Comprehensive Review of Methods for Prediction of Intrinsic Disorder and Its Molecular Functions
Document Type
Article
Publication Date
2017
Keywords
Intrinsic disorder, Prediction, Function of disordered proteins, Protein–protein interactions, Protein–RNA interactions, Protein–DNA interactions, MoRF, SLiM
Digital Object Identifier (DOI)
https://doi.org/10.1007/s00018-017-2555-4
Abstract
Computational prediction of intrinsic disorder in protein sequences dates back to late 1970 and has flourished in the last two decades. We provide a brief historical overview, and we review over 30 recent predictors of disorder. We are the first to also cover predictors of molecular functions of disorder, including 13 methods that focus on disordered linkers and disordered protein–protein, protein–RNA, and protein–DNA binding regions. We overview their predictive models, usability, and predictive performance. We highlight newest methods and predictors that offer strong predictive performance measured based on recent comparative assessments. We conclude that the modern predictors are relatively accurate, enjoy widespread use, and many of them are fast. Their predictions are conveniently accessible to the end users, via web servers and databases that store pre-computed predictions for millions of proteins. However, research into methods that predict many not yet addressed functions of intrinsic disorder remains an outstanding challenge.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Cellular and Molecular Life Sciences, v. 74, p. 3069-3090
Scholar Commons Citation
Meng, Fanchi; Uversky, Vladimir N.; and Kurgan, Lukasz, "Comprehensive Review of Methods for Prediction of Intrinsic Disorder and Its Molecular Functions" (2017). Molecular Medicine Faculty Publications. 271.
https://digitalcommons.usf.edu/mme_facpub/271
