# Fast Ultra-Selective 1H-15N 1D NMR Spectroscopy Unlocks Atom-Resolved Dynamics of Low-Complexity Protein Regions

Wiktor Adamski, Geraldine R Levy, François-Xavier Cantrelle, Davy Sinnaeve

► To cite this version:

Wiktor Adamski, Geraldine R Levy, François-Xavier Cantrelle, Davy Sinnaeve. Fast Ultra-Selective 1H-15N 1D NMR Spectroscopy Unlocks Atom-Resolved Dynamics of Low-Complexity Protein Regions. Angewandte Chemie International Edition, 2026, pp.e19206. 10.1002/anie.202519206. hal-05534270

HAL Id: hal-05534270

https://cnrs.hal.science/hal-05534270v1

Submitted on 3 Mar 2026

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons CC BY 4.0 - Attribution - International License
<figure><img src="image_2.png" /></figure>

COMMUNICATION

OPEN ACCESS

# Fast Ultra-Selective ¹H-¹⁵N 1D NMR Spectroscopy Unlocks Atom-Resolved Dynamics of Low-Complexity Protein Regions

Wiktor Adamski ID |

Geraldine R. Levy ID |

François-Xavier Cantrelle ID |

Davy Sinnaeve ID |

CNRS, Univ. Lille, Institut Pasteur de Lille, UMR 9031 – Integrative Structural Biology, Lille, France

**Correspondence:** Wiktor Adamski (wiktor.adamski1992@gmail.com) | Davy Sinnaeve (davy.sinnaeve@univ-lille.fr)

**Received:** 1 September 2025 | **Revised:** 1 February 2026 | **Accepted:** 6 February 2026

**Keywords:** ¹⁵N spin-relaxation | huntingtin | NMR spectroscopy | protein dynamics | selective experiments

## ABSTRACT

Insight into the conformational dynamics of proteins is essential toward understanding their function at a molecular level. The motions experienced by individual atoms in the protein can be precisely quantified through NMR relaxation rates, but their measurement requires well-resolved spectral responses. Two-dimensional ¹H-¹⁵N correlation spectra are the standard approach to resolve amide signals in protein NMR, but come with an excessive cost in experimental time when spectra are heavily congested due to limited ¹⁵N chemical shift dispersions. This limitation often thwarts the characterization of dynamics for intrinsically disordered proteins, especially when they feature low-complexity or homopolymer regions, or short sample life-times. Here, we introduce a fast, ultra-selective ¹H-¹⁵N 1D NMR method that allows high-quality measurement of individual ¹⁵N spin-relaxation constants, even when ¹⁵N resonances are merely 6–8 Hz apart. We demonstrate the new experiment by characterizing, for the first time, pico- to nanosecond dynamics along a 16-residue polyglutamine stretch within the protein huntingtin, the causal agent of Huntington’s disease, as well as millisecond conformational exchange in the SH3GL3 protein. The new experiment will find wide application in the study of conformational dynamics of intrinsically disordered proteins or any other biomacromolecule that features highly dense ¹H-¹⁵N 2D spectra.

Conformational dynamics are key for protein function. To quantify the conformational motions sensed by individual nuclei, NMR relaxation rates are a primary information source [1–3]. For this, it is essential that NMR spectral responses are fully resolved, which is usually achieved with multidimensional heteronuclear experiments. Unfortunately, multidimensional acquisition comes at the price of increased minimal experimental time. The smaller the chemical shift differences in the indirect dimension, the more time-consuming the experiment becomes. The time-cost is exacerbated for relaxation measurements, as these necessitate recording 2D experiments about ten times with variable delays, radio-frequency (rf) amplitudes or magnetic field strength [1, 2]. When spectra are congested and chemical shift differences

are very small — rampant for intrinsically disordered proteins (IDPs) with low sequence-complexity — complete high-quality quantification of conformational dynamics would require an excessive experimental time.

