New trends in computational structure prediction of ligand-protein complexes for receptor-based drug design

Abstract

A number of challenging computational problems arise in the field of structure-based drug design, including the estimation of ligand binding affinity and the de novo design of novel ligands. An important step toward solutions of these problems is the consistent and rapid prediction of the thermodynamically most favorable structure of a ligand—protein complex from the three-dimensional structures of its unbound ligand and protein components. This fundamental problem in molecular recognition is commonly known as the docking problem [1–3]. To solve this problem, two distinct conditions must be satisfied. The first is a thermodynamic requirement: the energy function used to describe ligand—protein binding must have the crystal structure of ligand—protein complexes as its global energy minimum. The second is a kinetic requirement: it must be possible to locate consistently and rapidly the global energy minimum on the ligand—protein binding energy landscape. While the first condition is necessary for successful structure prediction, it is by no means sufficient. Without kinetic accessibility, the global minimum cannot be reached during docking simulations, and computational structure prediction will fail. Here we review approaches to address both the kinetic and thermodynamic aspects of the docking problem.