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Updated: May 30, 2026
09:38
Identification of Nucleolar Factors During HIV-1 Replication Through Rev Immunoprecipitation and Mass Spectrometry
Published on: June 26, 2019
NoD: a Nucleolar localization sequence detector for eukaryotic and viral proteins.
Michelle S Scott1, Peter V Troshin, Geoffrey J Barton
1Division of Biological Chemistry and Drug Discovery, College of Life Sciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK. michelle@compbio.dundee.ac.uk
BMC Bioinformatics
|August 5, 2011
Summary
NoD is a new tool that predicts nucleolar localization sequences (NoLSs) in proteins. This computational approach aids in understanding protein traffic and function within the nucleolus.
Area of Science:
- Cell Biology
- Bioinformatics
- Proteomics
Background:
- Nucleolar localization sequences (NoLSs) are crucial for directing proteins to the nucleolus.
- The nucleolus is a vital subnuclear compartment involved in numerous cellular processes.
- NoLSs act as regulatory elements controlling protein localization and cellular traffic.
Purpose of the Study:
- To develop and present NoD, a computational tool for predicting NoLSs in protein sequences.
- To provide a user-friendly web server and a command-line program for NoLS prediction.
- To facilitate the systematic characterization of NoLS motifs across diverse organisms.
Main Methods:
- Utilized a human-trained artificial neural network predictor.
- Developed a web server for interactive prediction of NoLS presence and location.
- Created a command-line version for high-throughput proteome-wide predictions.
Main Results:
- NoD achieved a sensitivity of 71% and a positive predictive value of 79% in independent testing.
- The tool provides a graphical output of NoLS scores along protein sequences.
- Validated predictions using experimentally verified eukaryotic and viral proteins.
Conclusions:
- NoD is the first tool offering NoLS predictions for a wide range of eukaryotes and viruses.
- The NoD web server is accessible online for interactive use.
- The downloadable command-line version allows for local, large-scale analysis.
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