Practical use of chemical shift databases for protein solid-state NMR: 2D chemical shift maps and amino-acid assignment with secondary-structure information.

We introduce a Python-based program that utilizes the large database of (13)C and (15)N chemical shifts in the Biological Magnetic Resonance Bank to rapidly predict the amino acid type and secondary structure from correlated chemical shifts. The program, called PACSYlite Unified Query (PLUQ), is designed to help assign peaks obtained from 2D (13)C-(13)C, (15)N-(13)C, or 3D (15)N-(13)C-(13)C magic-angle-spinning correlation spectra. We show secondary-structure specific 2D (13)C-(13)C correlation maps of all twenty amino acids, constructed from a chemical shift database of 262,209 residues. The maps reveal interesting conformation-dependent chemical shift distributions and facilitate searching of correlation peaks during amino-acid type assignment. Based on these correlations, PLUQ outputs the most likely amino acid types and the associated secondary structures from inputs of experimental chemical shifts. We test the assignment accuracy using four high-quality protein structures. Based on only the Cα and Cß chemical shifts, the highest-ranked PLUQ assignments were 40-60 % correct in both the amino-acid type and the secondary structure. For three input chemical shifts (CO-Cα-Cß or N-Cα-Cß), the first-ranked assignments were correct for 60 % of the residues, while within the top three predictions, the correct assignments were found for 80 % of the residues. PLUQ and the chemical shift maps are expected to be useful at the first stage of sequential assignment, for combination with automated sequential assignment programs, and for highly disordered proteins for which secondary structure analysis is the main goal of structure determination.

Spectral editing of two-dimensional magic-angle-spinning solid-state NMR spectra for protein resonance assignment and structure determination.

Several techniques for spectral editing of 2D (13)C-(13)C correlation NMR of proteins are introduced. They greatly reduce the spectral overlap for five common amino acid types, thus simplifying spectral assignment and conformational analysis. The carboxyl (COO) signals of glutamate and aspartate are selected by suppressing the overlapping amide N-CO peaks through (13)C-(15)N dipolar dephasing. The sidechain methine (CH) signals of valine, lecuine, and isoleucine are separated from the overlapping methylene (CH(2)) signals of long-chain amino acids using a multiple-quantum dipolar transfer technique. Both the COO and CH selection methods take advantage of improved dipolar dephasing by asymmetric rotational-echo double resonance (REDOR), where every other π-pulse is shifted from the center of a rotor period t(r) by about 0.15 t(r). This asymmetry produces a deeper minimum in the REDOR dephasing curve and enables complete suppression of the undesired signals of immobile segments. Residual signals of mobile sidechains are positively identified by dynamics editing using recoupled (13)C-(1)H dipolar dephasing. In all three experiments, the signals of carbons within a three-bond distance from the selected carbons are detected in the second spectral dimension via (13)C spin exchange. The efficiencies of these spectral editing techniques range from 60 % for the COO and dynamic selection experiments to 25 % for the CH selection experiment, and are demonstrated on well-characterized model proteins GB1 and ubiquitin.