In silico anticancer activity of isoxazolidine and isoxazolines derivatives: DFT study, ADMET prediction, and molecular docking

Abstract

This study presents a comprehensive analysis of six isoxazolidine and isoxazoline derivatives, employing a multifaceted approach that integrates Density Functional Theory (DFT), AdmetSAR analysis, and molecular docking simulations to explore their electronic, pharmacokinetic, and anticancer properties. Utilizing DFT analysis with the B3LYP-D3BJ functional and the 6-311++G(d,p) basis set, molecular geometries were optimized, and vibrational frequencies in the IR spectrum were evaluated, offering insights into the molecular structure and stability of the pharmaceutical compounds. Electrostatic potential maps were analyzed to predict functional group reactivity and protein-substrate interactions. Frontier Molecular Orbital (FMO) analysis and Density of States (DOS) plots revealed varying stability levels among the compounds, with 1b, 2b, and 3b exhibiting slightly higher stability. Chemical potential and hardness analyses highlighted stronger binding affinity for compounds 1b and 2b, suggesting stronger potential interactions. AdmetSAR analysis predicted favorable human intestinal absorption (HIA) rates for all compounds, with compound 3b showing superior oral effectiveness. Molecular docking and dynamics simulations were conducted targeting the receptor (PDB: 1JU6). Molecular docking simulations confirmed the high affinity of these compounds towards the target protein 1JU6, particularly compound 3b, which exhibited the most favorable binding energy of -8.50 kcal/mol. Molecular dynamics simulations demonstrated the superior stability of ligand 3b over 1b and 5-FU over 100 ns, suggesting its potential for further study. The 3b-protein complex exhibited stability through hydrophobic and hydrogen bond interactions, with 3b demonstrating reduced solvent exposure compared to 1b and 5-FU. This study underscores the promising role of compound 3b in anticancer treatments, providing a solid foundation for future drug development and optimization efforts.