Characterization of dynamics across the whole IDP sequence is rarely essential. Often, just a subset of amino acid residues is of functional interest, such as those found near sites for intermolecular interaction or post-translational modifications [4], or when they need to be monitored under variable experimental conditions such as temperature or the presence of interacting partners [5, 6]. A significant time-gain can thus be achieved using selective experiments that yield one ¹H-¹⁵N correlation

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly
cited.

© 2026 The Author(s). *Angewandte Chemie International Edition* published by Wiley-VCH GmbH
<figure><img src="image_3.png" /><figcaption>**FIGURE 1** | (a) Amino acid sequence of htt exon-1 polyQ-16 and a standard ¹H-¹⁵N 2D HSQC (900 MHz, 340 µM, pH 6.8, 283 K) (grey), overlayed with several 2D SNIPERs targeting individual glutamine correlations from the polyQ (blue) or the proline-rich region (red). (b) F₁-cross-sections taken from the 2D SNIPER spectra (full line) and the standard 2D HSQC (dashed line) for a number of glutamines. (c) 1D SNIPER spectra (full line) and F₂-cross-sections from the standard 2D HSQC (dashed line) for a number of glutamines. The Supporting Information contains more examples. [Correction added on February 25, 2026, after first online publication: Figure 1 has been updated.]</figcaption></figure>

at a time, allowing the use of fast 1D experiments instead of multidimensional acquisition. This also allows a residue-specific optimization of the experimental setup, such as the number of scans, or the sampling of relaxation-weighting delays or of *rf*-filed strengths [5, 6]. This is especially true for experiments measuring conformational exchange using weak *rf*-fields such as off-resonance $R_{1ρ}$ relaxation dispersion and Chemical Exchange Saturation Transfer (CEST) [6–9], where the ¹⁵N irradiation frequencies must be tailored for each residue, making broadband 2D acquisition very time-inefficient. Selective methods for such experiments have been proposed for folded proteins with well-

dispersed spectra [6, 7], but do not achieve sufficient selectivity to be applicable to heavily overlapped regions as often encountered in IDPs. Here, we propose a new experiment that achieves a selectivity approaching the ¹⁵N natural line width while retaining good sensitivity, making even extremely dense spectral regions accessible.

The exon-1 fragment of the protein huntingtin (htt) presents a clear illustration of the spectral crowding encountered in IDPs. It features a 16-residue polyglutamine (polyQ) homorepeat, the abnormal expansion of which triggers Huntington's disease [10].
<figure><img src="image_4.png" /><figcaption>FIGURE 2 | $^{15}$N R₁, R₂ rates and {¹H}-¹⁵N nOes (with 95% uncertainties) extracted from htt exon-1 glutamines using 1D SNIPER.</figcaption></figure>

A gradual change of secondary structure adopted along the polyQ has been proposed as central toward understanding pathogenicity [11, 12], implying that characterization of conformational dynamics along this tract using NMR relaxation analysis would be a logical pursuit. Although relaxation rates have been reported for other polyglutamine-containing proteins using 2D NMR [13, 14], the profound density of the 2D ¹H-¹⁵N HSQC of htt (Figure 1a) has until now obstructed relaxation measurements on individual glutamines [12]. Note that the 2D HSQC in Figure 1a was recorded with a digital resolution along the ¹⁵N dimension similar to the natural line-widths, yet much overlap remains. Baseline-resolved correlations can be achieved using resolution-enhancing apodization, but at a significant cost in signal-to-noise ratio (see Supporting Information). An existing method to facilitate resolving individual residues in polyQ sequences uses additional ¹³C isotope labelling and non-uniformly sampled (NUS) high-dimensional experiments [12, 13], but spectra reconstructed from NUS data result in significantly lower fidelity for relaxation analysis [15, 16]. Another strategy involves residue-specific ¹⁵N isotopic labeling [11, 17, 18], but these methods have insufficient protein yields for relaxation measurements and require separate protein productions per residue. The ideal approach would cleanly isolate an individual correlation from crowded signal densities at a similar sensitivity and resolution achievable by the standard 2D method, but with a much shorter minimal experimental time and without resorting to sparse data sampling or elaborate isotope labeling.

