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革兰氏阴性菌中分泌蛋白的计算预测。

Computational prediction of secreted proteins in gram-negative bacteria.

作者信息

Hui Xinjie, Chen Zewei, Zhang Junya, Lu Moyang, Cai Xuxia, Deng Yuping, Hu Yueming, Wang Yejun

机构信息

Youth Innovation Team of Medical Bioinformatics, Shenzhen University Health Science Center, Shenzhen 518060, China.

College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China.

出版信息

Comput Struct Biotechnol J. 2021 Mar 22;19:1806-1828. doi: 10.1016/j.csbj.2021.03.019. eCollection 2021.

Abstract

Gram-negative bacteria harness multiple protein secretion systems and secrete a large proportion of the proteome. Proteins can be exported to periplasmic space, integrated into membrane, transported into extracellular milieu, or translocated into cytoplasm of contacting cells. It is important for accurate, genome-wide annotation of the secreted proteins and their secretion pathways. In this review, we systematically classified the secreted proteins according to the types of secretion systems in Gram-negative bacteria, summarized the known features of these proteins, and reviewed the algorithms and tools for their prediction.

摘要

革兰氏阴性菌利用多种蛋白质分泌系统,并分泌大部分蛋白质组。蛋白质可以输出到周质空间、整合到细胞膜中、运输到细胞外环境中,或转移到接触细胞的细胞质中。准确地对分泌蛋白及其分泌途径进行全基因组注释非常重要。在本综述中,我们根据革兰氏阴性菌分泌系统的类型对分泌蛋白进行了系统分类,总结了这些蛋白的已知特征,并综述了其预测算法和工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61ae/8047123/386e8959aa3e/gr3.jpg

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