Rosetta Protein Structure Prediction from Hydroxyl Radical Protein Footprinting Mass Spectrometry Data.
Rosetta Protein Structure Prediction from Hydroxyl Radical Protein Footprinting Mass Spectrometry Data.
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DOI：
10.1021/acs.analchem.8b01624
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发表时间：
2018-06-19
影响因子：
7.4
通讯作者：
Lindert S
中科院分区：
文献类型：
--
作者：
Aprahamian ML;Chea EE;Jones LM;Lindert S
近年来，以质谱为基础的共价标记技术，如羟基自由基足迹（HRF）已成为一种有价值的结构生物学技术，可以提供蛋白质三级结构的信息。然而，这些数据还不足以明确地预测蛋白质结构，因为它只提供了某些残留物相对溶剂暴露的信息。尽管最近取得了一些进展，但目前还没有软件可以利用共价标记质谱数据来预测蛋白质三级结构。我们已经开发了第一个这样的工具，它结合了质谱法从HRF标记中获得的保护因子，作为Rosetta评分函数的新质心评分项，以提高蛋白质三级结构的预测。我们在一组已知晶体结构的四种可溶性基准蛋白上测试了我们的方法，这些蛋白要么是已发表的HRF实验结果，要么是内部获得的数据。利用HRF标记数据，我们重新获得了Rosetta预测的四种基准蛋白的大型诱饵结构集。结果，与单独使用Rosetta评分相比，所有基准蛋白质的模型质量都有所提高。对于四种蛋白质中的两种，我们甚至能够通过添加HRF数据来识别原子分辨率模型。
In recent years mass spectrometry-based covalent labeling techniques such as hydroxyl radical footprinting (HRF) have emerged as valuable structural biology techniques yielding information on protein tertiary structure. This data, however, is not sufficient to predict protein structure unambiguously, as it only provides information on the relative solvent exposure of certain residues. Despite some recent advances, no software currently exists that can utilize covalent labeling mass spectrometry data to predict protein tertiary structure. We have developed the first such tool, which incorporates mass spectrometry derived protection factors from HRF labeling as a new centroid score term for the Rosetta scoring function to improve the prediction of protein tertiary structure. We tested our method on a set of four soluble benchmark proteins with known crystal structures and either published HRF experimental results or internally acquired data. Using the HRF labeling data, we rescored large decoy sets of structures predicted with Rosetta for each of the four benchmark proteins. As a result, the model quality improved for all benchmark proteins, as compared to when scored with Rosetta alone. For two of the four proteins, we were even able to identify atomic resolution models with the addition of HRF data.
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影响因子：
2.2
作者：
Durham, Elizabeth;Dorr, Brent;Woetzel, Nils;Staritzbichler, Rene;Meiler, Jens
通讯作者：
Meiler, Jens
影响因子：
64.8
作者：
Bhardwaj, Gaurav;Mulligan, Vikram Khipple;Bahl, Christopher D.;Gilmore, Jason M.;Harvey, Peta J.;Cheneval, Olivier;Buchko, Garry W.;Pulavarti, Surya V. S. R. K.;Kaas, Quentin;Eletsky, Alexander;Huang, Po-Ssu;Johnsen, William A.;Greisen, Per Jr;Rocklin, Gabriel J.;Song, Yifan;Linsky, Thomas W.;Watkins, Andrew;Rettie, Stephen A.;Xu, Xianzhong;Carter, Lauren P.;Bonneau, Richard;Olson, James M.;Coutsias, Evangelos;Correnti, Colin E.;Szyperski, Thomas;Craik, David J.;Baker, David
通讯作者：
Baker, David
影响因子：
5.6
作者：
Jiang, W;Baker, ML;Chiu, W
通讯作者：
Chiu, W
影响因子：
2
作者：
KATTA, V;CHAIT, BT
通讯作者：
CHAIT, BT
通过 iSPOT 进行多蛋白复合物的理论建模：小角度 X 射线散射、羟基自由基足迹和计算对接的集成。
影响因子：
3
作者：
Huang, Wei;Ravikumar, Krishnakumar M.;Parisien, Marc;Yang, Sichun
通讯作者：
Yang, Sichun