The new NMR approach introduced here, coined SNIPER (Selected Nuclei Irradiation for Precise and Expedited Relaxation measurements) meets these requirements. It cleanly delivers individual ¹H-¹⁵N correlations even when they are separated by very small ¹⁵N frequency differences. Several examples yielding individual glutamine correlations from htt exon-1 are shown overlayed on the standard ¹H-¹⁵N HSQC in Figure 1a, including from within the polyQ signal density and some that were not cleanly resolved in the standard 2D HSQC without resolution-enhancing apodization (Q18/Q20 and Q48/Q59). The spectral purity is highly satisfactory (Figure 1b), clearing the way to measure relaxation via fast 1D acquisition (Figure 1c).

Using 1D SNIPER, we obtained a full ¹⁵N R₁, R₂ and {¹H}-¹⁵N nOe dataset for each residue. Figure 2 shows ¹⁵N relaxation parameters extracted from a broad selection of glutamine signals using SNIPER. The fast 1D acquisition permitted sufficient signal averaging to attain good signal-to-noise ratios throughout the entire relaxation decay curves, resulting in high-quality mono-exponential fittings (Figures S18 and S19). Within the polyQ, the R₂ rates appear to be steady and high between Q18 and Q22, substantiating previous work that revealed Q20 and Q21 participate in bifurcated hydrogen bonding interactions with S16 and F17, respectively, stabilizing an α-helical secondary structure [18, 19]. The subsequent monotonic descent of R₂ rates toward the C-terminal end of the polyQ implies a gradual increase in the relative importance of motions occurring on single nanosecond
<figure><img src="image_5.png" /></figure>

**FIGURE 3** | SNIPER pulse sequences for measuring <sup>15</sup>N R<sub>1</sub> and R<sub>2</sub> (via constant-time R<sub>1ρ</sub>) [7] rates. Thin and wide filled black rectangles are hard 90° and 180° pulses, respectively. The <sup>15</sup>N selective 90° shaped pulse is colored green. White sine-bells are <sup>1</sup>H selective 90° pulses set to the water signal. Dark blue boxes are <sup>1</sup>H and <sup>15</sup>N irradiations at matched rf-field strength (ω<sub>1</sub> = 0.5×J<sub>NH</sub>) for selective polarization transfer. Grey rectangles represent CW irradiation of the amide proton. The delay ζ is 0-5 ms and Δ is 5-40 ms. χ is a delay matched to the <sup>1</sup>H CW power so the amide proton and water magnetizations are simultaneously aligned with the CW effective B<sub>1</sub>-field [23]. <sup>1</sup>H<sup>N</sup> selective inversion pulses are shown as grey shapes. The <sup>15</sup>N R<sub>1ρ</sub> spin-lock (SL) is applied on-resonance and temperature compensation spin-locks (TC) far off-resonance. The <sup>15</sup>N open-bar rectangles are pulses with flip angles matched to the spin-lock's offset from the <sup>15</sup>N resonance of interest [7]. Grey trapezoids are pulsed field gradients. CPD denotes composite pulse decoupling. The Supporting Information contains phase cycling, gradient amplitudes and further technical details.

time-scales [20–22]. This agrees with previous chemical shift analysis studies indicating that the α-helical propensity gradually decreases along the polyQ [11, 12, 17, 18]. The R₁ rates fluctuate along the polyQ, suggesting a diversity of motions on single nanosecond timescales. The {¹H}-¹⁵N nOes drop markedly beyond Q26, pointing toward a relative increase in the importance of motions occurring on the order of hundreds of picosecond time-scale [20–22]. This indicates a loss of cooperative motions in the C-terminal segment of the polyQ and thus lack of stable secondary structures. This is consistent with previous conclusions based on chemical shifts that suggested the helical structure is almost entirely vanished at Q28 for the htt polyQ-16 sequence [18]. For the glutamines in the proline-rich region (Q45-Q61), a remarkably non-uniform picture emerges for all relaxation parameters. This suggests a diversity of motional behaviors that could be due to yet unidentified specific interresidue contacts and local secondary structures.

