A Review on Quantum Mechanical Techniques in Protein-Ligand Docking

Review Article

Abstract

Quantum mechanical (QM) methods have changed protein-ligand docking by introducing high-level physics-based calculations into molecular modeling. The use of QM principles has significantly improved the accuracy of binding pose predictions and scoring functions compared to traditional molecular techniques. Recent scientific progress in QM-based scoring functions have enabled precise modeling of electronic effects, charge transfer, and polarization phenomena in protein-ligand complexes. The addition of fragment-based QM methods has streamlined computational workflows while maintaining quantum-level accuracy in specific interaction regions. Apart from these advances, balancing computational costs with accuracy remains a critical challenge, particularly in industrial drug discovery settings. The hybridization of QM methods with classical force fields has emerged as a practical solution, offering improved accuracy while maintaining computational efficiency. Industrial implementation of QM-enhanced docking faces several obstacles, including hardware requirements, software integration, and validation protocols. The evolution of high-performance computing infrastructure and specialized algorithms continues to address these challenges, making QM-based docking increasingly viable for large-scale drug discovery campaigns. Quantum mechanical approaches in protein-ligand docking represent a significant advancement in structure-based drug design, offering enhanced predictive power for lead optimization and binding affinity estimation