Journal of Biomolecular NMR最新文献

Structurally diverse ensembles of intrinsically disordered proteins or regions are difficult to determine, because experimental observables usually report a conformational average. Therefore, in order to infer the underlying distribution, a set of experiments that measure different aspects of the system is necessary. In principle, there exists a set of cross-correlated relaxation (CCR) rates that report on protein backbone geometry in a complementary way. However, CCR rates are hard to interpret, because geometric information is encoded in an ambiguous way and they present themselves as a convolute of both structure and dynamics. Despite these challenges, CCR rates analyzed within a suitable statistical framework are able to identify conformations in structured proteins. In the context of disordered proteins, we find that this approach has to be adjusted to account for local dynamics via including an additional CCR rate. The results of this study show that CCR rates can be used to characterize structure propensities also in disordered proteins. Instead of using an experimental reference structure, we employed computational spectroscopy to calculate CCR rates from molecular dynamics (MD) simulations and subsequently compared the results to conformations as observed directly in the MD trajectory.

Large proteins and dilute spin systems within a deuterated background are often characterized by long proton (¹H) spin-lattice relaxation times (T₁), which directly impacts the recycle delay and hence, the total experimental time. Dioxygen (O₂) is a well-known paramagnetic species whose short electronic spin-lattice relaxation time (7.5 ps) contributes to effective spin-lattice relaxation of high gamma nuclei. Oxygen’s chemical potential and high diffusivity also allows it to access both the protein exterior and much of the (hydrophobic) interior of the protein. Consequently, at O₂ partial pressures of ~ 10 bar, ¹H and ¹⁹F spin-lattice relaxation rates (R₁) typically reach 3–5 Hz (versus rates of 0.7-1.0 Hz without oxygen) with comparable line-broadening in protein NMR spectra. Using fluoroacetate dehalogenase (FAcD) a soluble 35 kDa homodimeric enzyme, a nanodisc-stabilized G protein-coupled receptor (A_2AR), and bovine serum albumin (BSA) as test cases, a 3-fold savings in time was achieved in acquiring ¹H-¹⁵ N HSQC and ¹⁹F NMR spectra, after oxygenation at 9 bar for 24 h. Additional spin-diffusion effects are anticipated to contribute to uniform ¹H spin-lattice relaxation for both solvent-exposed and buried protons, as demonstrated by T₁ relaxation analysis of amides in ¹⁵N-labeled FAcD. Finally, we show that in protein samples dissolved oxygen pre-equilibrated at 9 bar (pO₂) is largely retained in solution at 20° C or lower, using a standard NMR tube for a period of 3–4 days, thus avoiding the use of specialized apparatus or high-pressure NMR tubes in the spectrometer. The convenience of being able to add or remove the quenching species, while avoiding any complex apparatus in the NMR experiment, makes this a practical tool for both ¹⁹F, ¹H-¹³ C, and ¹H-¹⁵ N NMR studies of proteins.

The NMR signals from protein sidechains are rich in information about intra- and inter-molecular interactions, but their detection can be complicated due to spectral overlap as well as conformational and hydrogen exchange. In this work, we demonstrate a protocol for multi-dimensional solid-state NMR spectral editing of signals from basic sidechains based on Hadamard matrix encoding. The Hadamard method acquires multi-dimensional experiments in such a way that both the backbone and under-sampled sidechain signals can be decoded for unambiguous editing in the ¹⁵N spectral frequency dimension. All multi-dimensional ¹⁵N-edited solid-state NMR experiments can be acquired using this strategy, thereby accelerating the acquisition of spectra spanning broad frequency bandwidth. Application of these methods to the ferritin nanocage, reveals signals from N atoms from His, Arg, Lys and Trp sidechains, as well as their tightly bound, ordered water molecules. The Hadamard approach adds to the arsenal of spectroscopic approaches for protein NMR signal detection.