Figure 3 shows the SNIPER pulse sequences for <sup>15</sup>N R<sub>1</sub> and R<sub>2</sub> measurements (the {¹H}-¹⁵N nOe sequence is found in Figure S12). It applies selective in-phase <sup>1</sup>H-<sup>15</sup>N polarization transfers using matched <sup>1</sup>H and <sup>15</sup>N irradiation, either applied simultaneously (Hartmann-Hahn, HaHa) or consecutively (refocused single field polarization transfer, rSFPT) [4, 7, 24–27]. This already provides a selectivity of ca. 35-45 Hz in both <sup>1</sup>H and <sup>15</sup>N (see Supporting Information), similar to previous methods [7] but insufficient for very dense spectra such as htt. We therefore implemented a <sup>15</sup>N chemical-shift-selective filter (CSSF), consisting out of a 90°-y-ζ-90°-y sequence applied on longitudinal <sup>15</sup>N magnetization

during <sup>1</sup>H continuous wave (CW) decoupling, followed by a purge gradient. Previous selective methods used the ζ-delay to remove <sup>15</sup>N signals found (4ζ⁻¹ Hz off-resonance [7]), but this results in unacceptably high relaxation losses for very small frequency differences. SNIPER rather achieves its ultra-high <sup>15</sup>N selectivity by replacing the first <sup>15</sup>N 90° pulse in the CSSF by a selective excitation pulse. To cleanly differentiate close <sup>15</sup>N frequencies, this pulse should feature a sharp excitation profile, without off-resonance excitation side-bands, while being as efficient as possible in terms of relaxation losses. We found the classical Half-Gauss shape [28, 29] to be well-suited in many cases. For very small <sup>15</sup>N chemical shift differences (< ca. 12 Hz), however, as found in htt-exon-1, we could only achieve sufficient selectivity and sensitivity using a novel pulse shape derived using optimal control theory [30], which we coin GOLEM (*Gradient Optimized Line-width Exact Matching*) (see Supporting Information). The key feature of GOLEM is that the excitation profile and <sup>15</sup>N relaxation-weighting for long pulses (>100 ms) conspire [31] to yield a sharper excitation transition band. The improved <sup>15</sup>N CSSF results in a satisfying overall <sup>15</sup>N selectivity of SNIPER that can go as low as 6-8 Hz, approaching the natural line-width. This is far superior to what was achieved previously for 1D selective R<sub>1ρ</sub> experiments [7]. The cost in sensitivity is modest, as relaxation-weighting during the long GOLEM pulse is largely determined by <sup>15</sup>N R<sub>1</sub> rather than R<sub>2</sub>, as demonstrated experimentally in the Supporting Information. For instance, for Q18, one of the fasted relaxing glutamines and just 8 Hz away from Q20, 1D SNIPER was found to deliver a similar signal-to-noise ratio than a high-resolution 2D spectrum, but with an experimental time that is
four times less. Importantly, the minimal experimental time of the 2D approach to resolve individual resonances is limited by the sampling of time-domain points along the indirect dimension. 1D SNIPER does not have this limitation, meaning it can further trade-in signal-to-noise for speed. This is partly compensated for by using a residue-specific optimized sampling of the relaxation-weighting delays, delivering reliable relaxation rates even at lower signal-to-noise ratios (see Supporting Information) [5].

