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PHRONESIS: A One-Shot Approach for Sequential Assignment of Protein Resonances by Ultrafast MAS Solid-State NMR Spectroscopy. Chemphyschem 2022 Jul 05;23(13):e202200127

Date

05/03/2022

Pubmed ID

35499980

Pubmed Central ID

PMC9400877

DOI

10.1002/cphc.202200127

Scopus ID

2-s2.0-85130396254 (requires institutional sign-in at Scopus site)   4 Citations

Abstract

Solid-state NMR (ssNMR) spectroscopy has emerged as the method of choice to analyze the structural dynamics of fibrillar, membrane-bound, and crystalline proteins that are recalcitrant to other structural techniques. Recently, 1 H detection under fast magic angle spinning and multiple acquisition ssNMR techniques have propelled the structural analysis of complex biomacromolecules. However, data acquisition and resonance-specific assignments remain a bottleneck for this technique. Here, we present a comprehensive multi-acquisition experiment (PHRONESIS) that simultaneously generates up to ten 3D 1 H-detected ssNMR spectra. PHRONESIS utilizes broadband transfer and selective pulses to drive multiple independent polarization pathways. High selectivity excitation and de-excitation of specific resonances were achieved by high-fidelity selective pulses that were designed using a combination of an evolutionary algorithm and artificial intelligence. We demonstrated the power of this approach with microcrystalline U-13 C,15 N GB1 protein, reaching 100 % of the resonance assignments using one data set of ten 3D experiments. The strategy outlined in this work opens up new avenues for implementing novel 1 H-detected multi-acquisition ssNMR experiments to speed up and expand the application to larger biomolecular systems.

Author List

Gopinath T, Manu VS, Weber DK, Veglia G

Author

Gopinath Tata PhD Assistant Professor in the Biophysics department at Medical College of Wisconsin




MESH terms used to index this publication - Major topics in bold

Algorithms
Artificial Intelligence
Magnetic Resonance Spectroscopy
Nuclear Magnetic Resonance, Biomolecular
Proteins