SProtP: a web server to recognize those short-lived proteins based on sequence-derived features in human cells.

Protein turnover metabolism plays important roles in cell cycle progression, signal transduction, and differentiation. Those proteins with short half-lives are involved in various regulatory processes. To better understand the regulation of cell process, it is important to study the key sequence-der...

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Autores principales:	Xiaofeng Song, Tao Zhou, Hao Jia, Xuejiang Guo, Xiaobai Zhang, Ping Han, Jiahao Sha
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2011
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/981e692202094d679e31603874f983ca
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id	oai:doaj.org-article:981e692202094d679e31603874f983ca
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spelling	oai:doaj.org-article:981e692202094d679e31603874f983ca2021-11-18T07:34:04ZSProtP: a web server to recognize those short-lived proteins based on sequence-derived features in human cells.1932-620310.1371/journal.pone.0027836https://doaj.org/article/981e692202094d679e31603874f983ca2011-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22114707/?tool=EBIhttps://doaj.org/toc/1932-6203Protein turnover metabolism plays important roles in cell cycle progression, signal transduction, and differentiation. Those proteins with short half-lives are involved in various regulatory processes. To better understand the regulation of cell process, it is important to study the key sequence-derived factors affecting short-lived protein degradation. Until now, most of protein half-lives are still unknown due to the difficulties of traditional experimental methods in measuring protein half-lives in human cells. To investigate the molecular determinants that affect short-lived proteins, a computational method was proposed in this work to recognize short-lived proteins based on sequence-derived features in human cells. In this study, we have systematically analyzed many features that perhaps correlated with short-lived protein degradation. It is found that a large fraction of proteins with signal peptides and transmembrane regions in human cells are of short half-lives. We have constructed an SVM-based classifier to recognize short-lived proteins, due to the fact that short-lived proteins play pivotal roles in the control of various cellular processes. By employing the SVM model on human dataset, we achieved 80.8% average sensitivity and 79.8% average specificity, respectively, on ten testing dataset (TE1-TE10). We also obtained 89.9%, 99% and 83.9% of average accuracy on an independent validation datasets iTE1, iTE2 and iTE3 respectively. The approach proposed in this paper provides a valuable alternative for recognizing the short-lived proteins in human cells, and is more accurate than the traditional N-end rule. Furthermore, the web server SProtP (http://reprod.njmu.edu.cn/sprotp) has been developed and is freely available for users.Xiaofeng SongTao ZhouHao JiaXuejiang GuoXiaobai ZhangPing HanJiahao ShaPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 6, Iss 11, p e27836 (2011)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Xiaofeng Song Tao Zhou Hao Jia Xuejiang Guo Xiaobai Zhang Ping Han Jiahao Sha SProtP: a web server to recognize those short-lived proteins based on sequence-derived features in human cells.
description	Protein turnover metabolism plays important roles in cell cycle progression, signal transduction, and differentiation. Those proteins with short half-lives are involved in various regulatory processes. To better understand the regulation of cell process, it is important to study the key sequence-derived factors affecting short-lived protein degradation. Until now, most of protein half-lives are still unknown due to the difficulties of traditional experimental methods in measuring protein half-lives in human cells. To investigate the molecular determinants that affect short-lived proteins, a computational method was proposed in this work to recognize short-lived proteins based on sequence-derived features in human cells. In this study, we have systematically analyzed many features that perhaps correlated with short-lived protein degradation. It is found that a large fraction of proteins with signal peptides and transmembrane regions in human cells are of short half-lives. We have constructed an SVM-based classifier to recognize short-lived proteins, due to the fact that short-lived proteins play pivotal roles in the control of various cellular processes. By employing the SVM model on human dataset, we achieved 80.8% average sensitivity and 79.8% average specificity, respectively, on ten testing dataset (TE1-TE10). We also obtained 89.9%, 99% and 83.9% of average accuracy on an independent validation datasets iTE1, iTE2 and iTE3 respectively. The approach proposed in this paper provides a valuable alternative for recognizing the short-lived proteins in human cells, and is more accurate than the traditional N-end rule. Furthermore, the web server SProtP (http://reprod.njmu.edu.cn/sprotp) has been developed and is freely available for users.
format	article
author	Xiaofeng Song Tao Zhou Hao Jia Xuejiang Guo Xiaobai Zhang Ping Han Jiahao Sha
author_facet	Xiaofeng Song Tao Zhou Hao Jia Xuejiang Guo Xiaobai Zhang Ping Han Jiahao Sha
author_sort	Xiaofeng Song
title	SProtP: a web server to recognize those short-lived proteins based on sequence-derived features in human cells.
title_short	SProtP: a web server to recognize those short-lived proteins based on sequence-derived features in human cells.
title_full	SProtP: a web server to recognize those short-lived proteins based on sequence-derived features in human cells.
title_fullStr	SProtP: a web server to recognize those short-lived proteins based on sequence-derived features in human cells.
title_full_unstemmed	SProtP: a web server to recognize those short-lived proteins based on sequence-derived features in human cells.
title_sort	sprotp: a web server to recognize those short-lived proteins based on sequence-derived features in human cells.
publisher	Public Library of Science (PLoS)
publishDate	2011
url	https://doaj.org/article/981e692202094d679e31603874f983ca
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SProtP: a web server to recognize those short-lived proteins based on sequence-derived features in human cells.

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