De novo structure generation using chemical shifts for proteins with high-sequence identity but different folds.
De novo structure generation using chemical shifts for proteins with high-sequence identity but different folds.
复制标题
使用化学位移从头生成具有高序列同一性但不同折叠的蛋白质的结构。
DOI：
10.1002/pro.303
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
Bax,Ad
中科院分区：
文献类型：
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作者：
Shen,Yang;Bryan,PhilipN;He,Yanan;Orban,John;Baker,David;Bax,Ad
高序列同源性但折叠结构差异很大的蛋白质对基于序列的蛋白质结构预测方法提出了特殊的挑战。特别是，56个残基的三螺旋束蛋白(GA95)和α/β-折叠蛋白(GB95)的序列同源性为95%，是CASP-8结构预测竞赛的目标。在300个提交的GA95服务器CASP8模型中，只有12个显示了正确的折叠，尽管这种蛋白质体积很小，但被证明是特别具有挑战性的。在这里，我们证明了核磁共振化学位移中包含的信息可以很容易地被CS-Rosetta结构预测程序利用，并产生足够的收敛，即使输入化学位移仅限于1HN和15N或1HNAN1Hα值。
Proteins with high‐sequence identity but very different folds present a special challenge to sequence‐based protein structure prediction methods. In particular, a 56‐residue three‐helical bundle protein (GA95) and an α/β‐fold protein (GB95), which share 95% sequence identity, were targets in the CASP‐8 structure prediction contest. With only 12 out of 300 submitted server‐CASP8 models for GA95exhibiting the correct fold, this protein proved particularly challenging despite its small size. Here, we demonstrate that the information contained in NMR chemical shifts can readily be exploited by the CS‐Rosetta structure prediction program and yields adequate convergence, even when input chemical shifts are limited to just amide1HNand15N or1HNand1Hαvalues.