FoldUnfold: web server for the prediction of disordered regions in protein chain
FoldUnfold: web server for the prediction of disordered regions in protein chain
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DOI：
10.1093/bioinformatics/btl504
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发表时间：
2006-12-01
期刊：
影响因子：
5.8
通讯作者：
Lobanov, Michail Yu.
中科院分区：
文献类型：
--
作者：
Galzitskaya, Oxana V.;Garbuzynskiy, Sergiy O.;Lobanov, Michail Yu.
多肽链中的无序区域的鉴定是非常重要的，因为这些区域对于蛋白质功能是必需的。引入了一个新的参数，即残基平均堆积密度来检测蛋白质序列中的无序区域。我们已经证明，具有弱预期堆积密度的区域将负责无序区域的出现。我们的方法（FoldUnfold）已经在球状蛋白质（559个蛋白质）和长无序蛋白质片段（129个蛋白质）的数据集上进行了测试，并显示出比其他一些广泛使用的方法（如DISOPRED，PONDRVL3H，IUPred和GlobPlot）更好的性能。
Identification of disordered regions in polypeptide chains is very important because such regions are essential for protein function. A new parameter, namely mean packing density of residues has been introduced to detect disordered regions in a protein sequence. We have demonstrated that regions with weak expected packing density would be responsible for the appearance of disordered regions. Our method (FoldUnfold) has been tested on datasets of globular proteins (559 proteins) and long disordered protein segments (129 proteins) and showed improved performance over some other widely used methods, such as DISOPRED, PONDR VL3H, IUPred and GlobPlot.