LocNES: A computational tool for locating classical NESs in CRM1 cargo proteins

Darui Xu, Kara Marquis, Jimin Pei, Szu Chin Fu, Tolga Caʇatay, Nick V. Grishin, Yuh Min Chook

Research output: Contribution to journalArticle

42 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)1357-1365
Number of pages9
JournalBioinformatics
Volume31
Issue number9
DOIs
StatePublished - Nov 5 2014

Fingerprint

Nuclear Export Signals
Peptides
Proteins
Protein
Nuclear Proteins
Macromolecules
Support vector machines
Amino acids
Position-Specific Scoring Matrices
Amino Acids
Feature Model
Prediction
Amino Acid Sequence
exportin 1 protein
Scoring
Comparative Analysis
Nucleus
Assign
Disorder
Predictors

ASJC Scopus subject areas

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

Cite this

LocNES : A computational tool for locating classical NESs in CRM1 cargo proteins. / Xu, Darui; Marquis, Kara; Pei, Jimin; Fu, Szu Chin; Caʇatay, Tolga; Grishin, Nick V.; Chook, Yuh Min.

In: Bioinformatics, Vol. 31, No. 9, 05.11.2014, p. 1357-1365.

Research output: Contribution to journalArticle

Xu, Darui ; Marquis, Kara ; Pei, Jimin ; Fu, Szu Chin ; Caʇatay, Tolga ; Grishin, Nick V. ; Chook, Yuh Min. / LocNES : A computational tool for locating classical NESs in CRM1 cargo proteins. In: Bioinformatics. 2014 ; Vol. 31, No. 9. pp. 1357-1365.
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