Abstract
Ferulic acid (4-hydroxy-3-methoxycinnamic acid) is a phytochemical compound that is commonly found in conjugated forms within mono-, di-, polysaccharides and other organic compounds in cell walls of grain, fruits, and vegetables. This compound is highly abundant in the palm oil waste. The aim of the study was to predict the anticancer activity of ferulic acid against the breast cancer cell lines (MCF-7) receptors through a computational analysis. MCF-7 receptors with PDB IDs of 1R5K, 2IOG, 4IV2, 4IW6, 5DUE, 5T92, and 5U2B were selected based on the Simplified Molecular Input Line Entry System (SMILES) similarity of the native ligand. Thereafter, the protein was prepared on Chimera 1.16 and docked with ferulic acid on Autodock Vina 1.2.5. The ligand-protein complex interaction was validated by computing the root mean square fluctuation (RMSF) and radius of gyration (Rg) through molecular dynamic simulation. In addition, an absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction was performed on ferulic acid using the pkCSM platform. The molecular docking revealed that the ferulic acid could interact with all receptors as indicated by the affinity energy <-5 kcal/mol. The compound had the most optimum interaction with receptor 2IOG (affinity energy=-6.96 kcal/mol), involving hydrophobic interaction (n=12) and polar hydrogen interaction (n=4). The molecular dynamic simulation revealed that the complex had an RMSF of 1.713 Å with a fluctuation of Rg value around 1.000 Å. The ADMET properties of ferulic acid suggested that the compound is an ideal drug candidate. In conclusion, this study suggested that ferulic acid, which can be isolated from palm oil waste, has the potential to interact with MCF-7 receptors.