CheSPI: chemical shift secondary structure population inference

Jakob Toudahl Nielsen*, Frans A.A. Mulder*

*Corresponding author for this work

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Abstract

NMR chemical shifts (CSs) are delicate reporters of local protein structure, and recent advances in random coil CS (RCCS) prediction and interpretation now offer the compelling prospect of inferring small populations of structure from small deviations from RCCSs. Here, we present CheSPI, a simple and efficient method that provides unbiased and sensitive aggregate measures of local structure and disorder. It is demonstrated that CheSPI can predict even very small amounts of residual structure and robustly delineate subtle differences into four structural classes for intrinsically disordered proteins. For structured regions and proteins, CheSPI provides predictions for up to eight structural classes, which coincide with the well-known DSSP classification. The program is freely available, and can either be invoked from URL www.protein-nmr.org as a web implementation, or run locally from command line as a python program. CheSPI generates comprehensive numeric and graphical output for intuitive annotation and visualization of protein structures. A number of examples are provided.

Original languageEnglish
JournalJournal of Biomolecular NMR
Volume75
Issue6-7
Pages (from-to)273-291
Number of pages19
ISSN0925-2738
DOIs
Publication statusPublished - Jul 2021

Keywords

  • Chemical shifts
  • Disorder
  • NMR
  • Order
  • Protein
  • RESIDUAL DIPOLAR COUPLINGS
  • TAU FILAMENTS
  • ACCURATE CALCULATION
  • ALPHA-SYNUCLEIN
  • INTRINSICALLY DISORDERED PROTEINS
  • IN-VITRO
  • PAIRED HELICAL FILAMENTS
  • SUPEROXIDE-DISMUTASE
  • ENERGY LANDSCAPE

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