MatureP: prediction of secreted proteins with exclusive information from their mature regions

Abstract More than a third of the cellular proteome is non-cytoplasmic. Most secretory proteins use the Sec system for export and are targeted to membranes using signal peptides and mature domains. To specifically analyze bacterial mature domain features, we developed MatureP, a classifier that pred...

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Autores principales:	Georgia Orfanoudaki, Maria Markaki, Katerina Chatzi, Ioannis Tsamardinos, Anastassios Economou
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/448c13ed374e41d78ff599c062c721f9
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spelling	oai:doaj.org-article:448c13ed374e41d78ff599c062c721f92021-12-02T11:53:11ZMatureP: prediction of secreted proteins with exclusive information from their mature regions10.1038/s41598-017-03557-42045-2322https://doaj.org/article/448c13ed374e41d78ff599c062c721f92017-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-03557-4https://doaj.org/toc/2045-2322Abstract More than a third of the cellular proteome is non-cytoplasmic. Most secretory proteins use the Sec system for export and are targeted to membranes using signal peptides and mature domains. To specifically analyze bacterial mature domain features, we developed MatureP, a classifier that predicts secretory sequences through features exclusively computed from their mature domains. MatureP was trained using Just Add Data Bio, an automated machine learning tool. Mature domains are predicted efficiently with ~92% success, as measured by the Area Under the Receiver Operating Characteristic Curve (AUC). Predictions were validated using experimental datasets of mutated secretory proteins. The features selected by MatureP reveal prominent differences in amino acid content between secreted and cytoplasmic proteins. Amino-terminal mature domain sequences have enhanced disorder, more hydroxyl and polar residues and less hydrophobics. Cytoplasmic proteins have prominent amino-terminal hydrophobic stretches and charged regions downstream. Presumably, secretory mature domains comprise a distinct protein class. They balance properties that promote the necessary flexibility required for the maintenance of non-folded states during targeting and secretion with the ability of post-secretion folding. These findings provide novel insight in protein trafficking, sorting and folding mechanisms and may benefit protein secretion biotechnology.Georgia OrfanoudakiMaria MarkakiKaterina ChatziIoannis TsamardinosAnastassios EconomouNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-12 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Georgia Orfanoudaki Maria Markaki Katerina Chatzi Ioannis Tsamardinos Anastassios Economou MatureP: prediction of secreted proteins with exclusive information from their mature regions
description	Abstract More than a third of the cellular proteome is non-cytoplasmic. Most secretory proteins use the Sec system for export and are targeted to membranes using signal peptides and mature domains. To specifically analyze bacterial mature domain features, we developed MatureP, a classifier that predicts secretory sequences through features exclusively computed from their mature domains. MatureP was trained using Just Add Data Bio, an automated machine learning tool. Mature domains are predicted efficiently with ~92% success, as measured by the Area Under the Receiver Operating Characteristic Curve (AUC). Predictions were validated using experimental datasets of mutated secretory proteins. The features selected by MatureP reveal prominent differences in amino acid content between secreted and cytoplasmic proteins. Amino-terminal mature domain sequences have enhanced disorder, more hydroxyl and polar residues and less hydrophobics. Cytoplasmic proteins have prominent amino-terminal hydrophobic stretches and charged regions downstream. Presumably, secretory mature domains comprise a distinct protein class. They balance properties that promote the necessary flexibility required for the maintenance of non-folded states during targeting and secretion with the ability of post-secretion folding. These findings provide novel insight in protein trafficking, sorting and folding mechanisms and may benefit protein secretion biotechnology.
format	article
author	Georgia Orfanoudaki Maria Markaki Katerina Chatzi Ioannis Tsamardinos Anastassios Economou
author_facet	Georgia Orfanoudaki Maria Markaki Katerina Chatzi Ioannis Tsamardinos Anastassios Economou
author_sort	Georgia Orfanoudaki
title	MatureP: prediction of secreted proteins with exclusive information from their mature regions
title_short	MatureP: prediction of secreted proteins with exclusive information from their mature regions
title_full	MatureP: prediction of secreted proteins with exclusive information from their mature regions
title_fullStr	MatureP: prediction of secreted proteins with exclusive information from their mature regions
title_full_unstemmed	MatureP: prediction of secreted proteins with exclusive information from their mature regions
title_sort	maturep: prediction of secreted proteins with exclusive information from their mature regions
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/448c13ed374e41d78ff599c062c721f9
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MatureP: prediction of secreted proteins with exclusive information from their mature regions

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