DescribePROT: database of amino acid-level protein structure and function predictions

Author:

Zhao Bi1,Katuwawala Akila1,Oldfield Christopher J1,Dunker A Keith2,Faraggi Eshel3,Gsponer Jörg4,Kloczkowski Andrzej3,Malhis Nawar4,Mirdita Milot5,Obradovic Zoran6,Söding Johannes5ORCID,Steinegger Martin7,Zhou Yaoqi8ORCID,Kurgan Lukasz1ORCID

Affiliation:

1. Department of Computer Science, Virginia Commonwealth University, Richmond, VA, USA

2. Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA

3. Battelle Center for Mathematical Medicine at the Nationwide Children's Hospital, and Department of Pediatrics, The Ohio State University, Columbus, OH, USA

4. Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada

5. Quantitative and Computational Biology, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany

6. Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA

7. School of Biological Sciences and Institute of Molecular Biology & Genetics, Seoul National University, Seoul, Republic of Korea

8. Institute for Glycomics, Griffith University, Gold Coast, Queensland, Australia

Abstract

AbstractWe 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/.

Funder

National Science Foundation

National Institutes of Health

Robert J. Mattauch Endowment

Publisher

Oxford University Press (OUP)

Subject

Genetics

Reference102 articles.

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3. UniProtKB/Swiss-Prot, the manually annotated section of the UniProt KnowledgeBase: how to use the entry view;Boutet;Methods Mol. Biol.,2016

4. Prediction in 1D: secondary structure, membrane helices, and accessibility;Rost;Methods Biochem. Anal.,2003

5. Structural protein descriptors in 1-dimension and their sequence-based predictions;Kurgan;Curr. Protein Pept. Sci.,2011

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