A Simple Method To Predict Protein Flexibility Using Secondary Chemical Shifts

2005 ◽  
Vol 127 (43) ◽  
pp. 14970-14971 ◽  
Author(s):  
Mark V. Berjanskii ◽  
David S. Wishart
Keyword(s):  
Chemical Shifts ◽  
Protein Flexibility ◽  
Simple Method ◽  
Secondary Chemical Shifts ◽  
Secondary Chemical

scholarly journals Bayesian-Maximum-Entropy reweighting of IDP ensembles based on NMR chemical shifts

2019 ◽  
Author(s):  
Ramon Crehuet ◽  
Pedro J. Buigues ◽  
Xavier Salvatella ◽  
Kresten Lindorff-Larsen
Keyword(s):  
Chemical Shift ◽  
Maximum Entropy ◽  
Chemical Shifts ◽  
Intrinsically Disordered Protein ◽  
Intrinsically Disordered ◽  
Computational Data ◽  
Chemical Shift Data ◽  
Secondary Chemical Shifts ◽  
Validation Set ◽  
Secondary Chemical

AbstractBayesian and Maximum Entropy approaches allow for a statistically sound and systematic fitting of experimental and computational data. Unfortunately, assessing the relative confidence in these two types of data remains difficult as several steps add unknown error. Here we propose the use of a validation-set method to determine the balance, and thus the amount of fitting. We apply the method to synthetic NMR chemical shift data of an intrinsically disordered protein. We show that the method gives consistent results even when other methods to assess the amount of fitting cannot be applied. Finally, we also describe how the errors in the chemical shift predictor can lead to an incorrect fitting and how using secondary chemical shifts could alleviate this problem.

scholarly journals Bayesian-Maximum-Entropy Reweighting of IDP Ensembles Based on NMR Chemical Shifts

Entropy ◽  
2019 ◽  
Vol 21 (9) ◽  
pp. 898 ◽  
Author(s):  
Ramon Crehuet ◽  
Pedro J. Buigues ◽  
Xavier Salvatella ◽  
Kresten Lindorff-Larsen
Keyword(s):  
Chemical Shift ◽  
Maximum Entropy ◽  
Chemical Shifts ◽  
Intrinsically Disordered Protein ◽  
Intrinsically Disordered ◽  
Computational Data ◽  
Chemical Shift Data ◽  
Secondary Chemical Shifts ◽  
Validation Set ◽  
Secondary Chemical

Bayesian and Maximum Entropy approaches allow for a statistically sound and systematic fitting of experimental and computational data. Unfortunately, assessing the relative confidence in these two types of data remains difficult as several steps add unknown error. Here we propose the use of a validation-set method to determine the balance, and thus the amount of fitting. We apply the method to synthetic NMR chemical shift data of an intrinsically disordered protein. We show that the method gives consistent results even when other methods to assess the amount of fitting cannot be applied. Finally, we also describe how the errors in the chemical shift predictor can lead to an incorrect fitting and how using secondary chemical shifts could alleviate this problem.

Structural information from NMR secondary chemical shifts of peptide α C-H protons in proteins

1983 ◽  
Vol 3 (5) ◽  
pp. 443-452 ◽  
Author(s):  
D. C. Dalgarno ◽  
B. A. Levine ◽  
R. J. P. Williams
Keyword(s):  
Calcium Binding ◽  
Structural Information ◽  
Chemical Shifts ◽  
Troponin C ◽  
Secondary Chemical Shift ◽  
Secondary Chemical Shifts ◽  
Α Helix ◽  
Torsional Angles ◽  
Secondary Chemical ◽  
Β Sheet

The secondary chemical shift experienced by the 1H-NMR resonances of the α C-H protons in proteins can be correlated with their backbone torsional angles ψ, which dictate the orientation of the α C-H proton to the adjacent carbonyl group. It is shown that α C-H protons present in β-sheet regions experience downfield secondary shifts, whereas those in α-helix regions experience upfield secondary shifts. The predictive use of this correlation in assignment studies is illustrated for the calcium-binding protein paravalbumin, for which a crystal structure is available, and troponin C, for which no crystallographic data are available.

scholarly journals Random coil chemical shifts for serine, threonine and tyrosine phosphorylation over a broad pH range

