad Fakih
    Department of Pharmacy, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung, Bandung, 40116, Indonesia.
  • Dhania Novitasari
    Department of Pharmaceutical Analysis and Medicinal Chemistry, Faculty of Pharmacy, Universitas Padjadjaran, Sumedang, 45363, Indonesia.
  • Poppy Anjelisa Zaitun Hasibuan
    Department of Pharmacology, Faculty of Pharmacy, University of Sumatera Utara, Medan, Indonesia.
  • Denny Satria
    Department of Pharmaceutical Biology, Faculty of Pharmacy, Universitas Sumatera Utara, Medan, Indonesia.
  • Fathul Huda
    Department of Biomedical Sciences, Faculty of Medicine, Universitas Padjadjaran, Sumedang, 45363, Indonesia.
  • Muchtaridi Muchtaridi
    Department of Pharmaceutical Analysis and Medicinal Chemistry, Faculty of Pharmacy, Universitas Padjadjaran, Sumedang, 45363, Indonesia.
  • Adam Hermawan
    Laboratory of Macromolecular Engineering, Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Sekip Utara II, Yogyakarta, 55281, Indonesia.

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