School of Computer Science and Software Engineering, Tianjin Polytechnic University, Hedong District, Tianjin 300160, PR of China.
Bioinformatics. 2012 Feb 1;28(3):331-41. doi: 10.1093/bioinformatics/btr657. Epub 2011 Nov 29.
Nucleotides are multifunctional molecules that are essential for numerous biological processes. They serve as sources for chemical energy, participate in the cellular signaling and they are involved in the enzymatic reactions. The knowledge of the nucleotide-protein interactions helps with annotation of protein functions and finds applications in drug design.
We propose a novel ensemble of accurate high-throughput predictors of binding residues from the protein sequence for ATP, ADP, AMP, GTP and GDP. Empirical tests show that our NsitePred method significantly outperforms existing predictors and approaches based on sequence alignment and residue conservation scoring. The NsitePred accurately finds more binding residues and binding sites and it performs particularly well for the sites with residues that are clustered close together in the sequence. The high predictive quality stems from the usage of novel, comprehensive and custom-designed inputs that utilize information extracted from the sequence, evolutionary profiles, several sequence-predicted structural descriptors and sequence alignment. Analysis of the predictive model reveals several sequence-derived hallmarks of nucleotide-binding residues; they are usually conserved and flanked by less conserved residues, and they are associated with certain arrangements of secondary structures and amino acid pairs in the specific neighboring positions in the sequence.
http://biomine.ece.ualberta.ca/nSITEpred/
Supplementary data are available at Bioinformatics online.
核苷酸是多功能分子,对许多生物过程至关重要。它们是化学能的来源,参与细胞信号传递,并且参与酶反应。核苷酸-蛋白质相互作用的知识有助于注释蛋白质功能,并在药物设计中得到应用。
我们提出了一种新的用于预测 ATP、ADP、AMP、GTP 和 GDP 结合残基的准确高通量蛋白质序列预测器的集合。实证测试表明,我们的 NsitePred 方法显著优于现有的基于序列比对和残基保守评分的预测器和方法。NsitePred 可以准确地找到更多的结合残基和结合位点,并且对于序列中紧密聚集在一起的残基的位点表现特别好。高预测质量源于使用新颖、全面和定制设计的输入,这些输入利用从序列、进化轮廓、几个序列预测的结构描述符和序列比对中提取的信息。对预测模型的分析揭示了核苷酸结合残基的几个序列衍生特征;它们通常是保守的,并且被不太保守的残基所包围,并且与特定序列中特定相邻位置的二级结构和氨基酸对的某些排列相关联。
http://biomine.ece.ualberta.ca/nSITEpred/
补充数据可在 Bioinformatics 在线获得。