Structural similarity of binding sites in analogous enzymes

CINF 59

Yang Shen, yangshen@bu.edu1, Dmitri Beglov2, Ryan Brenke, rbrenke@gmail.com3, Dima Kozakov, vemikainen@gmail.com2, and Sandor Vajda, vajda@bu.edu2. (1) Department of Manufacturing Engineering, Boston University, Boston, MA 02215, (2) Department of Biomedical Engineering, Boston University, 44 Cummington Street, Boston, MA 02215, (3) Program in Bioinformatics, Boston University, 44 Cummington Street, Boston, MA
Two enzymes are analogous if they have the same EC number (or their EC numbers differ only in the last digit), but are evolutionarily unrelated, i.e., they lack both sequence and structural similarity. Analogous enzyme pairs are relatively rare, but occur in all major classes, assumed to be the results of convergent evolution. Research on analogous enzymes is very limited: it consists of searches for non-homologous enzymes with the same EC number and studies of specific cases of convergent evolution. It is known that at least in a number of cases the spatial arrangement of the catalytic residues is conserved, but very little is known about the similarity of the binding sites that occur on different protein scaffolds. In this work we use a new method developed to assess molecular similarity for the structural superimposition of enzyme binding sites. The physicochemical properties of the cavity-flanking residues are represented by pseudocenters. Given two sets of such pseudocenters, our goal is finding the largest subset of pseudocenters in both clefts in direct correspondence with each other geometrically as well as chemically. The proposed method performs an exhaustive evaluation of the correlation function in the discretized 6D space of mutual orientations of the two point sets using a very efficient algorithm involving Fast Fourier Transforms. The method is applied to a number of analogous enzyme pairs. Advantages over the more traditional structure comparison method based on the maximum clique algorithm are discussed.