scholarly journals Chemical shift assignments and secondary structure prediction of the C-terminal domain of the response regulator BfmR from Acinetobacter baumannii

2012 ◽  
Vol 8 (1) ◽  
pp. 67-70 ◽  
Author(s):  
Andrew L. Olson ◽  
Richele J. Thompson ◽  
Christian Melander ◽  
John Cavanagh
Keyword(s):  
Chemical Shift ◽  
Secondary Structure ◽  
Acinetobacter Baumannii ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
Response Regulator ◽  
Chemical Shift Assignments ◽  
Terminal Domain

PROTEIN SECONDARY STRUCTURE PREDICTION USING NMR CHEMICAL SHIFT DATA

2010 ◽  
Vol 08 (05) ◽  
pp. 867-884 ◽  
Author(s):  
YUZHONG ZHAO ◽  
BABAK ALIPANAHI ◽  
SHUAI CHENG LI ◽  
MING LI
Keyword(s):  
Chemical Shift ◽  
Secondary Structure ◽  
Structure Prediction ◽  
Nearest Neighbor ◽  
Tertiary Structure ◽  
Secondary Structure Prediction ◽  
Accurate Determination ◽  
Protein Secondary Structure ◽  
Sequence Information ◽  
K Nearest Neighbor

Accurate determination of protein secondary structure from the chemical shift information is a key step for NMR tertiary structure determination. Relatively few work has been done on this subject. There needs to be a systematic investigation of algorithms that are (a) robust for large datasets; (b) easily extendable to (the dynamic) new databases; and (c) approaching to the limit of accuracy. We introduce new approaches using k-nearest neighbor algorithm to do the basic prediction and use the BCJR algorithm to smooth the predictions and combine different predictions from chemical shifts and based on sequence information only. Our new system, SUCCES, improves the accuracy of all existing methods on a large dataset of 805 proteins (at 86% Q3 accuracy and at 92.6% accuracy when the boundary residues are ignored), and it is easily extendable to any new dataset without requiring any new training. The software is publicly available at .

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