The researchers examined 11 targets for which they had multiple crystal structures of each with bound fragments (which contained up to 15 non-hydrogen atoms) and larger molecules (which contained at least 20 non-hydrogen atoms); these crystal structures were the “correct” structures against which computational models could be judged. A total of 106 fragments and 100 larger molecules were then docked against their target proteins using a variety of different methods.
Surprisingly, the overall results were not overly impressive (<70% correct depending on methodology – often much less). But even more surprisingly, there was no difference between the success rates of the fragments and that of the larger molecules. However, the reasons for the poor performance were different. In the case of fragments, the problem was often that the scoring function didn’t recognize the correct solution; the energetics were just too subtle. In the case of the larger molecules, though, the problem was more often one of sampling: the docking program failed to produce the conformation of protein or ligand that corresponded to the correct solution, so it had no opportunity to score it. Potency made no difference: high-affinity compounds fared just as poorly as lower affinity compounds. What did make a difference, though, was ligand efficiency: compounds with high ligand-efficiency (> 0.4 kcal/mol/atom) were docked with considerably greater success than those with lower ligand efficiencies. As the authors point out, this makes sense intuitively:
High LE compounds form high-quality interactions with the target, which should make it easier for a docking program (both from a scoring and search perspective) to dock these compounds correctly.So the next time you see a computational model of a protein-ligand complex, you might want to take a closer look at ligand efficiency to get a sense of how trustworthy the structure might be.