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CheSPI: chemical shift secondary structure population inference

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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.

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taken from a 2D-color-scale (see Fig. S3) based on the position in Ramachandran plot of pairs of ϕ and Ψ backbone torsion angles using trigonometric averages of the ensemble values (see Eq. 16, Methods). With this scale, backbone angles in the helical domain of the Ramachandran map appear in red as before, and extended β-sheet-like conformations have blue colors. Furthermore, left-twisted β-strands as well as fragments with PPII structure appear with cyan colors, whereas conformations with positive ϕ have yellow and green colors, and finally, other conformation referred to elsewhere as “forbidden” in Ramachandran space are shown in black. Transparency is added to the bars using the above local angular order parameters as the “alpha value”. See also Figure S1

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Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. Python code for CheSPI is available for download at GitHub: https://github.com/protein-nmr.

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  1. Interdisciplinary Nanoscience Center (iNANO) and Department of Chemistry, Aarhus University, Gustav Wieds Vej 14, 8000, Aarhus C, Denmark

    Jakob Toudahl Nielsen & Frans A. A. Mulder

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  1. Jakob Toudahl Nielsen
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Nielsen, J.T., Mulder, F.A.A. CheSPI: chemical shift secondary structure population inference. J Biomol NMR 75, 273–291 (2021). https://doi.org/10.1007/s10858-021-00374-w

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