Identification of metal ion binding sites based on amino acid sequences.
Identification of metal ion binding sites based on amino acid sequences.
复制标题
基于氨基酸序列鉴定金属离子结合位点
DOI：
10.1371/journal.pone.0183756
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发表时间：
2017
期刊：
影响因子：
3.7
通讯作者：
Bao W
中科院分区：
文献类型：
--
作者：
Cao X;Hu X;Zhang X;Gao S;Ding C;Feng Y;Bao W
金属离子结合位点的鉴定对于蛋白质功能注释以及新药物分子的设计具有重要意义。本研究提出了一种仅基于序列信息分析和鉴定金属离子结合残基的有效方法。从BioLip数据库中提取了十种金属离子：Zn²⁺、Cu²⁺、Fe²⁺、Fe³⁺、Ca²⁺、Mg²⁺、Mn²⁺、Na⁺、K⁺和Co²⁺。分析表明，Zn²⁺、Cu²⁺、Fe²⁺、Fe³⁺和Co²⁺对结合位点处氨基酸的保守性较为敏感，使用位置权重评分矩阵算法可取得良好结果，准确率超过79.9%，马修斯相关系数超过0.6。其他金属的结合位点也可使用以多特征参数作为输入的支持向量机算法进行准确鉴定。此外，我们发现Ca²⁺对疏水性和亲水性信息不敏感，Mn²⁺对极化电荷信息不敏感。基于所提出方法的框架构建了一个在线服务器，可在http://60.31.198.140:8081/metal/HomePage/HomePage.html免费获取。
The identification of metal ion binding sites is important for protein function annotation and the design of new drug molecules. This study presents an effective method of analyzing and identifying the binding residues of metal ions based solely on sequence information. Ten metal ions were extracted from the BioLip database: Zn2+, Cu2+, Fe2+, Fe3+, Ca2+, Mg2+, Mn2+, Na+, K+ and Co2+. The analysis showed that Zn2+, Cu2+, Fe2+, Fe3+, and Co2+ were sensitive to the conservation of amino acids at binding sites, and promising results can be achieved using the Position Weight Scoring Matrix algorithm, with an accuracy of over 79.9% and a Matthews correlation coefficient of over 0.6. The binding sites of other metals can also be accurately identified using the Support Vector Machine algorithm with multifeature parameters as input. In addition, we found that Ca2+ was insensitive to hydrophobicity and hydrophilicity information and Mn2+ was insensitive to polarization charge information. An online server was constructed based on the framework of the proposed method and is freely available at http://60.31.198.140:8081/metal/HomePage/HomePage.html.
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