Protein–Ligand Interactions: Computational Docking

Abstract

Abstract A pharmaceutical drug compound is usually a small organic molecule, also termed as ligand, that binds to the target protein and alters the natural activity of the protein, thus, leading to a therapeutic effect. Computational docking or computer‐aided docking is an extremely useful tool to gain an understanding of protein–ligand interactions which is important for the drug discovery. Computational docking is the process of computationally predicting the placement and binding affinity of the ligand in the binding pocket of the protein. Docking methods rely on a search algorithm which computes the placement of the ligand in the binding pocket and a scoring function which estimates the binding affinity, that is, how strongly the ligand interacts with the protein. A variety of methods have been developed to solve the computational docking problems that range from simple point‐matching algorithms to explicit physical simulation methods. Key Concepts: Computational docking methods play an important role in the drug discovery process. A docking method computes the placement of a ligand in the binding pocket of a protein and estimates the binding affinity. Rigid‐body docking methods treat both the protein and ligand as rigid bodies. Flexible ligand methods treat the ligand as a flexible molecule and flexible receptor methods treat both the ligand and the protein as flexible molecules. Two main features of computational docking techniques are a conformation search algorithm and a scoring function that estimates binding affinity. Most of the computational docking programs treat the protein as a rigid molecule and the ligand as a flexible molecule. Protein flexibility is an important determinant of the accuracy of docking programs. Efforts have been made to account for protein flexibility in docking methods, but more needs to be done.