Integrating Atom-Based 3D-QSAR, Molecular Docking, and Molecular Dynamics: A Multistep Approach for the Discovery of Potent Adenosine A2A Receptor Antagonists

Abstract

The rational design of adenosine A_2A receptor antagonists offers a non-dopaminergic approach to alleviate symptoms of Parkinson's disease (PD). Preclinical studies indicate that A_2A antagonists may inhibit neuronal loss, although human studies are essential for validating effectiveness. This research focuses on optimizing ligands for the A_2A receptor through a multifaceted method uniting 3D quantitative structure–activity relationship (QSAR) modeling, molecular docking, binding energy calculations, molecular dynamics (MD) simulations, and interaction analysis. A robust atom-based 3D-QSAR model was developed, achieving predictive performance metrics (R² = 0.80, Q² = 0.65) and identifying key structural features associated with bioactivity. Screening 3,958 compounds, five lead molecules (CHEMBL16687, 113142, 1760901, 4289874, 482436) were prioritized based on binding energies (ranging from −12.938 to −9.986 kcal/mol). Binding affinity confirmations through MMGBSA highlighted significant electrostatic and van der Waals interactions. A 200 ns MD simulation assessed the stability of these compounds, with CHEMBL4289874 showcasing exceptional stability and occupying the smallest phase space in principal component analysis (PCA), indicating superior stability relative to the other compounds. 2D interaction diagrams elucidated critical ligand-residue interactions fundamental to maintaining structural integrity. This comprehensive investigation positions CHEMBL4289874 as an exceptionally promising candidate for further development in PD treatment.