2019 ◽  
Vol 73 (12) ◽  
pp. 713-725 ◽  
Author(s):  
Ruth Hendus-Altenburger ◽  
Catarina B. Fernandes ◽  
Katrine Bugge ◽  
Micha B. A. Kunze ◽  
Wouter Boomsma ◽  
...  
Keyword(s):  
Chemical Shift ◽  
Secondary Structure ◽  
Intrinsically Disordered Proteins ◽  
Chemical Shifts ◽  
Random Coil ◽  
Disordered Proteins ◽  
Phosphoryl Group ◽  
Intrinsically Disordered ◽  
Intrinsically Disordered Regions ◽  
Secondary Chemical

Abstract Phosphorylation is one of the main regulators of cellular signaling typically occurring in flexible parts of folded proteins and in intrinsically disordered regions. It can have distinct effects on the chemical environment as well as on the structural properties near the modification site. Secondary chemical shift analysis is the main NMR method for detection of transiently formed secondary structure in intrinsically disordered proteins (IDPs) and the reliability of the analysis depends on an appropriate choice of random coil model. Random coil chemical shifts and sequence correction factors were previously determined for an Ac-QQXQQ-NH2-peptide series with X being any of the 20 common amino acids. However, a matching dataset on the phosphorylated states has so far only been incompletely determined or determined only at a single pH value. Here we extend the database by the addition of the random coil chemical shifts of the phosphorylated states of serine, threonine and tyrosine measured over a range of pH values covering the pKas of the phosphates and at several temperatures (www.bio.ku.dk/sbinlab/randomcoil). The combined results allow for accurate random coil chemical shift determination of phosphorylated regions at any pH and temperature, minimizing systematic biases of the secondary chemical shifts. Comparison of chemical shifts using random coil sets with and without inclusion of the phosphoryl group, revealed under/over estimations of helicity of up to 33%. The expanded set of random coil values will improve the reliability in detection and quantification of transient secondary structure in phosphorylation-modified IDPs.

A simple method to determine the water content in organic solvents using the 1 H NMR chemical shifts differences between water and solvent

2018 ◽  
Vol 138 ◽  
pp. 395-400 ◽  
Author(s):  
Eungyu Kang ◽  
Hae Ri Park ◽  
Jeongbin Yoon ◽  
Hyo-Yeon Yu ◽  
Suk-Kyu Chang ◽  
...  
Keyword(s):  
Water Content ◽  
Organic Solvents ◽  
Chemical Shifts ◽  
Simple Method ◽  
Nmr Chemical Shifts ◽  
H Nmr

scholarly journals The RCI server: rapid and accurate calculation of protein flexibility using chemical shifts

2007 ◽  
Vol 35 (Web Server) ◽  
pp. W531-W537 ◽  
Author(s):  
M. V. Berjanskii ◽  
D. S. Wishart
Keyword(s):  
Chemical Shifts ◽  
Protein Flexibility ◽  
Accurate Calculation

A simple way for producing holographic filters suitable for image improvement

1978 ◽  
Vol 36 (1) ◽  
pp. 226-227
Author(s):  
K.-H. Herrmann ◽  
E. Reuber ◽  
P. Schiske
Keyword(s):  
Transfer Functions ◽  
Diffraction Order ◽  
Lateral Position ◽  
Simple Method ◽  
Spatial Frequencies ◽  
Resolution Electron ◽  
Wiener Filters ◽  
Image Improvement ◽  
Optical Reconstruction ◽  
Set Up

Aposteriori deblurring of high resolution electron micrographs of weak phase objects can be performed by holographic filters [1,2] which are arranged in the Fourier domain of a light-optical reconstruction set-up. According to the diffraction efficiency and the lateral position of the grating structure, the filters permit adjustment of the amplitudes and phases of the spatial frequencies in the image which is obtained in the first diffraction order.In the case of bright field imaging with axial illumination, the Contrast Transfer Functions (CTF) are oscillating, but real. For different imageforming conditions and several signal-to-noise ratios an extensive set of Wiener-filters should be available. A simple method of producing such filters by only photographic and mechanical means will be described here.A transparent master grating with 6.25 lines/mm and 160 mm diameter was produced by a high precision computer plotter. It is photographed through a rotating mask, plotted by a standard plotter.

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