Accurate Determination of Protein Secondary Structure Content from Raman and Raman Optical Activity Spectra

2010 ◽  
Vol 82 (15) ◽  
pp. 6347-6349 ◽  
Author(s):  
Myra N. Kinalwa ◽  
Ewan W. Blanch ◽  
Andrew J. Doig
2014 ◽  
Vol 6 (6) ◽  
pp. 1691-1699 ◽  
Author(s):  
Olayinka O. Oshokoya ◽  
Carol A. Roach ◽  
Renee D. JiJi

Determination of protein secondary structure (α-helical, β-sheet, and disordered motifs) has become an area of great importance in biochemistry and biophysics as protein secondary structure is directly related to protein function and protein related diseases.


Talanta ◽  
1993 ◽  
Vol 40 (4) ◽  
pp. 545-549 ◽  
Author(s):  
Prasad L. Polavarapu ◽  
Simeon T. Pickard ◽  
Howard E. Smith ◽  
Thomas M. Black ◽  
Laurence D. Barron ◽  
...  

2012 ◽  
Vol 7 (4) ◽  
pp. 1934578X1200700 ◽  
Author(s):  
Akira Sakamoto ◽  
Nao Ohya ◽  
Toshio Hasegawa ◽  
Hiroaki Izumi ◽  
Nakako Tokita ◽  
...  

Determining the absolute stereochemistry of organic compounds in solution remains a challenge. We investigated the use of Raman optical activity (ROA) spectroscopy to address this problem. The absolute configurations of (+)-( R)- and (-)-( S)-limonene were determined by ROA spectroscopy, which can be applied to smaller amounts of sample as compared with vibrational circular dichroism (VCD) spectroscopy. This ROA method was also applied to (+)-( E)-α-santalol and shown to be successful in the determination of the absolute configuration of this compound. ROA spectroscopy shows promise as a useful tool for determining the absolute stereochemistry of many natural compounds.


2010 ◽  
Vol 08 (05) ◽  
pp. 867-884 ◽  
Author(s):  
YUZHONG ZHAO ◽  
BABAK ALIPANAHI ◽  
SHUAI CHENG LI ◽  
MING LI

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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