![]() ![]() concluded that the best docking protocol for their set of ligands with AutoDock 4 was long, while the short option was best for Vina. The correspondance between predicted binding free energy and the experimental value was given in their Table 1: The RMSE values in kcal/mol they found for AutoDock 4 were very similar to the originally reported standard error of the scoring functions (although they did not say whether they used the bound, unbound, or extended assumption to model the ligand before binding). They found Vina was better than AD4 for 10 targets while both AutoDock 4 and AutoDock Vina had poor affinity correlation for 16 targets. But AutoDock 4 showed better performance, in terms of Pearson correlation coefficient of the predicted binding affinity with the experimental value, as well as better precision, & success rate, for 21 of the 47 targets. No surprises, they reported that AutoDock Vina was faster than AutoDock 4. ![]() These protocols corresponded to 250k evals, 2.5m evals and 25m evals for AutoDock 4 and exhaustiveness values of 8, 56, and 400 for AutoDock Vina. They performed re-docking of the 800 ligands to the 47 proteins, using both AutoDock4 and AutoDock Vina, with different options that controlled how far the docking engines searched, which they dubbed “ short“, “ medium“, and “ long“. ![]() selected 800 protein-ligand complexes for 47 protein targets that had both experimental PDB structures complexed with a ligand, as well as their associated binding affinity values. ing JCIM pointed out that while AutoDock Vina is faster, AutoDock 4 tends to have better correlation with experimental binding affinity. A recently just-released publication from Ngyuen et al. ![]()
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