Quantum-Driven High-Throughput Docking: Advances in Molecular Scoring and Drug Discovery

Computational methods are consolidated tools in early drug lead discovery. Among them, high-throughput molecular docking (HTD) is widely used to identify bioactive compounds within large chemical libraries by assessing likely binding modes and assigning docking scores. These methods also inform how hits may be modified to improve protein-ligand interactions, thus guiding lead optimization while reducing time and cost compared with experimental screening. For more than a decade, advances in methodology and computing power have renewed interest in applying quantum mechanics (QM) to macromolecular systems. A QM description of molecular association can provide improved accuracy over classical molecular mechanics (MM)-methods, since phenomena such as covalent bond formation, electronic polarization, charge transfer, bond rearrangement, and halogen bonding require explicit treatment of electrons. Here, we review recent developments in QM-based molecular docking and HTD, focusing on cases where QM is used explicitly in docking workflows.