NDLI: Improving the performance of protein kinase identification via high dimensional protein-protein interactions and substrate structure data.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Xu, Xiaoyi Li, Ao Zou, Liang Shen, Yi Fan, Wenwen Wang, Minghui
Description	Author Affiliation: Xu X ( School of Information Science and Technology, University of Science and Technology of China, Hefei AH230027, People's Republic of China.)
Abstract	As a crucial post-translational modification, protein phosphorylation regulates almost all basic cellular processes. Recently, thousands of phosphorylation sites have been discovered by large-scale phospho-proteomics studies, but only about 20% of them have information regarding catalytic kinases, which brings a great challenge for correct identification of the protein kinases responsible for experimentally verified phosphorylation sites. In most existing identification tools, only a local sequence was selected to construct predictive models, and information regarding protein-protein interaction (PPI) was adopted for further filtering. However, the limited information utilized by these tools is not sufficient to identify protein kinases responsible for phosphorylated proteins. In this work, a novel computational approach that fully incorporates PPI and substrate structure information is proposed to improve the performance of human protein kinase identification. To handle the issue of high-dimensional PPI and structure data, a two-step feature selection algorithm that incorporates a support vector machine (SVM), is designed to detect information useful in discriminating the corresponding kinase of phosphorylation sites. Benchmark datasets for kinase identification are constructed using human protein phosphorylation data extracted from the latest Phospho.ELM database. With the selected PPI and structure features, the performance of kinase identification is significantly enhanced as compared with that obtained by using only sequence information. To further verify our method, we compared it with the state-of-the-art tools NetworKIN and IGPS at two stringency levels with medium (>90.0%) and high (>99.0%) specificity. The results show that our method outperforms existing tools in identifying protein kinases. Further evaluation demonstrates that our method also has superior performance on different hierarchical levels including kinase, subfamily, family and group.
File Format	HTM / HTML
ISSN	1742206X
Issue Number	3
Volume Number	10
e-ISSN	17422051
Journal	Molecular BioSystems
Language	English
Publisher	Royal Society of Chemistry
Publisher Date	2014-03-04
Publisher Place	Great Britain (UK)
Access Restriction	Subscribed
Subject Keyword	Discipline Molecular Biology Discipline Biochemistry Protein Interaction Mapping Protein Kinases Metabolism Area Under Curve Databases, Protein Humans Phosphorylation Methods Chemistry Protein Processing, Post-translational Roc Curve Reproducibility Of Results Substrate Specificity Journal Article Research Support, Non-u.s. Gov't
Content Type	Text
Resource Type	Article
Subject	Molecular Biology Biotechnology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in