Alternative global goodness metrics and sensitivity analysis: heuristics to check the robustness of conclusions from studies comparing virtual screening methods.
We introduce two ways of testing the robustness of conclusions from studies comparing virtual screening methods: alternative "global goodness" metrics and sensitivity analysis. While the robustness tests cannot eliminate all biases in virtual screening comparisons, they are useful as a "reality check" for any given study. To illustrate this, we apply them to a set of enrichments published in McGaughey et al. (J. Chem. Inf. Model. 2007, 47, 1504-1519) where 11 target protein/ligand combinations are tested on 2D and 3D similarity methods, plus docking. The major conclusions in that paper, for instance, that ligand-based methods are better than docking methods, hold up. However, some minor conclusions, such as Glide being the best docking method, do not.
Sheridan
Robert P
RP
Molecular Systems, Merck Research Laboratories, RY50SW-100, Rahway, New Jersey 07065, USA. sheridan@merck.com
D000465:Algorithms; D003198:Computer Simulation; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D008024:Ligands; D011485:Protein Binding; D011506:Proteins
D008024:Ligands; D011506:Proteins