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DescribePROT in 2023: more, higher-quality and experimental annotations and improved data download options

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Basu, Sushmita; Zhao, Bi; Biro, Balint; Faraggi, Eshel; Gsponer, Jorg; Hu, Gang; Kloczkowski, Andrzej; Malhis, Nawar; Mirdita, Milot; Soeding, Johannes; Steinegger, Martin; Wang, Duolin; Wang, Kui; Xu, Dong; Zhang, Jian; Kurgan, Lukasz

Issue Date
Oxford University Press
Nucleic Acids Research, Vol.52 No.D1, pp.D426-D433
The DescribePROT database of amino acid-level descriptors of protein structures and functions was substantially expanded since its release in 2020. This expansion includes substantial increase in the size, scope, and quality of the underlying data, the addition of experimental structural information, the inclusion of new data download options, and an upgraded graphical interface. DescribePROT currently covers 19 structural and functional descriptors for proteins in 273 reference proteomes generated by 11 accurate and complementary predictive tools. Users can search our resource in multiple ways, interact with the data using the graphical interface, and download data at various scales including individual proteins, entire proteomes, and whole database. The annotations in DescribePROT are useful for a broad spectrum of studies that include investigations of protein structure and function, development and validation of predictive tools, and to support efforts in understanding molecular underpinnings of diseases and development of therapeutics. DescribePROT can be freely accessed at Graphical Abstract
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Related Researcher

  • College of Natural Sciences
  • School of Biological Sciences
Research Area Development of algorithms to search, cluster and assemble sequence data, Metagenomic analysis, Pathogen detection in sequencing data


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