ASEDock is a novel docking program based on a shape similarity assessment between a concave portion (i.e., concavity) on a protein and the ligand. We have introduced two novel concepts into ASEDock. One is an ASE model, which is defined by the combination of alpha spheres generated at a concavity in a protein and the excluded volumes around the concavity. The other is an ASE score, which evaluates the shape similarity between the ligand and the ASE model. The ASE score selects and refines the initial pose by maximizing the overlap between the alpha spheres and the ligand, and minimizing the overlap between the excluded volume and the ligand. Because the ASE score makes good use of the Gaussian-type function for evaluating and optimizing the overlap between the ligand and the site model, it can pose a ligand onto the docking site relatively faster and more effectively than using potential energy functions. The posing stage through the use of the ASE score is followed by full atomistic energy minimization. Because the posing algorithm of ASEDock is free from any bias except for shape, it is a very robust docking method. A validation study using 59 high-quality X-ray structures of the complexes between drug-like molecules and the target proteins has demonstrated that ASEDock can faithfully reproduce experimentally determined docking modes of various druglike molecules in their target proteins. Almost 80% of the structures were reconstructed within the estimated experimental error. The success rate of approximately 98% was attained based on the docking criterion of the root-mean-square deviation (RMSD) of non-hydrogen atoms (< or = 2.0 A). The markedly high success of ASEDock in redocking experiments clearly indicates that the most important factor governing the docking process is shape complementarity.

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Alpha sphere filter (ASF) method is a novel previrtual screening method to undertake a rapid virtual screening of a huge chemical space. The small-molecule binding site of a target molecule can be characterized by a set of alpha spheres generated at the site. Two types of pseudomolecules representing molecules that likely fit into the binding site were molded from the set of alpha spheres. Based on the pseudomolecules, pseudomolecular descriptors corresponding to the conventional two-dimensional (2D) molecular descriptors were calculated. The correlations between the pseudomolecular descriptors and the 2D molecular descriptors were analyzed for a set of high-quality X-ray structures of the complexes between ligands and proteins. By use of these correlations, specific value ranges of the 2D molecular descriptors were determined. These value ranges were applied in virtual screening. In a trial to screen 200 active ligands out of a chemical database with 42,547 molecules, the enrichment rate of 5.8 was attained. The enrichment rate was good enough for a prescreening tool prior to docking simulations. As the ASF method screens molecules by 2D molecular descriptors, it is rapid enough to screen a huge chemical space and could significantly decrease the number of trivial compounds to be considered in the following docking simulations. Therefore, the ASF method can contribute to enlarge the possibility of virtual screening.