MIB: Metal Ion-Binding Site Prediction and Docking Server

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• 作者：Yu-Feng Lin ; Chih-Wen Cheng ; Chung-Shiuan Shih ; Jenn-Kang Hwang ; Chin-Sheng Yu ; Chih-Hao Lu
• 刊名：Journal of Chemical Information and Modeling
• 出版年：2016
• 出版时间：December 27, 2016
• 年：2016
• 卷：56
• 期：12
• 页码：2287-2291
• 全文大小：335K
• ISSN：1549-960X

文摘

The structure of a protein determines its biological function(s) and its interactions with other factors; the binding regions tend to be conserved in sequence and structure, and the interacting residues involved are usually in close 3D space. The Protein Data Bank currently contains more than 110 000 protein structures, approximately one-third of which contain metal ions. Identifying and characterizing metal ion-binding sites is thus essential for investigating a protein’s function(s) and interactions. However, experimental approaches are time-consuming and costly. The web server reported here was built to predict metal ion-binding residues and to generate the predicted metal ion-bound 3D structure. Binding templates have been constructed for regions that bind 12 types of metal ion-binding residues have been used to construct binding templates. The templates include residues within 3.5 Å of the metal ion, and the fragment transformation method was used for structural comparison between query proteins and templates without any data training. Through the adjustment of scoring functions, which are based on the similarity of structure and binding residues. Twelve kinds of metal ions (Ca²⁺, Cu²⁺, Fe³⁺, Mg²⁺, Mn²⁺, Zn²⁺, Cd²⁺, Fe²⁺, Ni²⁺, Hg²⁺, Co²⁺, and Cu⁺) binding residues prediction are supported. MIB also provides the metal ions docking after prediction. The MIB server is available at http://bioinfo.cmu.edu.tw/MIB/.