An Innovative Protocol for Comparing Protein Binding Sites via Atomic Grid Maps

This paper deals with a novel computational approach that aims to measure the similarities of protein binding sites through comparison of atomic grid maps. The assessment of structural similarity between proteins is a longstanding goal in biology and in structure-based drug design. Instead of focusing on standard structural alignment techniques, mostly based on superposition of common structural elements, the proposed approach starts from a physicochemical description of the proteins’ binding site. We call these atomic grid maps. These maps are preprocessed to reduce the dimensionality of the data while retaining the relevant information. Then, we devise an alignment-based similarity measure, based on a rigid registration algorithm (the Iterative Closest Point –ICP). The proposed approach, tested on a real dataset involving 22 proteins, has shown encouraging results in comparison with standard procedures.