ArticlePloS one2012
Prediction of metal ion-binding sites in proteins using the fragment transformation method.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.
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Who cites it
59 citing papers in PubMed.
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- Insulin-cobalt core-shell nanoparticles for receptor-targeted bioimaging and diabetic wound healing.RSC advances · 2023Article
- Metal3D: a general deep learning framework for accurate metal ion location prediction in proteins.Nature communications · 2023Article
- Molecular characterization of Satsuma mandarin (Plant biotechnology (Tokyo, Japan) · 2023Article
Corrections and comments
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4 authors.
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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 Ca(2+), Cu(2+), Fe(3+), Mg(2+), Mn(2+), and Zn(2+)-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.
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