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- Title
LocNES: a computational tool for locating classical NESs in CRM1 cargo proteins.
- Authors
Darui Xu; Marquis, Kara; Jimin Pei; Szu-Chin Fu; Cağatay, Tolga; Grishin, Nick V.; Yuh Min Chook
- Abstract
Motivation: Classical nuclear export signals (NESs) are short cognate peptides that direct proteins out of the nucleus via the CRM1-mediated export pathway. CRM1 regulates the localization of hundreds of macromolecules involved in various cellular functions and diseases. Due to the diverse and complex nature of NESs, reliable prediction of the signal remains a challenge despite several attempts made in the last decade. Results: We present a new NES predictor, LocNES. LocNES scans query proteins for NES consensus-fitting peptides and assigns these peptides probability scores using Support Vector Machine model, whose feature set includes amino acid sequence, disorder propensity, and the rank of position-specific scoring matrix score. LocNES demonstrates both higher sensitivity and precision over existing NES prediction tools upon comparative analysis using experimentally identified NESs.
- Subjects
PROTEIN analysis; AMINO acid sequence; NUCLEAR proteins; COMPUTER software
- Publication
Bioinformatics, 2015, Vol 31, Issue 9, p1357
- ISSN
1367-4803
- Publication type
Product Review
- DOI
10.1093/bioinformatics/btu826