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Int. J. Mol. Sci. 2015, 16(10), 23446-23462; doi:10.3390/ijms161023446

An Overview of Predictors for Intrinsically Disordered Proteins over 2010–2014

1,†
,
1,†
,
1
,
1,2
,
1
,
1
and
1,2,3,*
1
College of Life Sciences & Key Laboratory of Ministry of Education for Bio-Resources and Bio-Environment, Sichuan University, Chengdu 610064, China
2
State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, China
3
State Key Laboratory of Oral Diseases, West China College of Stomatology, Sichuan University, Chengdu 610041, China
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editors: Lukasz Kurgan and Vladimir N. Uversky
Received: 31 May 2015 / Revised: 25 August 2015 / Accepted: 31 August 2015 / Published: 29 September 2015
View Full-Text   |   Download PDF [3395 KB, uploaded 29 September 2015]   |  

Abstract

The sequence-structure-function paradigm of proteins has been changed by the occurrence of intrinsically disordered proteins (IDPs). Benefiting from the structural disorder, IDPs are of particular importance in biological processes like regulation and signaling. IDPs are associated with human diseases, including cancer, cardiovascular disease, neurodegenerative diseases, amyloidoses, and several other maladies. IDPs attract a high level of interest and a substantial effort has been made to develop experimental and computational methods. So far, more than 70 prediction tools have been developed since 1997, within which 17 predictors were created in the last five years. Here, we presented an overview of IDPs predictors developed during 2010–2014. We analyzed the algorithms used for IDPs prediction by these tools and we also discussed the basic concept of various prediction methods for IDPs. The comparison of prediction performance among these tools is discussed as well. View Full-Text
Keywords: intrinsically disordered proteins; predictor; computational methods intrinsically disordered proteins; predictor; computational methods
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Li, J.; Feng, Y.; Wang, X.; Li, J.; Liu, W.; Rong, L.; Bao, J. An Overview of Predictors for Intrinsically Disordered Proteins over 2010–2014. Int. J. Mol. Sci. 2015, 16, 23446-23462.

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