Abstract A new computer program, called SHIFTX2, is described which is capable of rapidly and accurately calculating diamagnetic 1H, 13C and 15N chemical shifts from protein coordinate data. Compared to its predecessor (SHIFTX) and to other existing protein chemical shift prediction programs, SHIFTX2 is substantially more accurate (up to 26% better by correlation coefficient with an RMS error that is up to 3.3Ã? smaller) than the next best performing program. It also provides significantly more coverage (up to 10% more), is significantly faster (up to 8.5Ã?) and capable of calculating a wider variety of backbone and side chain chemical shifts (up to 6Ã?) than many other shift predictors. In particular, SHIFTX2 is able to attain correlation coefficients between experimentally observed and predicted backbone chemical shifts of 0.9800 (15N), 0.9959 (13Cα), 0.9992 (13Cβ), 0.9676 (13Câ?²), 0.9714 (1HN), 0.9744 (1Hα) and RMS errors of 1.1169, 0.4412, 0.5163, 0.5330, 0.1711, and 0.1231 ppm, respectively. The correlation between SHIFTX2â??s predicted and observed side chain chemical shifts is 0.9787 (13C) and 0.9482 (1H) with RMS errors of 0.9754 and 0.1723 ppm, respectively. SHIFTX2 is able to achieve such a high level of accuracy by using a large, high quality database of training proteins (>190), by utilizing advanced machine learning techniques, by incorporating many more features (Ï?2 and Ï?3 angles, solvent accessibility, H-bond geometry, pH, temperature), and by combining sequence-based with structure-based chemical shift prediction techniques. With this substantial improvement in accuracy we believe that SHIFTX2 will open the door to many long-anticipated applications of chemical shift prediction to protein structure determination, refinement and validation. SHIFTX2 is available both as a standalone program and as a web server (http://www.shiftx2.ca).
Content Type Journal Article
Pages 1-15
DOI 10.1007/s10858-011-9478-4
Authors
Beomsoo Han, Department of Computing Science, University of Alberta, Edmonton, AB, Canada
Yifeng Liu, Department of Computing Science, University of Alberta, Edmonton, AB, Canada
Simon W. Ginzinger, Department of Molecular Biology, Division of Bioinformatics, Center of Applied Molecular Engineering, University of Salzburg, Hellbrunnerstr. 34/3.OG, 5020 Salzburg, Austria
David S. Wishart, Department of Computing Science, University of Alberta, Edmonton, AB, Canada
Combining NMR ensembles and molecular dynamics simulations provides more realistic models of protein structures in solution and leads to better chemical shift prediction
Combining NMR ensembles and molecular dynamics simulations provides more realistic models of protein structures in solution and leads to better chemical shift prediction
Abstract While chemical shifts are invaluable for obtaining structural information from proteins, they also offer one of the rare ways to obtain information about protein dynamics. A necessary tool in transforming chemical shifts into structural and dynamic information is chemical shift prediction. In our previous work we developed a method for 4D prediction of protein 1H chemical shifts in which molecular motions, the...
nmrlearner
Journal club
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02-11-2012 10:31 AM
SHIFTX2: Chemical Shift Prediction
SHIFTX2 website
SHIFTX2 is capable of rapidly and accurately calculating diamagnetic 1H, 13C and 15N chemical shifts from protein coordinate data. Compared to its predecessor (SHIFTX) and to other existing protein chemical shift prediction programs, SHIFTX2 is substantially more accurate (up to 26% better by correlation coefficient with an RMS error that is up to 3.3× smaller) than the next best performing program. It also provides significantly more coverage (up to 10% more), is significantly faster (up to 8.5×) and capable of calculating a wider variety of backbone and side chain...
gwnmr
NMR software
0
01-10-2012 06:13 PM
Chemical shift prediction for protein structure calculation and quality assessment using an optimally parameterized force field
Chemical shift prediction for protein structure calculation and quality assessment using an optimally parameterized force field
Publication year: 2011
Source: Progress in Nuclear Magnetic Resonance Spectroscopy, In Press, Accepted Manuscript, Available online 23 May 2011</br>
Jakob T., Nielsen , Hamid R., Eghbalnia , Niels Chr., Nielsen</br>
The exquisite sensitivity of chemical shifts as reporters of structural information, and the ability to measure them routinely and accurately, gives great import to formulations that elucidate the structure-chemical-shift relationship. Here we...
nmrlearner
Journal club
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05-24-2011 10:02 PM
4D prediction of protein 1H chemical shifts
4D prediction of protein 1H chemical shifts
Abstract A 4D approach for protein 1H chemical shift prediction was explored. The 4th dimension is the molecular flexibility, mapped using molecular dynamics simulations. The chemical shifts were predicted with a principal component model based on atom coordinates from a database of 40 protein structures. When compared to the corresponding non-dynamic (3D) model, the 4th dimension improved prediction by 6â??7%. The prediction method achieved RMS errors of 0.29 and 0.50 ppm for Hα and HN shifts, respectively. However, for individual proteins...
nmrlearner
Journal club
0
01-09-2011 12:46 PM
Protein secondary structure prediction using NMR chemical shift data.
Protein secondary structure prediction using NMR chemical shift data.
Related Articles Protein secondary structure prediction using NMR chemical shift data.
J Bioinform Comput Biol. 2010 Oct;8(5):867-84
Authors: Zhao Y, Alipanahi B, Li SC, Li M
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)...
nmrlearner
Journal club
0
10-29-2010 07:05 PM
SPARTA+: a modest improvement in empirical NMR chemical shift prediction by means of
Abstract NMR chemical shifts provide important local structural information for proteins and are key in recently described protein structure generation protocols. We describe a new chemical shift prediction program, SPARTA+, which is based on artificial neural networking. The neural network is trained on a large carefully pruned database, containing 580 proteins for which high-resolution X-ray structures and nearly complete backbone and 13Cβ chemical shifts are available. The neural network is trained to establish quantitative relations between chemical shifts and protein structures,...
Chemical shift prediction in random coil peptides
Please check this program and let me know if it does work for your random coil peptides.
http://bloch.anu.edu.au/cgi-bin/shiftpred/shiftpred.cgi
Thank you,
Bogdan Bancia
bbancia@yahoo.com
SHIFTX2: significantly improved protein chemical shift prediction
Linear Mode
