Journal of Biomolecular NMR

, Volume 70, Issue 3, pp 141–165 | Cite as

POTENCI: prediction of temperature, neighbor and pH-corrected chemical shifts for intrinsically disordered proteins

  • Jakob Toudahl Nielsen
  • Frans A. A. Mulder


Chemical shifts contain important site-specific information on the structure and dynamics of proteins. Deviations from statistical average values, known as random coil chemical shifts (RCCSs), are extensively used to infer these relationships. Unfortunately, the use of imprecise reference RCCSs leads to biased inference and obstructs the detection of subtle structural features. Here we present a new method, POTENCI, for the prediction of RCCSs that outperforms the currently most authoritative methods. POTENCI is parametrized using a large curated database of chemical shifts for protein segments with validated disorder; It takes pH and temperature explicitly into account, and includes sequence-dependent nearest and next-nearest neighbor corrections as well as second-order corrections. RCCS predictions with POTENCI show root-mean-square values that are lower by 25–78%, with the largest improvements observed for 1Hα and 13C′. It is demonstrated how POTENCI can be applied to analyze subtle deviations from RCCSs to detect small populations of residual structure in intrinsically disorder proteins that were not discernible before. POTENCI source code is available for download, or can be deployed from the URL


Chemical shift Software Intrinsically disordered proteins Random coil 

Supplementary material

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Supplementary material 1 (DOCX 1721 KB)


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© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Interdisciplinary Nanoscience Center (iNANO)Aarhus UniversityAarhus CDenmark
  2. 2.Department of ChemistryAarhus UniversityAarhus CDenmark

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