The TOPCONS web server for consensus prediction of membrane protein topology and signal peptides.

The TOPCONS web server for consensus prediction of membrane protein topology and signal peptides.
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DOI:
10.1093/nar/gkv485
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发表时间:
2015-07-01
影响因子:
14.9
通讯作者:
Elofsson A
Elofsson A
中科院分区:
生物学2区
文献类型:
--
作者:
Tsirigos KD;Peters C;Shu N;Käll L;Elofsson A

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TOPCONS(http://topcons.net/)是一个广泛使用的网络服务器,用于膜蛋白拓扑结构的一致性预测。我们在此对服务器进行了重大更新,并进行了一些实质性改进,包括:(i)TOPCOS现在可以有效地将信号肽与跨膜区域分离。(ii)服务器现在可以更成功地区分球状蛋白和膜蛋白。(iii)服务器现在甚至稍微快一点,尽管使用了更大的数据库来生成多序列比对。对于大多数蛋白质,最终的预测是在几秒钟内产生的。(iv)保留了用户友好的界面,并具有提交批处理文件和使用标准界面以编程方式访问服务器的附加功能,因此非常适合蛋白质组范围的分析。用户现在可以在几天内扫描整个人类蛋白质组。(v)对于与已知的3D结构具有同源性的蛋白质,还显示同源性推断的拓扑结构。(vi)最后,与目前可用的最佳评分方法相比,目前实施的方法的组合实现了4%的性能总体提高,并且TOPCOS是唯一可以识别信号肽并仍然保持拓扑预测中最先进性能的方法。
TOPCONS (http://topcons.net/) is a widely used web server for consensus prediction of membrane protein topology. We hereby present a major update to the server, with some substantial improvements, including the following: (i) TOPCONS can now efficiently separate signal peptides from transmembrane regions. (ii) The server can now differentiate more successfully between globular and membrane proteins. (iii) The server now is even slightly faster, although a much larger database is used to generate the multiple sequence alignments. For most proteins, the final prediction is produced in a matter of seconds. (iv) The user-friendly interface is retained, with the additional feature of submitting batch files and accessing the server programmatically using standard interfaces, making it thus ideal for proteome-wide analyses. Indicatively, the user can now scan the entire human proteome in a few days. (v) For proteins with homology to a known 3D structure, the homology-inferred topology is also displayed. (vi) Finally, the combination of methods currently implemented achieves an overall increase in performance by 4% as compared to the currently available best-scoring methods and TOPCONS is the only method that can identify signal peptides and still maintain a state-of-the-art performance in topology predictions.
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