SHIFTX2: Significantly improved protein chemical shift prediction

  1. Get@NRC: SHIFTX2: Significantly improved protein chemical shift prediction (Opens in a new window)
DOIResolve DOI:
AuthorSearch for: ; Search for: ; Search for: ; Search for:
Journal titleJournal of Biomolecular NMR
Pages4357; # of pages: 15
Subjectcarbon 13; nitrogen 15; protein; proton; accuracy; article; computer program; correlation coefficient; machine learning; prediction; priority journal; protein structure; proton nuclear magnetic resonance; Carbon Isotopes; Hydrogen Bonding; Nitrogen Isotopes; Nuclear Magnetic Resonance, Biomolecular; Protein Conformation; Proteins; Protons; Software
AbstractA 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 3.3× 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 chemical shifts (up to 6×) 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 ( 13C′), 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 SHIFTX2'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 (x2 and x3 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 ( © The Author(s) 2011. This article is published with open access at
Publication date
AffiliationNational Research Council Canada (NRC-CNRC); National Institute for Nanotechnology (NINT-INNT)
Peer reviewedYes
NPARC number21271131
Export citationExport as RIS
Report a correctionReport a correction
Record identifiereb72147a-ef02-4e95-9af9-c8b79b8fa8bf
Record created2014-03-24
Record modified2016-05-09
Bookmark and share
  • Share this page with Facebook (Opens in a new window)
  • Share this page with Twitter (Opens in a new window)
  • Share this page with Google+ (Opens in a new window)
  • Share this page with Delicious (Opens in a new window)
Date modified: