From Protein Structure to Function with Bioinformatics.pdf

192 E.C. Meng et al.Fig. 8.1 Active site residues from members of the enolase superfamily, illustrating aspects ofmotif representation and specificity. The superimposed side chains of two basic and three acidicresidues are shown from each of the following: mandelate racemase (yellow, PDB 2mnr), enolase(salmon, PDB 4enl), and methylaspartate ammonia lyase (blue, PDB 1kcz). Balls indicate alphacarbonand side chain centroid locations. Single-letter codes near the alpha-carbons indicateresidue types: H for histidine, K for lysine, D for aspartic acid, and E for glutamic acid. While theacidic residues at the two lower left positions are highly conserved in type and conformation,variations in the sites include: (1) differing (albeit similar) residue types at the other three positions; (2)different side chain conformations, exemplified by the two lysines on the right; (3) different locationsin primary sequence, where the basic residue on the upper left is C-terminal to the others inenolase but N-terminal in the sequences of the other two proteins. Using side chain centroidsrather than the positions of functional atoms generally imparts more tolerance to changes in conformationand residue type. Including side chain atoms or centroids (not just backbone) decreasestolerance toward side chain flexibility, but conversely, provides more specificity for a precisearrangement of atoms in a functional site. Including atoms from the backbone decreases tolerancetoward cases of functional residue migration, where an important side chain can emanate fromdifferent locations in the sequence (Todd et al. 2002). The image was created with UCSF Chimera(Pettersen et al. 2004) (http://www.cgl.ucsf.edu/chimera)●Methods based on graph theory. A graph consists of vertices (points) and edges(lines that connect pairs of vertices). A molecular structure or 3D motif can betreated as a labelled graph. For example, atoms can be represented as verticeslabelled with residue type, and edges connecting each pair of vertices can belabelled with the corresponding interatomic distances. Isomorphic-subgraph algorithmslook for the occurrence of a smaller graph and all of its edges within alarger graph. Such an algorithm can be applied along with the graph labels to findsets of atoms in structures that match the types and distances within a 3D motif(Artymiuk et al. 1994; Spriggs et al. 2003). Tolerance values allow similar butnon-identical distances to match. Clique detection (Schmitt et al. 2002) isultimately similar, but the graph in this case describes the geometries of both