Intrinsically disordered proteins and protein regions are central to many biological processes but difficult to characterize at atomic resolution. Nuclear magnetic resonance is particularly well-suited for providing structural and dynamical information on intrinsically disordered proteins, but existing NMR methodologies need to be constantly refined to provide greater sensitivity and resolution, particularly to capitalise on the potential of high magnetic fields to investigate large proteins. In this paper, we describe how ¹⁵N-detected 2D NMR experiments can be optimised for better performance. We show that using selective aliphatic ¹H decoupling in N-TROSY type experiments results in significant increases in sensitivity and resolution for a prototypical intrinsically disordered protein, α-synuclein, as well as for a heterogeneous intrinsically disordered region of a large multidomain protein, CBP-ID4. We also investigated the performance of incorporating longitudinal relaxation enhancement in N-TROSY experiments, both with and without aliphatic ¹H decoupling, and discussed the findings in light of the available information for the two systems.

Chemical shift assignments of large membrane proteins by solid-state NMR experiments are challenging. Recent advancements in sensitivity-enhanced pulse sequences, have made it feasible to acquire ¹H-detected 4D spectra of these challenging protein samples within reasonable timeframes. However, obtaining unambiguous assignments remains difficult without access to side-chain chemical shifts. Drawing inspiration from sensitivity-enhanced TOCSY experiments in solution NMR, we have explored the potential of ¹³C- ¹³C TOCSY mixing as a viable option for triple sensitivity-enhanced 4D experiments aimed at side-chain assignments in solid-state NMR. Through simulations and experimental trials, we have identified optimal conditions to achieve uniform transfer efficiency for both transverse components and to minimize undesired cross-transfers. Our experiments, conducted on the 30 kDa membrane protein GlpG embedded in E. coli liposomes, have demonstrated enhanced sensitivity compared to the most effective dipolar and J-coupling-based ¹³C- ¹³C mixing sequences. Notably, a non-uniformly sampled 4D hCXCANH spectrum with exceptionally high sensitivity was obtained in just a few days using a 600 MHz spectrometer equipped with a 1.3 mm probe operating at a magic angle spinning rate of 55 kHz.

Inclusion of residual dipolar couplings (RDCs) during the early rounds of protein structure determination requires use of a floating alignment tensor or knowledge of the alignment tensor strength and rhombicity. For proteins with interdomain motion, such analysis can falsely hide the presence of domain dynamics. We demonstrate for three proteins, maltotriose-ligated maltose binding protein (MBP), Ca²⁺-ligated calmodulin, and a monomeric N-terminal deletion mutant of the SARS-CoV-2 Main Protease, MPro, that good alignment tensor estimates of their domains can be obtained from RDCs measured for residues that are identified as α-helical based on their chemical shifts. The program, Helix-Fit, fits the RDCs to idealized α-helical coordinates, often yielding a comparable or better alignment tensor estimate than fitting to the actual high-resolution X-ray helix coordinates. The 13 helices of ligated MBP all show very similar alignment tensors, indicative of a high degree of order relative to one another. By contrast, while for monomeric MPro the alignment strengths of the five helices in the C-terminal helical domain (residues 200–306) are very similar, pointing to a well-ordered domain, the single α-helix Y54-I59 in the N-terminal catalytic domain (residues 10–185) aligns considerably weaker. This result indicates the presence of large amplitude motions of either Y54-I59 or of the entire N-terminal domain relative to the C-terminal domain, contrasting with the high degree of order seen in the native homodimeric structure.

The resonance assignment of large intrinsically disordered proteins (IDPs) is difficult due to the low dispersion of chemical shifts (CSs). Luckily, CSs are often specific for certain residue types, which makes the task easier. Our recent work showed that the CS-based spin-system classification can be improved by applying a linear discriminant analysis (LDA). In this paper, we extend a set of classification parameters by adding temperature coefficients (TCs), i.e., rates of change of chemical shifts with temperature. As demonstrated previously by other groups, the TCs in IDPs depend on a residue type, although the relation is often too complex to be predicted theoretically. Thus, we propose an approach based on experimental data; CSs and TCs values of residues assigned using conventional methods serve as a training set for LDA, which then classifies the remaining resonances. The method is demonstrated on a large fragment (1-239) of highly disordered protein Tau. We noticed that adding TCs to sets of chemical shifts significantly improves the recognition efficiency. For example, it allows distinguishing between lysine and glutamic acid, as well as valine and isoleucine residues based on ({{text {H}}^{text {N}}}), N, ({{text {C}}_alpha }) and C(^{prime }) data. Moreover, adding TCs to CSs of ({{text {H}}^{text {N}}}), N, ({{text {C}}_alpha }), and C(^{prime }) is more beneficial than adding ({{text {C}}_beta }) CSs. Our program for LDA analysis is available at https://github.com/gugumatz/LDA-Temp-Coeff.

