Rapid Quantification of Protein Secondary Structure Composition from a Single Unassigned 1D 13C Nuclear Magnetic Resonance Spectrum

Abstract

The function of a protein is predicated upon its three-dimensional fold. Representing its complex structure as a series of repeating secondary structural elements is one of the most useful ways by which we study, characterize, and visualize a protein. Consequently, experimental methods that quantify the secondary structure content allow us to connect a protein's structure to its function. Here, we introduce an automated gradient descent-based method we refer to as secondary-structure distribution by NMR that allows for rapid quantification of the protein secondary structure composition of a protein from a single, 1D ¹³C NMR spectrum without chemical shift assignments. The analysis of nearly 900 proteins with known structure and chemical shifts demonstrates the capabilities of our approach. We show that these results rival alternative techniques such as FT-IR and circular dichroism that are commonly used to estimate secondary structure compositions. The resulting method requires only the primary sequence of the protein and its referenced ¹³C NMR spectrum. Each residue is modeled in an ensemble of secondary structures with percentage contributions from random coil, α-helix, and β-sheet secondary structures obtained by minimizing the difference between a simulated and experimental 1D ¹³C NMR spectrum. The capabilities of the method are demonstrated as applied to samples at natural abundance or enriched in ¹³C, acquired by either solution or solid-state NMR, and even on low magnetic field benchtop NMR spectrometers. This approach allows for rapid characterization of protein secondary structure across traditionally challenging to characterize states including liquid-liquid phase-separated, membrane-bound, or aggregated states.