The Challenge of Considering Receptor Flexibility in Ligand Docking and Virtual Screening

CAVASOTTO, CLAUDIO N.; ORRY, ANDREW J.; ABAGYAN, RUBEN A.

CURRENT COMPUTER-AIDED DRUG DESIGN

BENTHAM SCIENCE PUBL LTD

Año: 2005 vol. 1 p. 423 - 440

1573-4099

Computational ligand docking and screening is widely employed throughout the pharmaceutical industry to speed up the drug discovery process and identify drug candidates from very large pools of virtual compound libraries. When a ligand interacts with a receptor a number of structural changes within the ligand binding site might occur. It is therefore critical for these methods to accurately predict, or otherwise take into account the receptor flexibility upon ligand binding. This flexibility within the binding pocket explains why a diverse range of ligand sizes and shapes can sometimes bind to the same receptor pocket. This observation supersedes the notion that ligand-receptor interaction is a purely ´lock and key´ mechanism. The capability to correctly predict molecular interactions is critical for computer-aided molecular design technology. In this review, we discuss biological cases of receptor flexibility upon ligand binding that can range from ´large-scale´ movement of loops to single ´gate-keeper´ amino acid movements. In addition, we provide further evidence that rigid receptor docking alone will more than likely fail in the drug-discovery process. We then discuss computational methods, which have been developed to mimic flexibility within the binding pocket and predict ligand-receptor interactions. Early flexible receptor docking methods used ´soft-potential docking´ and rotamer libraries. More recently methods have focused on constructing an ensemble of structures generated by a variety of means including X-ray crystallography, NMR, Monte Carlo sampling, Normal Modes-based methods and Molecular Dynamics. It is evident that methods that ignore receptor flexibility can result in poorly docked solutions and therefore the challenge is to develop computational methods, which can accurately and efficiently predict this phenomenon.