Directory of Useful Decoys, Enhanced (DUD-E): Better Ligands and Decoys for Better Benchmarking

A key metric to assess molecular docking remains ligand enrichment against challenging decoys. Whereas the directory of useful decoys (DUD) has been widely used, clear areas for optimization have emerged. Here we describe an improved benchmarking set that includes more diverse targets such as GPCRs and ion channels, totaling 102 proteins with 22886 clustered ligands drawn from ChEMBL, each with 50 property-matched decoys drawn from ZINC. To ensure chemotype diversity, we cluster each target’s ligands by their Bemis–Murcko atomic frameworks. We add net charge to the matched physicochemical properties and include only the most dissimilar decoys, by topology, from the ligands. An online automated tool (http://decoys.docking.org) generates these improved matched decoys for user-supplied ligands. We test this data set by docking all 102 targets, using the results to improve the balance between ligand desolvation and electrostatics in DOCK 3.6. The complete DUD-E benchmarking set is freely available at http://dude.docking.org

Orientational Matching Diagram.

<p>A toy example illustrating the matching sphere orientational matching algorithm. A) Toy receptor with 4 matching spheres shown as circles and a toy ligand with 3 spheres shown as stars. B) The distance matrices constructed from these spheres are show in the upper right. C) The 2 possible orientational matches of the ligand spheres (as stars) onto the receptor spheres with a distance tolerance of 0.1 (assuming 3 matching nodes are used, in 3D this is usually 4). D) The additional two orientations produced when the distance tolerance is raised to 0.2.</p

Compiler Optimizations.

<p>Compiler Optimizations.</p

Ligand Building Explanations.

<p>At left, several conformations of a ligand built with electrostatics off. At right the same ligand built with electrostatics on. The MMFF94S energies from OMEGA are shown below each pose. The bottom conformation on either side is the lowest energy conformation according to either energy function. The scales at either side are the differences in energy score from the best conformation to the shown conformation, this is the energy window used in construction.</p

DOCK score effects with varying degrees of orientational sampling.

<p>A) The crystal ligand from PDB Code 1VSO. The critical contacts are defined as 3 atoms from the ligand crystal structure making key polar contacts with the protein, highlighted with spheres. 4 poses of ZINC00013260 are shown in B through E, with increasing sampling going from left to right, better DOCK scores and lower critical contact RMSD (with the exception of the critical contact RMSD rising from Match Goal of 50 to 500). Protein is shown in gray, crystal ligand shown in purple and representative docked pose shown in green, with hydrogen bonds drawn according to UCSF Chimera defaults. An additional molecule, ZINC00374553, is similarly shown in subfigures F through I, with a similar trend of increasing DOCK energies and decreasing critical contact RMSD.</p

Speed versus different measures for five levels of orientational sampling.

<p>Speed measured in mean time in hours across all 102 DUD-E Targets against three measures of docking performance: Adjusted logAUC, AUC and EF1. Data shown for the full MMFF94S energy function used in ligand bulding (Green Squares) as well as the energy function with electrostatics turned off (Orange Diamonds).</p

Enrichment changes with varying degrees of orientational sampling.

<p>A) The histogram of changes between match goals of 50 and 20000 over all 102 DUD-E systems is shown. B) At right, the histogram of which of the five match goal levels produced the best enrichment for each of the 102 DUD-E targets. For each enrichment produced by another match gal, the histogram of the differences is shown to the left.</p

Hydroxyl dihedral distribution.

<p>A) Distribution of dihedral angles in radians for hydroxyls adjacent to any aromatic six-membered rings in the Cambridge Structural Database<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0075992#pone.0075992-Allen2" target="_blank">[133]</a>. Inset images show a phenol with the dihedral angle marked, B) is an example of off-planar aromatic hydroxyls produced by DOCK3.5.54, DOCK3.6 or in this paper as the “No Reset” option, C) is the Reset Hydroxyl version. The bin from 3.1 to −3.1 is shown only at left.</p

DOCK score effects with varying degrees of orientational sampling.

<p>The effect of changing the desired number of match goals, or orientational samples, on the DOCK score of both the ligands (in blue) and decoys (in red). 5 comparisons of the 4 levels of match goals are shown for Glutamate Receptor Ionotropic Kainate 1 (GRIK1) in A through E.</p

Effects of changing the bump limit on docking performance and time.

<p>A & B) Differences for varying the bump limit at a match goal of 500 are shown here for one DUD-E target, Thyroid hormone receptor beta-1 (THB). This is one of the few cases where ligands and even some decoys find scores with a higher bump limit than they do with a lower bump limit in kcal/mol. C) The timings for this run and the mean over all 102 DUD-E targets is shown. The bump limit itself does not have a large effect on the time, but using a high bump limit instead of none roughly doubles the speed of docking.</p