Terribilini Michael, Sander Jeffry D, Lee Jae-Hyung, Zaback Peter, Jernigan Robert L, Honavar Vasant, Dobbs Drena
Department of Genetics, Development & Cell Biology, Bioinformatics & Computational Biology Program, Iowa State University, Ames, Iowa 50011, USA.
Nucleic Acids Res. 2007 Jul;35(Web Server issue):W578-84. doi: 10.1093/nar/gkm294. Epub 2007 May 5.
Understanding interactions between proteins and RNA is key to deciphering the mechanisms of many important biological processes. Here we describe RNABindR, a web-based server that identifies and displays RNA-binding residues in known protein-RNA complexes and predicts RNA-binding residues in proteins of unknown structure. RNABindR uses a distance cutoff to identify which amino acids contact RNA in solved complex structures (from the Protein Data Bank) and provides a labeled amino acid sequence and a Jmol graphical viewer in which RNA-binding residues are displayed in the context of the three-dimensional structure. Alternatively, RNABindR can use a Naive Bayes classifier trained on a non-redundant set of protein-RNA complexes from the PDB to predict which amino acids in a protein sequence of unknown structure are most likely to bind RNA. RNABindR automatically displays 'high specificity' and 'high sensitivity' predictions of RNA-binding residues. RNABindR is freely available at http://bindr.gdcb.iastate.edu/RNABindR.
了解蛋白质与RNA之间的相互作用是破译许多重要生物过程机制的关键。在此，我们描述了RNABindR，这是一个基于网络的服务器，可识别并显示已知蛋白质-RNA复合物中的RNA结合残基，并预测未知结构蛋白质中的RNA结合残基。RNABindR使用距离阈值来识别（来自蛋白质数据库的）已解析复合物结构中哪些氨基酸与RNA接触，并提供一个标记的氨基酸序列和一个Jmol图形查看器，其中RNA结合残基在三维结构背景下显示。或者，RNABindR可以使用基于来自蛋白质数据库的一组非冗余蛋白质-RNA复合物训练的朴素贝叶斯分类器，来预测未知结构蛋白质序列中哪些氨基酸最有可能结合RNA。RNABindR会自动显示RNA结合残基的“高特异性”和“高灵敏度”预测结果。可通过http://bindr.gdcb.iastate.edu/RNABindR免费访问RNABindR。
