Proteins (e.g., enzymes, receptors, hormones, antibodies, transporter proteins, etc.) seldom act alone in the cell, and their functions rely on their interactions with various partners such as small molecules, other proteins, and/or nucleic acids. Molecular docking is a computational method developed to model these interactions at the molecular level by predicting the 3D structures of complexes. Predicting the binding site and pose of a protein with its partner through docking can help us to unveil protein structure-function relationship and aid drug design in numerous ways. In this chapter, we focus on the fundamentals of protein docking by describing docking methods including search algorithm, scoring, and assessment steps as well as illustrating recent successful applications in drug discovery. We especially address protein–small-molecule (drug) docking by comparatively analyzing available tools implementing different approaches such as ab initio, structure-based, ligand-based (pharmacophore-/shape-based), information-driven, and machine learning approaches.
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