Predicting Protein Ligand Binding Sites by Combining Evolutionary Sequence Conservation and 3D Structure
Figure 4
Comparison of ConCavity with publicly available ligand binding site prediction servers.
ConCavity significantly outperforms each previous method at the prediction of ligand binding residues. The existing servers focus on the task of pocket prediction, and return sets of residues that represent binding pocket predictions. They do not give different scores to these individual residues. In contrast, ConCavity assigns each residue a likelihood of binding, and thus residues in the same predicted pocket can have different scores. This ability and the direct integration of sequence conservation are the major sources of ConCavity's improvement. Conservation, the method based solely on sequence conservation, is competitive with these previous structural approaches. This figure is based on 234 proteins from the LigASite apo dataset for which we were able to obtain predictions from all methods.