Fast 1D selective methods are equally beneficial for quantifying millisecond conformational exchange. Standard 2D *zz*-exchange experiments feature additional ‘cross-peaks’ between the correlations of the slowly exchanging states (‘diagonal peaks’) [32], often delivering congested spectra even in the case of folded proteins. When the ¹⁵N chemical shifts of the two exchanging states are close, quantification of the exchange rates via such cross-peaks requires long 2D data acquisitions [32]. SNIPER can separate the two states using fast 1D spectra and thus also the cross-peaks between them. The Supporting Information contains an illustration of this principle on the folded SH3 domain of the SH3GL3 protein [33]. Another *zz*-exchange approach that reported improved ¹⁵N selectivity is the *F*₁*F*₂-selective experiment, which combines selective HaHa with 2D acquisition to resolve close ¹⁵N chemical shifts [34, 35]. However, this results in profoundly longer experimental times and turned out unsuccessful in resolving exchange cross-peaks that were readily obtained using SNIPER (see Supporting Information).

SNIPER delivers high-quality, high-precision atom-resolved information on conformational dynamics of individual residues in a fraction of the time needed by 2D approaches. It provides access to key functional residues in crowded spectral regions when an exhaustive full spectral analysis is not required or when sample lifetimes are short, such as for aggregation-prone proteins. This makes SNIPER a powerful complement to recently proposed selective methods for fast spectral assignment, such as FOSY [4]. Importantly, in contrast to these methods, it does not rely on ¹³C labeling. We foresee it to be especially beneficial for experiments whose optimal setup is very residue-specific, such as off-resonance R₁ρ relaxation dispersion or CEST [6–8]. Even in cases where ¹⁵N R₁, R₂ and {¹H}-¹⁵N nOe relaxation data from a maximum of residues is required, the most time-efficient strategy will be to first use the 2D approach for well-resolved correlations and then apply complementary SNIPER experiments on key residues located in dense spectral regions. For IDPs, which commonly feature very crowded spectra, it will thus provide rapid access to conformational dynamics that previously would have been challenging to collect. The opportunities created by the ability to selectively excite an individual residue with a ¹⁵N resolution approaching the natural line-width can be seen as similar to the recent breakthrough of ultra-selective fast 1D methods in small molecule ¹H NMR [36–39]. We expect SNIPER will find wide application in protein dynamics studies, as well as for other biomacromolecules such as RNA.

## Acknowledgments

The authors thank Emannuelle Boll (CNRS UMR 9031) for help with the SH3 domain assignment. D.S. acknowledges funding from the Agence Nationale de la Recherche (ANR) (ANR-20-CE29-0015-01 URANUS) and

an « *accueil de talent* » grant from the Métropole Européenne de Lille (PUSHUP). The 600 MHz NMR spectrometer is funded by the Nord Region Council, CNRS, Institut Pasteur de Lille, the European Community (ERDF), the French Ministry of Research and the Université de Lille and by the CTRL CPER co-funded by the European Union with the European Regional Development Fund (ERDF), by the Hauts-de-France Regional Council (contract n°17003781), Métropole Européenne de Lille (contract n°2016_ESR_05), and French State (contract n°2017-R3-CTRL-Phase1). The IR INFRANALYTICS FR2054 is gratefully acknowledged for financial support of the 900 MHz NMR spectrometer.

Open access publication funding provided by COUPERIN CY26.

## Conflicts of Interest

The authors declare no conflicts of interest.

## Data Availability Statement

NMR raw data, Bruker pulse sequences and pulse shapes can be downloaded from https://doi.org/10.5281/zenodo.16489356.

## References

1. A. G. Palmer and F. Massi, "Characterization of the Dynamics of Biomacromolecules Using Rotating-Frame Spin Relaxation NMR Spectroscopy," *Chemical Reviews* 106 (2006): 1700-1719, https://doi.org/10.1021/cr0404287.

2. C. Charlier, S. F. Cousin, and F. Ferrage, "Protein Dynamics From Nuclear Magnetic Relaxation," *Chemical Society Reviews* 45 (2016): 2410-2422, https://doi.org/10.1039/C5CS00832H.

