Predicting Protein Calcium Binding Sites

• Main Author: Wang, Xue
• Format: Others
• Published: Digital Archive @ GSU 2009
• Subjects: Ligand; Graph theory; Apo; Holo; Pocket; Clique; Rotamer; Optimization; Computer Sciences
• Online Access: http://digitalarchive.gsu.edu/cs_diss/46; http://digitalarchive.gsu.edu/cgi/viewcontent.cgi?article=1043&context=cs_diss

Calcium is one of the closely relevant metal ions that involves in enormous physicochemical activities in human body, including cell division and apoptosis, muscle contraction, neurotransmitter release, enzyme activation, and blood-clotting. Calcium fulfills its functions through the binding to different classes of calcium-binding proteins. To facilitate our understanding of the roles of calcium in biological systems, and to design novel metal-binding proteins with tailored binding capabilities, it is important to develop computation algorithms to predict calcium-binding sites in different classes of proteins. In literature, calcium-binding sites may be represented by either a spacial point, or the set of residues chelating calcium ion. A thorough statistical analysis of known calcium-binding proteins deposited in Protein Data Bank gives reference values of various parameters characterizing geometric and chemical features in calcium-binding sites including distances, angles, dihedral angles, the Hull property, coordination numbers, ligand types and formal charges. It also reveals clear differences between the well-known EF-hand calcium-binding motif and other calcium-binding motifs. Utilizing the above multiple geometric and chemical parameters in well-formed calcium binding sites, we developed MUG (MUltiple Geometries) program. MUG can re-identify the coordinates of the documented calcium ion and the set of ligand residues. Three previously published data sets were tested. They are comprised of, respectively, 19, 44 and 54 holo protein structures with 48, 92 and 91 documented calcium-binding sites. Defining a "correct hit" as a point within 3.5 angstrom to the documented calcium location, MUG has a sensitivity around 90% and selectivity around 80%. The set of ligand residues (calcium-binding pockets) were identified for 43, 66 and 63 documented calcium ion in these three data set respectively. In order to achieve true prediction, our program was then enhanced to predict calcium-binding pockets in apo (calcium-free) proteins. Our new program MUGSR accounts for the conformational changes involved in calcium-binding pockets before and after the binding of calcium ions. It is able to capture calcium binding pockets that may undergo local conformational changes or side chain torsional rotations, which is validated by referring back to the corresponding holo protein structure sharing more than 98% sequence similarity with the apo protein.