Prediction of transition metal‐binding sites from apo protein structures

Abstract

Metal ions are crucial for protein function. They participate in enzyme catalysis, play regulatory roles, and help maintain protein structure. Current tools for predicting metal-protein interactions are based on proteins crystallized with their metal ions present (holo forms). However, a majority of resolved structures are free of metal ions (apo forms). Moreover, metal binding is a dynamic process, often involving conformational rearrangement of the binding pocket. Thus, effective predictions need to be based on the structure of the apo state. Here, we report an approach that identifies transition metal-binding sites in apo forms with a resulting selectivity >95%. Applying the approach to apo forms in the Protein Data Bank and structural genomics initiative identifies a large number of previously unknown, putative metal-binding sites, and their amino acid residues, in some cases providing a first clue to the function of the protein.

The PMS2 Subunit of Human MutLα Contains a Metal Ion Binding Domain of the Iron-Dependent Repressor Protein Family

“…Metal ion binding sites were predicted using MetSite, 39 CHED, 40 and FEATURE 41 servers and by the ZincFinder program. 43 Additional protein family classification was performed with the SVM-Prot server.…”

MetalMine: a database of functional metal-binding sites in proteins

“…There have been several prediction methods based on structural information, such as the threading model (Sodhi et al 2004;Goyal et al 2008) and the force field model (Schymkowitz et al 2005). An empirical method based on the comparison of holo-apo pairs of known metal-binding sites appears to be one of the most practical approaches currently available because of the quality of the results (Babor et al 2008). An ambitious de novo approach based on a sequence using a machine-learning method has also been developed (Lippi et al 2008), although its prediction ability appears to be limited compared with the structure based predictions .…”

Metalloproteins: Structure, Conservation and Prediction of Metal Binding Sites

“…It has been observed that many metal binding sites in proteins are centered in a shell of hydrophilic ligands surrounded by a hydrophobic area. 6 A number of algorithms are available for predicting metal binding sites [6][7][8][9][10][11][12] and metal binding proteins. 13 Mostly, they are based on information derived from holo forms.…”