Prediction of Disordered RNA, DNA, and Protein Binding Regions Using DisoRDPbind
Document Type
Book Chapter
Publication Date
2016
Keywords
Intrinsic Disorder, Prediction, Protein–protein Interactions, Protein–dna Interactions, Protein–rna Interactions, Disordpbind
Digital Object Identifier (DOI)
https://doi.org/10.1007/978-1-4939-6406-2_14
Abstract
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.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Prediction of Disordered RNA, DNA, and Protein Binding Regions Using DisoRDPbind, in Y. Zhou, A. Kloczkowski, E. Faraggi & Y. Yang (Eds.), Prediction of Protein Secondary Structure, Humana Press, p. 187-203
Scholar Commons Citation
Peng, Zhenling; Wang, Chen; Uversky, Vladimir N.; and Kurgan, Lukasz, "Prediction of Disordered RNA, DNA, and Protein Binding Regions Using DisoRDPbind" (2016). Molecular Medicine Faculty Publications. 1098.
https://digitalcommons.usf.edu/mme_facpub/1098
