Predicting Functions of Disordered Proteins with MoRFpred
Document Type
Book Chapter
Publication Date
2018
Keywords
Intrinsic Disorder, Prediction, Molecular Recognition Features, Morfs, Protein-protein Interactions, Morfpred
Digital Object Identifier (DOI)
https://doi.org/10.1007/978-1-4939-8736-8_19
Abstract
Intrinsically disordered proteins and regions are involved in a wide range of cellular functions, and they often facilitate protein-protein interactions. Molecular recognition features (MoRFs) are segments of intrinsically disordered regions that bind to partner proteins, where binding is concomitant with a transition to a structured conformation. MoRFs facilitate translation, transport, signaling, and regulatory processes and are found across all domains of life. A popular computational tool, MoRFpred, accurately predicts MoRFs in protein sequences. MoRFpred is implemented as a user-friendly web server that is freely available at http://biomine.cs.vcu.edu/servers/MoRFpred/. We describe this predictor, explain how to run the web server, and show how to interpret the results it generates. We also demonstrate the utility of this web server based on two case studies, focusing on the relevance of evolutionary conservation of MoRF regions.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Predicting Functions of Disordered Proteins with MoRFpred, in T. Sikosek (Ed.), Computational Methods in Protein Evolution, p. 337-352
Scholar Commons Citation
Oldfield, Christopher J.; Uversky, Vladimir N.; and Kurgan, Lukasz, "Predicting Functions of Disordered Proteins with MoRFpred" (2018). Molecular Medicine Faculty Publications. 1095.
https://digitalcommons.usf.edu/mme_facpub/1095
