Lessons Learned in Empirical Scoring with smina from the CSAR 2011 Benchmarking Exercise

We describe a general methodology for designing an empirical scoring function and provide smina, a version of AutoDock Vina specially optimized to support high-throughput scoring and user-specified custom scoring functions. Using our general method, the unique capabilities of smina, a set of default interaction terms from AutoDock Vina, and the CSAR (Community Structure–Activity Resource) 2010 data set, we created a custom scoring function and evaluated it in the context of the CSAR 2011 benchmarking exercise. We find that our custom scoring function does a better job sampling low RMSD poses when crossdocking compared to the default AutoDock Vina scoring function. The design and application of our method and scoring function reveal several insights into possible improvements and the remaining challenges when scoring and ranking putative ligands

Query results for top four- and five-feature pharmacophore models.

<p>Query results for top four- and five-feature pharmacophore models.</p

Chemical structure of DHODH inhibitor 5-methyl-7-(naphthalene-2-yl-amino)-1H-[1,2,4]triazolo[1,5-a]pyrimidine-3,8-diium.

<p>The six pharmacophore features used to define the sparse model search space are labeled. Green labels refer to hydrophobic groups, blue labels refer to hydrogen bond features.</p

The distribution of tested and active compounds within the submitted (a) Vina ranked and (b) custom ranked compounds.

<p>For each ranking 1000 compounds were submitted from which the TDT organizers sampled a total of 167 compounds for testing. Within the Vina ranking, better scoring compounds are more likely to be active. No such enrichment is observed for the custom ranking.</p

A pharmacophore derived by a student from a structure of DHODH bound to an inhibitor (PDB 3I65).

<p>The pharmacophore consists of hydrophobic features (green spheres) and a hydrogen donor feature (white sphere). This pharmacophore was used as part of a virtual screen for novel inhibitors.</p