Prediction of Metal Ion–Binding Sites in Proteins Using the Fragment Transformation Method

Abstract

The structure of a protein determines its function and its interactions with other factors. Regions of proteins that interact with ligands, substrates, and/or other proteins, tend to be conserved both in sequence and structure, and the residues involved are usually in close spatial proximity. More than 70,000 protein structures are currently found in the Protein Data Bank, and approximately one-third contain metal ions essential for function. Identifying and characterizing metal ion–binding sites experimentally is time-consuming and costly. Many computational methods have been developed to identify metal ion–binding sites, and most use only sequence information. For the work reported herein, we developed a method that uses sequence and structural information to predict the residues in metal ion–binding sites. Six types of metal ion–binding templates– those involving Ca2+, Cu2+, Fe3+, Mg2+, Mn2+, and Zn2+–were constructed using the residues within 3.5 Å of the center of the metal ion. Using the fragment transformation method, we then compared known metal ion–binding sites with the templates to assess the accuracy of our method. Our method achieved an overall 94.6 % accuracy with a true positive rate of 60.5 % at a 5 % false positive rate and therefore constitutes a significant improvement in metal-binding site prediction.

MavN is a Legionella pneumophila vacuole-associated protein required for efficient iron acquisition during intracellular growth

“…His-rich sequences can be found in diverse families of metal transporters (59). Additionally, histidines tend to be enriched in binding sites for iron (60). We generated three mutant constructions-a 3-His (H445A, H450A, H452A), a 4-His (H460A, H462A, H465A, H466A), and a composite 7-His mutant-by site-specific mutagenesis (Fig.…”

“…S5B). Given the identification of essential amino acids in loop 7, we created two additional mutant constructs that alter regions rich in Glu and Asp residues in this loop, as acidic side chains are often involved in metal binding (60) (Fig. 6B, EXXE-4b and EXXE-5b).…”

Identification of Ca2+-binding residues of a protein from its primary sequence

“…In 2006, Deng et al (2006) developed the graphtheory-based and geometry-based approach to detect calciumbinding sites, and got a sensitivity of about 90% for 123 calcium binding proteins. Lu et al (2012) predicted the metal ion-binding site in proteins by the fragment transformation method. By using the method, they compared 273 known calcium binding proteins with 407 binding templates and achieved 94.1% accuracy with 48.9% true positive rate (Lu et al, 2012).…”

“…Lu et al (2012) predicted the metal ion-binding site in proteins by the fragment transformation method. By using the method, they compared 273 known calcium binding proteins with 407 binding templates and achieved 94.1% accuracy with 48.9% true positive rate (Lu et al, 2012). Roy and Zhang (2012) recognized protein-ligand binding site by global structural alignment and local geometry refinement using low-resolution protein structural models, which obtained a good result in the blind test in CASP9 (Schmidt et al, 2011).…”

Molecular characterization influencing metal resistance in theCupriavidus/Ralstoniagenomes

“…For instance, it was thought that, the more G+C rich genomes in thermophilic bacteria is a result of the selection pressure acting on them, as they are more thermostable (Lu, Lin, Lin & Yu, 2012). In our study, although the optimal codon is highly conserved among C. eutropha H16, C.eutropha JMP134, C.taiwanensis, C.necatar N-1 and C.metallidurans ( Figure 5), yet there are small but notable differences in their codon usage.…”