Affiliation

Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, 29208, USA.

Corresponding Author

Dr. Jianjun Hu, Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, 29208, USA; Tel: +1(803)7777304; Fax:+1(803)7773747; E-mail: jianjunh@cse.sc.edu

Citation

Jianjun Hu., et al. Computational Identification of Phosphorylation Sites around Nuclear Localization Signal Sequence Reveals New Insight into Genes Associated With Human Diseases (2017) Bioinfo Proteom Img Anal 3(1): 177- 181

Copy rights

© 2017 Jianjun Hu. This is an Open access article distributed under the terms of Creative Commons Attribution 4.0 International License.

Keywords

Abstract

  Alterations in protein Subcellular localization often contribute to the development of human diseases. Post-transcriptional modifications, such as phosphorylation on the Nuclear Localization Signal (NLS), may change the protein’s localization. However, little is known about the frequency and local effects of phosphorylation near NLS sites. In this study, a computer program was developed to search various databases in order to find proteins with NLS Phosphorylations, and any diseases that are associated with those genes. 308 NLS sequences were found in the NLSdb database, resulting in the identification of 133,448 NLS-containing proteins in the Uniprot database. We cross-referenced these proteins with phosphorylation data available from the PhosphoSitePlus database and found that about 21% of these NLS-containing proteins have evidence of phosphorylation sites. After plugging this into the gene disease association database, 138 of disease-associated genes (1% of NLS-containing proteins)were identified to have phosphorylation sites on their NLS sequences. Further evaluation of the NLS phosphorylation status of these genes in clinical samples may lead to development of new biomarkers for human diseases, and shed new light into the pathogenesis of these gene-associated diseases.