Peng Zhenling, Wang Chen, Uversky Vladimir N, Kurgan Lukasz
Center for Applied Mathematics, Tianjin University, Tianjin, 300072, China.
Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada, T6G 2V4.
Methods Mol Biol. 2017;1484:187-203. doi: 10.1007/978-1-4939-6406-2_14.
Intrinsically disordered proteins and regions (IDPs and IDRs) are involved in a wide range of cellular functions and they often facilitate interactions with RNAs, DNAs, and proteins. Although many computational methods can predict IDPs and IDRs in protein sequences, only a few methods predict their functions and these functions primarily concern protein binding. We describe how to use the first computational method DisoRDPbind for high-throughput prediction of multiple functions of disordered regions. Our method predicts the RNA-, DNA-, and protein-binding residues located in IDRs in the input protein sequences. DisoRDPbind provides accurate predictions and is sufficiently fast to make predictions for full genomes. Our method is implemented as a user-friendly webserver that is freely available at http://biomine.ece.ualberta.ca/DisoRDPbind/ . We overview our predictor, discuss how to run the webserver, and show how to interpret the corresponding results. We also demonstrate the utility of our method based on two case studies, human BRCA1 protein that binds various proteins and DNA, and yeast 60S ribosomal protein L4 that interacts with proteins and RNA.
内在无序蛋白质和区域(IDP和IDR)参与广泛的细胞功能,它们常常促进与RNA、DNA和蛋白质的相互作用。尽管许多计算方法能够预测蛋白质序列中的IDP和IDR,但只有少数方法能预测它们的功能,且这些功能主要涉及蛋白质结合。我们描述了如何使用第一种计算方法DisoRDPbind对无序区域的多种功能进行高通量预测。我们的方法预测输入蛋白质序列中位于IDR内的RNA、DNA和蛋白质结合残基。DisoRDPbind能提供准确的预测,并且速度足够快,可以对全基因组进行预测。我们的方法实现为一个用户友好的网络服务器,可在http://biomine.ece.ualberta.ca/DisoRDPbind/免费获取。我们概述了我们的预测器,讨论了如何运行网络服务器,并展示了如何解释相应的结果。我们还基于两个案例研究展示了我们方法的实用性,这两个案例分别是与多种蛋白质和DNA结合的人类BRCA1蛋白,以及与蛋白质和RNA相互作用的酵母60S核糖体蛋白L4。