DisEnrich: database of enriched regions in human dark proteome

Author:

Medvedev Kirill E1ORCID,Pei Jimin2ORCID,Grishin Nick V134

Affiliation:

1. Department of Biophysics, University of Texas Southwestern Medical Center , Dallas, TX 75390, USA

2. McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center , Dallas, TX 75390, USA

3. Department of Biochemistry, University of Texas Southwestern Medical Center , Dallas, TX 75390, USA

4. Howard Hughes Medical Institute, University of Texas Southwestern Medical Center , Dallas, TX 75390, USA

Abstract

Abstract Motivation Intrinsically disordered proteins (IDPs) are involved in numerous processes crucial for living organisms. Bias in amino acid composition of these proteins determines their unique biophysical and functional features. Distinct intrinsically disordered regions (IDRs) with compositional bias play different important roles in various biological processes. IDRs enriched in particular amino acids in human proteome have not been described consistently. Results We developed DisEnrich—the database of human proteome IDRs that are significantly enriched in particular amino acids. Each human protein is described using Gene Ontology (GO) function terms, disorder prediction for the full-length sequence using three methods, enriched IDR composition and ranks of human proteins with similar enriched IDRs. Distribution analysis of enriched IDRs among broad functional categories revealed significant overrepresentation of R- and Y-enriched IDRs in metabolic and enzymatic activities and F-enriched IDRs in transport. About 75% of functional categories contain IDPs with IDRs significantly enriched in hydrophobic residues that are important for protein–protein interactions. Availability and implementation The database is available at http://prodata.swmed.edu/DisEnrichDB/. Supplementary information Supplementary data are available at Bioinformatics Advances online.

Funder

National Institutes of Health

Welch Foundation

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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