UNRAVELLING THE INTERACTION BETWEEN GARCINISIDONE-A AND HER2 PROTEIN IN BREAST CANCER: A COMPUTATIONAL STUDY - FURQAN, MAINAL; DACHRIYANUS; SUSANTI, MERI; PUTRA, PURNAWAN PONTANA; WAHYUNI, FATMA SRI (International Journal of Applied Pharmaceutics, 2024)
Objective: One substance found in the leaves of Garcinia cowa Roxb that has anticancer properties is garcinisidone-A. The study aims to simulate the docking of garcinisidone-A (Gar-A), molecular dynamics, and predict the ADME by predicting the binding of the HER2 protein in breast cancer cells and developing new drug candidate options for cancer treatment, often starting with computational analysis. Methods: The research method involves computational utilization of pkCSM applications, Gar-A docking simulation with the HER2 protein using Gnina software version 1.0.2, and molecular dynamics conducted with GROMACS 2022.2 and CHARMMGUI applications. Results: Gar-A has a molecular weight of less than 500, a Log P value of greater than 5, a limited amount of water solubility, a low level of skin permeability, good intestinal permeability, and a Convolutional Neural Network (CNN) pose score on the HER2 protein of 0.6178. It also does not readily cross the blood-brain barrier, and total clearance values indicate rapid elimination via other excretory routes or enzyme metabolism. Gar-A is thought to have interactions with HER2. There are hydrogen bond interactions with amino acids Lys753 and Asp863, carbon-hydrogen bonds with amino acids Leu785, Ser783, Thr862, and alkyl bonds with amino acids Leu726, Leu852, and Ile767. The stability of the Gar-A-substrate interaction could have been more evident during 100 ns molecular dynamics simulation. Conclusion: The physicochemical properties of Gar-A align with Lipinski's rule for drug candidates. ADME predictions indicate good intestinal permeability for Gar-A; however, it suggests it cannot penetrate the blood-brain barrier. The docking results reveal that Gar-A has a value close to one which indicates similar action to its natural ligand and molecular dynamics simulations that Gar-A is less stable. The results illustrate that Gar-A has the potential as a breast anticancer.