Protein Secondary Structure Changes of Watermelon Juice Treated with High Hydrostatic Pressure by FTIR Spectroscopy

2014 ◽  
Vol 37 (6) ◽  
pp. 543-549 ◽  
Author(s):  
Qing Liu ◽  
Ru-Fu Wang ◽  
Bo-Bo Zhang ◽  
Xiao-Yan Zhao ◽  
Dan Wang ◽  
...  
Biomolecules ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 359 ◽  
Author(s):  
Usoltsev ◽  
Sitnikova ◽  
Kajava ◽  
Uspenskaya

Human serum albumin (HSA) is the most abundant protein in blood plasma. HSA is involved in the transport of hormones, fatty acids, and some other compounds, maintenance of blood pH, osmotic pressure, and many other functions. Although this protein is well studied, data about its conformational changes upon different denaturation factors are fragmentary and sometimes contradictory. This is especially true for FTIR spectroscopy data interpretation. Here, the effect of various denaturing agents on the structural state of HSA by using FTIR spectroscopy in the aqueous solutions was systematically studied. Our data suggest that the second derivative deconvolution method provides the most consistent interpretation of the obtained IR spectra. The secondary structure changes of HSA were studied depending on the concentration of the denaturing agent during acid, alkaline, and thermal denaturation. In general, the denaturation of HSA in different conditions is accompanied by a decrease in α-helical conformation and an increase in random coil conformation and the intermolecular β-strands. Meantime, some variation in the conformational changes depending on the type of the denaturation agent were also observed. The increase of β-structural conformation suggests that HSA may form amyloid-like aggregates upon the denaturation.


2013 ◽  
Vol 130 (1) ◽  
pp. 359-369 ◽  
Author(s):  
James Michael Bier ◽  
Casparus Johannes Reinhard Verbeek ◽  
Mark Christopher Lay

2015 ◽  
Vol 35 (2) ◽  
pp. 189-202 ◽  
Author(s):  
Nasir Mehmood Khan ◽  
Tai-Hua Mu ◽  
Hong-Nan Sun ◽  
Miao Zhang ◽  
Jing-Wang Chen

2021 ◽  
pp. 1-7
Author(s):  
P.I. Haris ◽  
J.A. Hering

Besides NMR and X-ray crystallography, FTIR and CD spectroscopy are widely considered to be useful for determining protein secondary structure. These techniques can be used to obtain data in few minutes, using small quantities of proteins, which make them amenable for proteomics research. Here we explore the possibility of using artificial intelligence techniques to simultaneously analyse both FTIR and CD spectroscopic data for an identical set of proteins. Neural network analysis was carried out on normalised regions of FTIR (1700-1600 cm−1) and CD (180-259 nm) spectral data both with and without boxcar averaging in order to quantify the average length and percentages of secondary structures. A hybrid genetic algorithm/neural network approach, that automatically selects structure-sensitive wavelength/frequency, was used for the quantification of the protein secondary structure. Using this algorithm we also successfully identified the region of the CD spectrum that contains the most structure-sensitive information. This was located between 214-251 nm, suggesting that this region alone may be sufficient to rapidly determine the secondary structure content from CD spectral data. Overall, CD spectroscopic analysis produced better results compared to FTIR spectroscopy when selected wavelengths were used, although FTIR was better when the entire region between 1700-1600 cm−1 (FTIR), and 180-259 nm (CD), was subjected to neural network analysis. Application of Adaptive Neuro-Fuzzy Inference System (ANFIS) with fuzzy subtractive clustering for the analysis of the spectral data led to a slightly better prediction of the average helix/sheet length for FTIR spectroscopy compared to CD. Our findings reveal the potential of using artificial intelligence techniques for not only extracting structural information but also for better understanding of the relationship between complex spectral data and biologically important information.


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