Design and Evaluation of Piperazine‐Based CB1 Antagonists as Promising Therapeutic Candidates for Obesity Treatment

Abstract

Abstract Obesity is the fifth leading cause of death worldwide, making the identification of new therapeutic targets a critical public health priority. The type 1 cannabinoid receptor (CB1) is a key modulator of food intake and energy metabolism, and CB1 antagonists, such as rimonabant, have been clinically applied to manage appetite and body weight in animals and humans. A multistep in silico approach was employed to identify potential CB1 inhibitors among piperazine derivatives. This included 3D‐QSAR modeling, molecular docking, molecular dynamics (MD) simulations, and MM/PBSA binding energy calculations. The predictive ability of the CoMSIA/SEA QSAR model was assessed, and contour maps were generated to highlight key molecular features influencing biological activity. ADMET analysis evaluated the pharmacokinetic properties and drug‐likeness of the designed compounds. The best CoMSIA/SEA model exhibited strong predictive performance ( Q 2 = 0.619, R 2 = 0.918, R 2 pred = 0.804), with electrostatic, steric, and hydrogen‐bond acceptor fields contributing significantly to activity. Docking and 500 ns MD simulations confirmed the stability of the ligand–CB1 complexes. Compounds 51T and 58T demonstrated superior binding affinities, favorable pharmacokinetic profiles, and non‐toxic characteristics, suggesting enhanced therapeutic potential over existing treatments. This integrated computational strategy allowed the rational selection and optimization of novel CB1 ligands. Compounds 51T and 58T emerge as promising candidates for anti‐obesity therapy, providing a foundation for further experimental validation and potential drug development.