Artificial intelligence (AI) models are revolutionising scientific data analysis but are reliant on large training data sets. While artificial training data can be used in the context of NMR processing and data analysis methods, relating NMR parameters back to protein sequence and structure requires experimental data. In this perspective we examine what the biological NMR community needs to do, in order to store and share its data better so that we can make effective use of AI methods to further our understanding of biological molecules. We argue, first, that the community should be depositing much more of its experimental data. In particular, we should be depositing more spectra and dynamics data. Second, the NMR data deposited needs to capture the full information content required to be able to use and validate it adequately. The NMR Exchange Format (NEF) was designed several years ago to do this. The widespread adoption of NEF combined with a new proposal for dynamics data specifications come at the right time for the community to expand its deposition of data. Third, we highlight the importance of expanding and safeguarding our experimental data repository, the Biological Magnetic Resonance Data Bank (BMRB), not only in the interests of NMR spectroscopists, but biological scientists more widely. With this article we invite others in the biological NMR community to champion increased (possibly mandatory) data deposition, to get involved in designing new NEF specifications, and to advocate on behalf of the BMRB within the wider scientific community.

The recent application of ¹⁹F NMR in the study of biomolecular structure and dynamics has made it a potentially attractive probe to complement traditional ¹⁵N/¹³C labelled probes for backbone and sidechain dynamics, albeit with some complications. The utility of ¹⁵N relaxation rates of rigid backbone amide groups to determine the rotational diffusion tensor of proteins is well established. Here we show that the measured ¹⁹F relaxation rates of two buried and possibly immobile ¹⁹F labelled tryptophan sidechains for the multidomain protein RfaH, in its closed conformation, are in reasonable agreement with the calculated values, only when anisotropic rotational diffusion of the protein is considered. While the sparsity of ¹⁹F relaxation data from a limited number of probes precludes the experimental determination of the rotational diffusion tensor here, these results demonstrate the influence of rotational diffusion anisotropy of proteins on ¹⁹F NMR relaxation of rigid tryptophan sidechains, while adding to the expanding literature of ¹⁹F NMR relaxation data sets in biomolecules.

The dynamics of the backbone and side-chains of protein are routinely studied by interpreting experimentally determined ¹⁵N spin relaxation rates. R₁(¹⁵N), the longitudinal relaxation rate, reports on fast motions and encodes, together with the transverse relaxation R₂, structural information about the shape of the molecule and the orientation of the amide bond vectors in the internal diffusion frame. Determining error-free ¹⁵N longitudinal relaxation rates remains a challenge for small, disordered, and medium-sized proteins. Here, we show that mono-exponential fitting is sufficient, with no statistical preference for bi-exponential fitting up to 800 MHz. A detailed comparison of the TROSY and HSQC techniques at medium and high fields showed no statistically significant differences. The least error-prone DD/CSA interference removal technique is the selective inversion of amide signals while avoiding water resonance. The exchange of amide with solvent deuterons appears to affect the rate R₁ of solvent-exposed amides in all fields tested and in each DD/CSA interference removal technique in a statistically significant manner. In summary, the most accurate R₁(¹⁵N) rates in proteins are achieved by selective amide inversion, without the addition of D₂O. Importantly, at high magnetic fields stronger than 800 MHz, when non-mono-exponential decay is involved, it is advisable to consider elimination of the shortest delays (typically up to 0.32 s) or bi-exponential fitting.