Pocket Similarity: Are α Carbons Enough?

A novel method for measuring protein pocket similarity was devised, using only the a carbon positions of the pocket residues. Pockets were compared pairwise using an exhaustive three-dimensional C alpha common subset search, grouping residues by physicochemical properties. At least five C alpha matches were required for each hit, and distances between corresponding points were fit to an Extreme Value Distribution resulting in a probabilistic score or likelihood for any given superposition. A set of 85 structures from 13 diverse protein families was clustered based on binding sites alone, using this score. It was also successfully used to cluster 25 kinases into a number of subfamilies. Using a test kinase query to retrieve other kinase pockets, it was found that a specificity of 99.2% and sensitivity of 97.5% could be achieved using an appropriate cutoff score. The search itself took from 2 to 10 min on a single 3.4 GHz CPU to search the entire Protein Data Bank (133 800 pockets), depending on the number of hits returned.