Pre-docking filter for protein and ligand 3D structures

Abstract

Virtual drug screening using protein-ligand docking techniques is a time-consuming process, which requires high computational power for binding affinity calculation. There are millions of chemical compounds available for docking. Eliminating compounds that are unlikely to exhibit high binding affinity from the screening set should speed-up the virtual drug screening procedure. We performed docking of 6353 ligands against twenty-one protein X-ray crystal structures. The docked ligands were ranked according to their calculated binding affinities, from which the top five hundred and the bottom five hundred were selected. We found that the volume and number of rotatable bonds of the top five hundred docked ligands are similar to those found in the crystal structures and corresponded with the volume of the binding sites. In contrast, the bottom five hundred set contains ligands that are either too large to enter the binding site, or too small to bind with high specificity and affinity to the binding site. A pre-docking filter that takes into account shapes and volumes of the binding sites as well as ligand volumes and flexibilities can filter out low binding affinity ligands from the screening sets. Thus, the virtual drug screening procedure speed is increased. Background: Virtual screening techniques are becoming increasingly more important in drug discovery. A popular method for virtual screening is molecular docking [1, 2], which selects small-molecule structures from databases such as ChemBank [3], ChemPDB [4], KEGG [5], and NCI [6] and docks them into the protein binding site [7]. These processes involve the prediction of binding energies and analysis of molecular binding modes, which are time consuming and computationally expensive. The two-dimensional (2D) fingerprint technique, a virtual screening method which measures the structural similarity of molecules has been developed to address the above problems [8]. The similarity search is based upon the "similar property principle", which states that molecules that are structurally similar are likely to have similar properties [9]. This technique uses a ligand with known chemical properties, inhibitory activities, or binding modes for a target of interest as a reference for searching similar ligands in the database regardless of the shape and size of the protein binding site. The accuracy of this method depends on which similarity coefficient is used [10-12], and the Tanimoto coefficient is most popularly employed [13]. Based on the "lock-and-key" principle, we propose a novel pre-docking procedure that matches the sizes of the ligand with the protein binding site, and optimizes the grid-box size before docking. This simple procedure dramatically reduces the size of screening ligand sets, significantly reducing time and effort required for virtual drug screening.