Towards predicting Ca²⁺‐binding sites with different coordination numbers in proteins with atomic resolution

Abstract

Ca 2+ -binding sites in proteins exhibit a wide range of polygonal geometries that directly relate to an equally-diverse set of biological functions. Although the highly-conserved EF-Hand motif has been studied extensively, non-EF-Hand sites exhibit much more structural diversity which has inhibited efforts to determine the precise location of Ca 2+ -binding sites, especially for sites with few coordinating ligands. Previously, we established an algorithm capable of predicting Ca 2+ -binding sites using graph theory to identify oxygen clusters comprised of four atoms lying on a sphere of specified radius, the center of which was the predicted calcium position. Here we describe a new algorithm, MUG (MUltiple Geometries), that predicts Ca 2+ -binding sites in proteins with atomic resolution. After first identifying all possible oxygen clusters by finding maximal cliques, a calcium center (CC) for each cluster, corresponding to the potential Ca 2+ position, is located to maximally regularize the structure of the (cluster, CC) pair. The structure is then inspected by geometric filters. An unqualified (cluster, CC) pair is further handled by recursively removing oxygen atoms and relocating the CC until its structure is either qualified or contains fewer than four ligand atoms. Ligand coordination is then determined for qualified structures. This algorithm, which predicts both Ca 2+ positions and ligand groups, has been shown to successfully predict over 90% of the documented Ca 2+ -binding sites in three datasets of highlydiversified protein structures with 0.22 to 0.49 Å accuracy. All multiple-binding sites (i.e. -sites with a single ligand atom associated with multiple calcium ions) were predicted, as were half of the low-coordination sites (i.e. -sites with less than four protein ligand atoms) and 14/16 cofactorcoordinating sites. Additionally, this algorithm has the flexibility to incorporate surface water molecules and protein cofactors to further improve the prediction for low-coordination and cofactor-coordinating Ca 2+ -binding sites.

Identification of an l-Phenylalanine Binding Site Enhancing the Cooperative Responses of the Calcium-sensing Receptor to Calcium

“…By using our own computational algorithms, we previously identified five putative Ca 2ϩ -binding sites in the modeled CaSR ECD (Fig. 1) (25,26,45). Among these, site 1 is located in the hinge region between the two lobes in the Venus flytrap motif.…”

Analysis and prediction of calcium‐binding pockets from apo‐protein structures exhibiting calcium‐induced localized conformational changes

“…In a more recent study, we further exploited the properties of oxygen clusters involved in calcium binding and were able to successfully identify the set of ligand residues in 75% of the test cases. 19 To date, prediction efforts based on apo structures have not been able to accurately identify the set of ligand residues comprising a binding pocket, due mainly to the complex reconfigurations which occur as a consequence of metal binding. The blind docking algorithms typically perform better with the binding of medium to large molecules.…”

“…Each generated potential conformation is then passed back to S2. 19 To obtain the aforementioned maximal clique, a graph G(V, E) is constructed, where V is the set of all vertices and E is the set of all edges of G. Each vertex represents an oxygen atom. An edge is assigned between two vertices if the distance between these two vertices is within a preset O-O cutoff (7.5 Å ).…”

“…45 The size of a maximal clique is the number of vertices it contains. MUG SR identifies the CC within each oxygen cluster by finding the point that accrues the least penalty according to a penalty function detailed in our previous work, 19 so that the CC is located to optimize the structure of the (cluster, CC) pair to those observed in holo structures.…”

“…Filters are used to inspect each tentative (cluster, CC) pair. Two sets of filters, chemical-filters, and geometrical-filters, 19 are currently applied in MUG SR . Chemical-filters examine the formal charge of each cluster.…”