A through bond, C4â?²/H4â?² selective, â??out and stayâ?? type 4D HC(P)CH experiment is introduced which provides sequential connectivity via H4â?²(i)â??C4â?²(i)â??C4â?²(iâ??1)â??H4â?²(iâ??1) correlations. The 31P dimension (used in the conventional 3D HCP experiment) is replaced with evolution of better dispersed C4â?² dimension. The experiment fully utilizes 13C-labeling of RNA by inclusion of two C4â?² evolution periods. An additional evolution of H4â?² is included to further enhance peak resolution. Band selective 13C inversion pulses are used to achieve selectivity and prevent signal dephasing due to the of C4â?²â??C3â?² and C4â?²â??C5â?² homonuclear couplings. For reasonable resolution, non-uniform sampling is employed in all indirect dimensions. To reduce sensitivity losses, multiple quantum coherences are preserved during shared-time evolution and coherence transfer delays. In the experiment the intra-nucleotide peaks are suppressed whereas inter-nucleotide peaks are enhanced to reduce the ambiguities. The performance of the experiment is verified on a fully 13C, 15N-labeled 34-nt hairpin RNA comprising typical structure elements.
4D Non-uniformly sampled HCBCACON and 1J(NCα)-selective HCBCANCO experiments for the sequential assignment and chemical shift analysis of intrinsically disordered proteins
4D Non-uniformly sampled HCBCACON and 1J(NCα)-selective HCBCANCO experiments for the sequential assignment and chemical shift analysis of intrinsically disordered proteins
Abstract A pair of 4D NMR experiments for the backbone assignment of disordered proteins is presented. The experiments exploit 13C direct detection and non-uniform sampling of the indirectly detected dimensions, and provide correlations of the aliphatic proton (Hα, and Hβ) and carbon (Cα, Cβ) resonance frequencies to the protein backbone. Thus, all the chemical shifts regularly used to map the transient...
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05-17-2012 08:40 AM
Analysis of non-uniformly sampled spectra with multi-dimensional decomposition
Analysis of non-uniformly sampled spectra with multi-dimensional decomposition
Publication year: 2011
Source:Progress in Nuclear Magnetic Resonance Spectroscopy, Volume 59, Issue 3</br>
Vladislav Yu. Orekhov, Victor A. Jaravine</br>
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03-09-2012 09:16 AM
Multidimensional oriented solid-state NMR experiments enable the sequential assignment of uniformly 15N labeled integral membrane proteins in magnetically aligned lipid bilayers
Multidimensional oriented solid-state NMR experiments enable the sequential assignment of uniformly 15N labeled integral membrane proteins in magnetically aligned lipid bilayers
Abstract Oriented solid-state NMR is the most direct methodology to obtain the orientation of membrane proteins with respect to the lipid bilayer. The method consists of measuring 1H-15N dipolar couplings (DC) and 15N anisotropic chemical shifts (CSA) for membrane proteins that are uniformly aligned with respect to the membrane bilayer. A significant advantage of this approach is that tilt and azimuthal...
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10-10-2011 06:27 AM
Analysis of non-uniformly sampled spectra with Multi-Dimensional Decomposition
Analysis of non-uniformly sampled spectra with Multi-Dimensional Decomposition
Publication year: 2011
Source: Progress in Nuclear Magnetic Resonance Spectroscopy, In Press, Accepted Manuscript, Available online 24 February 2011</br>
Vladislav Yu., Orekhov , Victor A., Jaravine</br>
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02-26-2011 01:07 PM
FM reconstruction of non-uniformly sampled protein NMR data at higher dimensions and optimization by distillation
FM reconstruction of non-uniformly sampled protein NMR data at higher dimensions and optimization by distillation
Abstract Non-uniform sampling (NUS) enables recording of multidimensional NMR data at resolutions matching the resolving power of modern instruments without using excessive measuring time. However, in order to obtain satisfying results, efficient reconstruction methods are needed. Here we describe an optimized version of the Forward Maximum entropy (FM) reconstruction method, which can reconstruct up to three indirect dimensions. For complex datasets, such as NOESY spectra,...