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利用末端疏水性螺旋规则提高拓扑预测。

Improved topology prediction using the terminal hydrophobic helices rule.

机构信息

Department of Biochemistry and Biophysics, Science for Life Laboratory and.

Department of Biochemistry and Biophysics, Science for Life Laboratory and Sweden Bioinformatics Infrastructure for Life Sciences (BILS), Stockholm University, Solna 17121, Sweden.

出版信息

Bioinformatics. 2016 Apr 15;32(8):1158-62. doi: 10.1093/bioinformatics/btv709. Epub 2015 Dec 7.

Abstract

MOTIVATION

The translocon recognizes sufficiently hydrophobic regions of a protein and inserts them into the membrane. Computational methods try to determine what hydrophobic regions are recognized by the translocon. Although these predictions are quite accurate, many methods still fail to distinguish marginally hydrophobic transmembrane (TM) helices and equally hydrophobic regions in soluble protein domains. In vivo, this problem is most likely avoided by targeting of the TM-proteins, so that non-TM proteins never see the translocon. Proteins are targeted to the translocon by an N-terminal signal peptide. The targeting is also aided by the fact that the N-terminal helix is more hydrophobic than other TM-helices. In addition, we also recently found that the C-terminal helix is more hydrophobic than central helices. This information has not been used in earlier topology predictors.

RESULTS

Here, we use the fact that the N- and C-terminal helices are more hydrophobic to develop a new version of the first-principle-based topology predictor, SCAMPI. The new predictor has two main advantages; first, it can be used to efficiently separate membrane and non-membrane proteins directly without the use of an extra prefilter, and second it shows improved performance for predicting the topology of membrane proteins that contain large non-membrane domains.

AVAILABILITY AND IMPLEMENTATION

The predictor, a web server and all datasets are available at http://scampi.bioinfo.se/

CONTACT

arne@bioinfo.se

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

动机

易位子识别蛋白中足够疏水的区域,并将其插入膜中。计算方法试图确定易位子识别哪些疏水区。尽管这些预测相当准确,但许多方法仍然无法区分边缘疏水性跨膜(TM)螺旋和可溶性蛋白结构域中同样疏水性的区域。在体内,这个问题很可能通过 TM 蛋白的靶向来避免,这样非 TM 蛋白就永远不会看到易位子。蛋白质通过 N 端信号肽被靶向到易位子。N 端螺旋比其他 TM 螺旋更疏水,这也有助于靶向。此外,我们最近还发现 C 端螺旋比中心螺旋更疏水。这些信息在早期的拓扑预测器中没有被使用。

结果

在这里,我们利用 N 端和 C 端螺旋更疏水的事实,开发了一种基于第一性原理的拓扑预测器 SCAMPI 的新版本。新的预测器有两个主要优点;首先,它可以用于有效地直接分离膜和非膜蛋白,而无需使用额外的预滤波器,其次,它在预测含有大非膜结构域的膜蛋白拓扑方面表现出了改进的性能。

可用性和实现

预测器、一个网络服务器和所有数据集都可以在 http://scampi.bioinfo.se/ 上获得。

联系方式

arne@bioinfo.se

补充信息

补充数据可在在线生物信息学中获得。

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