doi:10.1093/bioinformatics/btl079BIOINFORMATICS ORIGINAL PAPER Structural bioinformatics Predicting protein interaction sites: binding hot-spots in protein–protein and protein–ligand interfaces

Motivation: Protein assemblies are currently poorly represented in structural databases and their structural elucidation is a key goal in biology. Here we analyse clefts in protein surfaces, likely to correspond to binding ‘hot-spots’, and rank them according to sequence conserva-tion and simple measures of physical properties including hydrophobi-city, desolvation, electrostatic and van der Waals potentials, to predict which are involved in binding in the native complex. Results: The resulting differences between predicting binding-sites at protein–protein and protein–ligand interfaces are striking. There is a high level of predictionaccuracy (93%) for protein–ligand interactions, based on the following attributes: van derWaals potential, electrostatic potential, desolvation and surface conservation. Generally, the predic-tion accuracy for protein–protein interactions is lower, with the excep-tion of enzymes. Our results show that the ease of cleft desolvation is strongly predictive of interfaces and strongly maintained across all classes of protein-binding interface. Contact