3. A. R. Camacho-Zarco, V. Schnapka, S. Guseva, et al., "NMR Provides Unique Insight Into the Functional Dynamics and Interactions of Intrinsically Disordered Proteins," *Chemical Reviews* 122 (2022): 9331-9356, https://doi.org/10.1021/acs.chemrev.1c01023.

4. D. M. Lesovoy, P. S. Georgoulia, T. Diercks, et al., "Unambiguous Tracking of Protein Phosphorylation by Fast High-Resolution FOSY NMR," *Angewandte Chemie International Edition* 60 (2021): 23540-23544, https://doi.org/10.1002/anie.202102758.

5. J. A. Jones, P. Hodgkinson, A. L. Barker, and P. J. Hore, "Optimal Sampling Strategies for the Measurement of Spin-Spin Relaxation Times," *Journal of Magnetic Resonance, Series B* 113 (1996): 25-34, https://doi.org/10.1006/jmrb.1996.0151.

6. X. G. Niu, J. Ding, W. B. Zhang, Q. W. Li, Y. F. Hu, and C. W. Jin, "Residue Selective ¹⁵N CEST and CPMG Experiments for Studies of Millisecond Timescale Protein Dynamics," *Magnetic Resonance* 293 (2018): 47-55, https://doi.org/10.1016/j.jmr.2018.05.016.

7. D. M. Korzhnev, V. Y. Orekhov, and L. E. Kay, "Off-Resonance R₁ρ NMR Studies of Exchange Dynamics in Proteins With Low Spin-Lock Fields: An Application to a Fyn SH3 Domain," *Journal of the American Chemical Society* 127 (2005): 713-721, https://doi.org/10.1021/ja0446855.

8. P. Vallurupalli, G. Bouvignies, and L. E. Kay, "Studying "Invisible" Excited Protein States in Slow Exchange With a Major State Conformation," *Journal of the American Chemical Society* 134 (2012): 8148-8161, https://doi.org/10.1021/ja3001419.

9. R. Auer, P. Neudecker, D. R. Muhandiram, et al., "Measuring the Signs of ¹Hα Chemical Shift Differences between Ground and Excited Protein States by Off-Resonance Spin-Lock R₁ρ NMR Spectroscopy," *Journal of the American Chemical Society* 131 (2009): 10832-10833, https://doi.org/10.1021/ja904315m.

10. F. Saudou and S. Humbert, "The Biology of Huntingtin," *Neuron* 89 (2016): 910-926, https://doi.org/10.1016/j.neuron.2016.02.003.

11. C. A. Elena-Real, A. Sagar, A. Urbanek, et al., "The Structure of Pathogenic Huntingtin Exon1 Defines the Bases of Its Aggregation Propensity," *Nature Structural & Molecular Biology* 30 (2023): 309-320, https://doi.org/10.1038/s41594-023-00920-0.
12. M. Baias, P. E. S. Smith, K. Shen, et al., "Structure and Dynamics of the Huntingtin Exon-1 N-Terminus: A Solution NMR Perspective," *Journal of the American Chemical Society* 139 (2017): 1168–1176, https://doi.org/10.1021/jacs.6b10893.

13. B. Eftekharchadeh, A. Piai, G. Chiesa, et al., "Sequence Context Influences the Structure and Aggregation Behavior of a PolyQ Tract," *Biophysical Journal* 110 (2016): 2361–2366, https://doi.org/10.1016/j.bpj.2016.04.022.

14. A. Escobedo, J. Piccirillo, J. Aranda, et al., "A Glutamine-Based Single α-Helix Scaffold to Target Globular Proteins," *Nature Communications* 13 (2022): 7073, https://doi.org/10.1038/s41467-022-34793-6.

