Document Type
Article
Publication Date
2013
Digital Object Identifier (DOI)
https://doi.org/10.1093/nar/gks1226
Abstract
We present the Database of Disordered Protein Prediction (D2P2), available at http://d2p2.pro (including website source code). A battery of disorder predictors and their variants, VL-XT, VSL2b, PrDOS, PV2, Espritz and IUPred, were run on all protein sequences from 1765 complete proteomes (to be updated as more genomes are completed). Integrated with these results are all of the predicted (mostly structured) SCOP domains using the SUPERFAMILY predictor. These disorder/structure annotations together enable comparison of the disorder predictors with each other and examination of the overlap between disordered predictions and SCOP domains on a large scale. D2P2 will increase our understanding of the interplay between disorder and structure, the genomic distribution of disorder, and its evolutionary history. The parsed data are made available in a unified format for download as flat files or SQL tables either by genome, by predictor, or for the complete set. An interactive website provides a graphical view of each protein annotated with the SCOP domains and disordered regions from all predictors overlaid (or shown as a consensus). There are statistics and tools for browsing and comparing genomes and their disorder within the context of their position on the tree of life.
Rights Information
This work is licensed under a Creative Commons Attribution-Noncommercial 3.0 License
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Nucleic Acids Research, v. 41, issue D1, p. D508-D516
Scholar Commons Citation
Oates, Matt E.; Romero, Pedro R.; Ishida, Takashi; Ghalwash, Mohamed; Mizianty, Marcin J.; Xue, Bin; Dosztányi, Zsuzsanna; Uversky, Vladimir N.; Obradovic, Zoran; Kurgan, Lukasz; Dunker, A. Keith; and Gough, Julian, "D2P2: Database of Disordered Protein Predictions" (2013). Molecular Medicine Faculty Publications. 611.
https://digitalcommons.usf.edu/mme_facpub/611
