Computational methods are a powerful and consolidated tool in the early stage of the drug lead discovery process. Among these techniques, high-throughput molecular docking has proved to be extremely useful in identifying novel bioactive compounds within large chemical libraries. In the docking procedure, the predominant binding mode of each small molecule within a target binding site is assessed, and a docking score reflective of the likelihood of binding is assigned to them. These methods also shed light on how a given hit could be modified in order to improve protein-ligand interactions and are thus able to guide lead optimization. The possibility of reducing time and cost compared to experimental approaches made this technology highly appealing. Due to methodological developments and the increase of computational power, the application of quantum mechanical methods to study macromolecular systems has gained substantial attention in the last decade. A quantum mechanical description of the interactions involved in molecular association of biomolecules may lead to better accuracy compared to molecular mechanics, since there are many physical phenomena that cannot be correctly described within a classical framework, such as covalent bond formation, polarization effects, charge transfer, bond rearrangements, halogen bonding, and others, that require electrons to be explicitly accounted for. Considering the fact that quantum mechanics-based approaches in biomolecular simulation constitute an active and important field of research, we highlight in this work the recent developments of quantum mechanical-based molecular docking and high-throughput docking.
Keywords: Computer-aided drug discovery; High-throughput docking; Molecular docking; Protein–ligand interaction; Quantum mechanics; Structure-based drug design.