15. M. Urbańczyk, M. Nowakowski, W. Koźmiński, and K. Kazimierczuk, "Joint Non-Uniform Sampling of all Incremented Time Delays for Quicker Acquisition in Protein Relaxation Studies," *Journal of Biomolecular NMR* 68 (2017): 155–161, https://doi.org/10.1007/s10858-017-0115-8.

16. G. Carlström, F. Elvander, J. Swärd, A. Jakobsson, and M. Akke, "Rapid NMR Relaxation Measurements Using Optimal Nonuniform Sampling of Multidimensional Accordion Data Analyzed by a Sparse Reconstruction Method," *Journal of Physical Chemistry A* 123 (2019): 5718–5723, https://doi.org/10.1021/acs.jpca.9b04152.

17. A. Urbanek, A. Morató, F. Allemand, et al., "A General Strategy to Access Structural Information at Atomic Resolution in Polyglutamine Homorepeats," *Angewandte Chemie International Edition* 57 (2018): 3598–3601, https://doi.org/10.1002/anie.201711530.

18. A. Urbanek, M. Popovic, A. Morató, et al., "Flanking Regions Determine the Structure of the Poly-Glutamine in Huntingtin Through Mechanisms Common Among Glutamine-Rich Human Proteins," *Structure* (London, England) 28 (2020): 733–746, https://doi.org/10.1016/j.str.2020.04.008.

19. A. Escobedo, B. Topal, M. B. A. Kunze, et al., "Side Chain to Main Chain Hydrogen Bonds Stabilize a Polyglutamine Helix in a Transcription Factor," *Nature Communications* 10 (2019): 2034, https://doi.org/10.1038/s41467-019-09923-2.

20. S. N. Khan, C. Charlier, R. Augustyniak, et al., "Distribution of Pico- and Nanosecond Motions in Disordered Proteins From Nuclear Spin Relaxation," *Biophysical Journal* 109 (2015): 988–999, https://doi.org/10.1016/j.bpj.2015.06.069.

21. A. Abyzov, N. Salvi, R. Schneider, et al., "Identification of Dynamic Modes in an Intrinsically Disordered Protein Using Temperature-Dependent NMR Relaxation," *Journal of the American Chemical Society* 138 (2016): 6240–6251, https://doi.org/10.1021/jacs.6b02424.

22. M. L. Gill, R. A. Byrd, and A. G. Palmer Iii, "Dynamics of GCN4 Facilitate DNA Interaction: A Model-Free Analysis of an Intrinsically Disordered Region," *Physical Chemistry Chemical Physics* 18 (2016): 5839–5849, https://doi.org/10.1039/C5CP06197K.

23. D. F. Hansen and L. E. Kay, "Improved Magnetization Alignment Schemes for Spin-Lock Relaxation Experiments," *Journal of Biomolecular NMR* 37 (2007): 245–255, https://doi.org/10.1007/s10858-006-9126-6.

24. E. R. Rey Castellanos, D. P. Frueh, and J. Wist, "Selective Polarization Transfer Using a Single rf Field," *Journal of Chemical Physics* 129 (2008): 014504, https://doi.org/10.1063/1.2939572.

25. Y. Toyama and I. Shimada, "Frequency Selective Coherence Transfer NMR Spectroscopy to Study the Structural Dynamics of High Molecular Weight Proteins," *Journal of Magnetic Resonance* 304 (2019): 62–77, https://doi.org/10.1016/j.jmr.2019.05.004.

26. P. Pelupessy and E. Chiarparin, "Hartmann-Hahn Polarization Transfer in Liquids: An Ideal Tool for Selective Experiments," *Concepts in Magnetic Resonance* 12 (2000): 103–124, https://doi.org/10.1002/(SICI)1099-0534(2000)12:3%3c103::AID-CMR1%3e3.0.CO;2-.

27. P. Pelupessy, E. Chiarparin, and G. Bodenhausen, "Excitation of Selected Proton Signals in NMR of Isotopically Labeled Macromolecules," *Journal of Magnetic Resonance* 138 (1999): 178–181, https://doi.org/10.1006/jmre.1999.1715.

