DescribePROT: database of amino acid-level protein structure and function predictions
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Journal articleDate
2020-10-29Author
Zhao, BiKatuwawala, Akila
Oldfield, Christopher J.
Dunker, A. Keith
Faraggi, Eshel
Gsponer, Jörg
Kloczkowski, Andrzej
Malhis, Nawar
Mirdita, Milot
Obradovic, Zoran
Söding, Johannes
Steinegger, Martin
Zhou, Yaoqi
Kurgan, Lukasz
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http://hdl.handle.net/20.500.12613/6176
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https://doi.org/10.1093/nar/gkaa931Abstract
We present DescribePROT, the database of predicted amino acid-level descriptors of structure and function of proteins. DescribePROT delivers a comprehensive collection of 13 complementary descriptors predicted using 10 popular and accurate algorithms for 83 complete proteomes that cover key model organisms. The current version includes 7.8 billion predictions for close to 600 million amino acids in 1.4 million proteins. The descriptors encompass sequence conservation, position specific scoring matrix, secondary structure, solvent accessibility, intrinsic disorder, disordered linkers, signal peptides, MoRFs and interactions with proteins, DNA and RNAs. Users can search DescribePROT by the amino acid sequence and the UniProt accession number and entry name. The pre-computed results are made available instantaneously. The predictions can be accesses via an interactive graphical interface that allows simultaneous analysis of multiple descriptors and can be also downloaded in structured formats at the protein, proteome and whole database scale. The putative annotations included by DescriPROT are useful for a broad range of studies, including: investigations of protein function, applied projects focusing on therapeutics and diseases, and in the development of predictors for other protein sequence descriptors. Future releases will expand the coverage of DescribePROT. DescribePROT can be accessed at http://biomine.cs.vcu.edu/servers/DESCRIBEPROT/.Citation
Bi Zhao, Akila Katuwawala, Christopher J Oldfield, et al. DescribePROT: database of amino acid-level protein structure and function predictions, Nucleic Acids Research, Volume 49, Issue D1, 8 January 2021, Pages D298–D308, https://doi.org/10.1093/nar/gkaa931Citation to related work
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Nucleic Acids Research, Vol. 49, Issue D1ADA compliance
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http://dx.doi.org/10.34944/dspace/6158
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