Article Journal of Medicinal Chemistry, 2009, Vol. 52, No. 18 5713 Figure 1. The DOCK Blaster web interface, available starting from http://blaster.docking.org/. In principle, such an automated procedure could bring docking to a much larger community and could be used to explore targets on a proteomic scale. For the first goal to provide more good than harm, it is important to provide what may often be na ı¨ve users with an automated self-assessment of the docking results. We investigate methods to do so using pose fidelity and enrichment based on a single observed crystallographic ligand. To investigate the plausibility of the second goal, we describe here docking screens on 7755 protein targets where each screen is performed against a feasibility library of 100 molecules. Methods DOCK Blaster is composed of an expert system engine and a web-enabled user interface (Figure 1). The docking program used is DOCK 3.5.54,28,29 a version of UCSF DOCK. The DOCK Blaster pipeline is composed of six modules (Figure 2): (a) the parser, which identifies the receptor and ligand from a PDB file, (b) the scrutinizer, which attempts to correct for problems, such as incomplete or disordered residues on the receptor, (c) the preparer, which protonates the receptor, calculates “hot spots” and scoring grids, assigns atomic para- meters, including these for cofactors, post-translational mod- ifications and metals, and prepares the ligand, decoys, and any actives and inactives for docking, (d) the calibrator, which uses supplied data to assess docking performance and suggests optimal docking parameters, (e) the docker, which manages a full database screen on the computer cluster, and (f) the assessor, which prepares reports to interpret database screen- ing results. We take up each module in turn. a. The Parser. This expert system starts with a PDB code. The file is retrieved directly from the PDB Web site with no preprocessing. The Parser uses dictionaries of common cofactors, ions, post-translational modifications, and solutes to identify and separate the ligand from the receptor. If the Figure 2. DOCK Blaster pipeline schematic. Left: two starting points for DOCK Blaster. Center: six main modules of the auto- matic docking pipeline. Right: four places in which automatic docking can fail. ligand itself is a common solute or cofactor, a three letter code of the ligand must be specified. If more than one ligand is available, the Parser asks the user to pick one. In fully automated screens, such ambiguity stops the procedure. If no ligand can be identified, the Parser also halts the calcula- tion with an error message. A future version may use auto- matic binding site identification software30-32 to identify the binding site in this case. The Parser produces files that are ready to be used by the scrutinizer in the next step and may be accessed online at http://blaster.docking.org/parser.shtml. b. The Scrutinizer. The Scrutinizer takes as input a target structure and a specification of the binding site, which may be either a docked ligand in mol2 format or atoms in or near the binding site in PDB format. The Scrutinizer checks that the receptor and ligand are properly formatted, and that at least one atom of the ligand is within a binding site on the protein. This step also attempts to flesh out incomplete residues and pick the first of any disorder models present. The Scrutinizer can take input directly from the parser (module a, above) or from the job preparation page, http:// blaster.docking.org/start.shtml. c. The Preparer. The Preparer is an expert system that performs actions necessary before docking can begin. This includes maturing the receptor model by removal of ordered water molecules, protonation of receptor atoms to a united atom model, and assignment of AMBER atom types33 including to metals, cofactors, and post-translational mod- ifications that are effectively part of the receptor. Subse- quently docking “hot spots” are calculated by sphgen,34 while van der Waals and electrostatics scoring grids are calculated by chemgrid35 and Delphi,36 respectively. To correct for ligand desolvation, solvmap37 is used to calculate a solvent occlusion grid. To prepare a dockable database of the ligand and any actives and inactive controls, the PDB format ligand is converted to SMILES using OpenEye’s OEChem38 to eliminate bias. The molecule is then processed using the standard ZINC protocol,39 which aims to enumer- ate all physiologically relevant protonated and tautomeric forms of the molecule. In parallel, property-matched decoys for the ligand are found from ZINC using the DUD proto- cols27,40 for enrichment and ranking.