28. H. Kessler, U. Anders, G. Gemmecker, and S. Steuernagel, "Improvement of NMR Experiments by Employing Semiselective Half-Gaussian-Shaped Pulses," *Journal of Magnetic Resonance* 85 (1989): 1–14.

29. R. Freeman, "Selective Excitation in High-Resolution NMR," *Chemical Reviews* 91 (1991): 1397–1412, https://doi.org/10.1021/cr00007a006.

30. T. E. Skinner, T. O. Reiss, B. Luy, N. Khaneja, and S. J. Glaser, "Application of Optimal Control Theory to the Design of Broadband Excitation Pulses for High-resolution NMR," *Journal of Magnetic Resonance* 163 (2003): 8–15, https://doi.org/10.1016/S1090-7807(03)00153-8.

31. J. M. Nuzillard and R. Freeman, "Band-Selective Pulses Designed to Accommodate Relaxation," *Journal of Magnetic Resonance, Series A* 107 (1994): 113–118, https://doi.org/10.1006/jmra.1994.1056.

32. N. A. Farrow, O. W. Zhang, J. D. Forman-Kay, and L. E. Kay, "A Heteronuclear Correlation Experiment for Simultaneous Determination of ¹⁵N Longitudinal Decay and Chemical Exchange Rates of Systems in Slow Equilibrium," *Journal of Biomolecular NMR* 4 (1994): 727–734, https://doi.org/10.1007/BF00404280.

33. A. Sittler, S. Wälter, N. Wedemeyer, et al., "SH3GL3 associates With the Huntingtin Exon 1 Protein and Promotes the Formation of Polyglync-Containing Protein Aggregates," *Molecular Cell* 2 (1998): 427–436, https://doi.org/10.1016/S1097-2765(00)80142-2.

34. M. Nishizawa, E. Walinda, D. Morimoto, and K. Sugase, "Pinpoint Analysis of a Protein in Slow Exchange Using F₁F₂-Selective ZZ-Exchange Spectroscopy: Assignment and Kinetic Analysis," *Journal of Biomolecular NMR* 74 (2020): 205–211, https://doi.org/10.1007/s10858-020-00309-x.

35. E. Walinda, D. Morimoto, M. Shirakawa, and K. Sugase, "F₁F₂-Selective NMR Spectroscopy," *Journal of Biomolecular NMR* 68 (2017): 41–52, https://doi.org/10.1007/s10858-017-0113-x.

36. P. Kiraly, N. Kern, M. P. Plesniak, et al., "Single-Scan Selective Excitation of Individual NMR Signals in Overlapping Multiplets," *Angewandte Chemie International Edition* 60 (2021): 666–669, https://doi.org/10.1002/anie.202011642.

37. P. Kiraly, M. Nilsson, G. A. Morris, and R. W. Adams, "Single-Scan Ultra-Selective 1D Total Correlation Spectroscopy," *Chemical Communications* 57 (2021): 2368–2371, https://doi.org/10.1039/D0CC08033K.

38. J. W. Cha, M. S. Kim, and J. S. Park, "A Single-Scan Ultraselective Heteronuclear Polarization Transfer Method for Unambiguous Complex Structure Assignment," *Angewandte Chemie International Edition* 62 (2023): e202304196, https://doi.org/10.1002/anie.202304196.

39. E. L. Gates, M. J. Smith, J. P. Bradley, et al., "Ultra-Selective, Ultra-clean 1D Rotating-frame Overhauser Effect Spectroscopy," *Chemical Communications* 59 (2023): 5854–5857, https://doi.org/10.1039/D3CC00550J.

## Supporting Information

Additional supporting information can be found online in the Supporting Information section.

The authors have cited additional references within the Supporting Information [1–30].

**Supporting File:** anie71519-sup-0001-SuppMat.pdf