Paircoil2：基于序列对卷曲螺旋的预测能力提升

Paircoil2: improved prediction of coiled coils from sequence.

作者信息

McDonnell A V, Jiang T, Keating A E, Berger B

机构信息

Mathematics Department, Computer Science and Artificial Intelligence Laboratory, Cambridge, MA 02139, USA.

出版信息

Bioinformatics. 2006 Feb 1;22(3):356-8. doi: 10.1093/bioinformatics/bti797. Epub 2005 Nov 29.

DOI:10.1093/bioinformatics/bti797

PMID:16317077

Abstract

We introduce Paircoil2, a new version of the Paircoil program, which uses pairwise residue probabilities to detect coiled-coil motifs in protein sequence data. Paircoil2 achieves 98% sensitivity and 97% specificity on known coiled coils in leave-family-out cross-validation. It also shows superior performance compared with published methods in tests on proteins of known structure.

摘要

我们推出了Paircoil2，它是Paircoil程序的新版本，利用成对残基概率来检测蛋白质序列数据中的卷曲螺旋基序。在留族交叉验证中，Paircoil2对已知的卷曲螺旋的灵敏度达到98%，特异性达到97%。在对已知结构蛋白质的测试中，它也比已发表的方法表现更优。