Scoring functions for protein-ligand docking.

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Molecular Docking and Structure-Based Drug Design Strategies (2015, background): “Prediction of the binding energy is performed by evaluating the most important physical-chemical phenomena involved in ligand-receptor binding, including intermolecular interactions, desolvation and entropic effects [55].”
TANKBind: Trigonometry-Aware Neural NetworKs for Drug-Protein Binding Structure Prediction (2022, background): “Moreover, they need to sample a large range of possible ligand poses and protein side-chain conformations, which leads to relatively high computational cost [7, 12].”
Advances and Challenges in Protein-Ligand Docking (2010, methodology): “The scoring function is a key element of a protein-ligand docking algorithm, because it directly determines the accuracy of the algorithm [78–82].”
Virtual screening strategies in drug discovery: a critical review. (2013, background): “Some of the commonly used scoring functions can be grouped into three broad categories: force field-based, knowledge-based and empirical [69, 70].”
Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go (2008, background): “These SFs are classified as force field (FF)-based, empirical and knowledge-based (Tame, 1999; Schulz-Gasch and Stahl, 2004; Mohan et al ., 2005; Tame, 2005; Jain, 2006).”