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Sensitivity-enhanced Four-dimensional Amide-amide Correlation NMR Experiments for Sequential Assignment of Proline-rich Disordered Proteins Leo E Wong, Joachim Maier, Jürgen Wienands, Stefan Becker, and Christian Griesinger J. Am. Chem. Soc., Just Accepted Manuscript • DOI: 10.1021/jacs.8b00215 • Publication Date (Web): 28 Feb 2018 Downloaded from http://pubs.acs.org on March 1, 2018

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Journal of the American Chemical Society

Sensitivity-enhanced Four-dimensional Amide-amide Correlation NMR Experiments for Sequential Assignment of Prolinerich Disordered Proteins Leo E. Wong,*,# Joachim Maier,# Jürgen Wienands,^ Stefan Becker,# and Christian Griesinger*,# #Department for NMR-based Structural Biology, Max Planck Institute for Biophysical Chemistry, Am Faßberg 11, 37077 Göttingen, Germany. ^Institute of Cellular and Molecular Immunology, Georg August University of Göttingen, Humboldtallee 34, 37073 Göttingen, Germany.

Supporting Information Placeholder ABSTRACT: Proline is prevalent in intrinsically disordered proteins (IDPs). NMR assignment of proline-rich IDPs is a challenge due to low dispersion of chemical shifts. We propose here new sensitivity-enhanced 4D NMR experiments that correlate two pairs of amide resonances that are either consecutive (NHi-1, NHi) or flanking a proline at position i-1 (NHi-2, NHi). The maximum two-fold enhancement of sensitivity is achieved by employing two coherence order-selective (COS) transfers incorporated unconventionally into the pulse sequence. Each COS transfer confers an enhancement over amplitude-modulated transfer by a factor of √2 specifically when transverse relaxation is slow. The experiments connect amide resonances over a long fragment of sequence interspersed with proline. When this method was applied to the proline-rich region of B cell adaptor protein SLP-65 (pH 6.0) and α-synuclein (pH 7.4), which contain a total of 52 and 5 prolines, respectively, 99 % and 92 % of their non-prolyl amide resonances have been successfully assigned, demonstrating its robustness to address the assignment problem in large prolinerich IDPs.

Proline is abundant in the human proteome, accounting for 68% of all amino acids1,2. In many cases, short proline-rich sequences serve as recognition motifs for several protein-interaction domains like SH3, WW, and EVH1 domains3. Hence, prolines are expected to be more abundant in adaptor proteins that function as recruiters of other proteins for signal transduction. Proline confers special properties on the backbone conformation of a protein4. Proline disfavors formation of α-helix and β-sheet, resulting in an extended chain conformation. On the other hand, polyproline sequences have a tendency to form polyproline II helices. Therefore, prolyl residues interspersed along the amino acid sequence of an IDP are likely to have an impact on its ensemble structures and function. SLP-655 (SH2 domain-containing leukocyte adaptor protein of 65 kDa), which is also called BLNK6 (B-cell linker protein), is an adaptor protein central to B-cell antigen receptor activated signaling for B cell differentiation7,8. The N-terminal domain of SLP-65 has been assigned and shown to interact with lipid vesicles in a residue-specific manner9. The proline-rich region of SLP-65 (residue 41 to 330) is of great interest for structural studies, since it possesses multiple phosphorylation sites6,10 as well as binding sites for SH3 domains11.

The suite of established 3D triple-resonance experiments for backbone assignment of folded proteins12 is inadequate for large IDPs due to severe overlap of the resonances especially for 1H, 13 α C and 13Cβ nuclei13. The general strategy for circumventing this problem is by acquiring higher dimensional NMR spectra that correlate multiple backbone nuclei of two adjacent residues. A multitude of methods for sparse sampling of spectra, spectral processing and analysis14,15 is mandatory for such endeavors. For instance, G-matrix Fourier transform16,17, projection reconstruction18-20 and automated projection spectroscopy (APSY)21-24 are related methods categorized as reduced-dimensionality NMR. Alternatively, multidimensional decomposition25,26 and sparse multidimensional Fourier transform13,27,28 are also widely used to reconstruct non-uniformly sampled high-dimensional spectra. Besides HN-based experiments, CON-based high-dimensional spectra are also employed for the assignment of IDPs29-33. 13Cdetection has three advantages. First, it avoids amide protons that usually undergo fast amide-water exchange at physiological pH and temperature34. Second, it harnesses the large chemical shift dispersion of carbonyl carbons35. Third, proline’s 15N chemical shifts can be directly assigned. However, sensitivity of 13Cdetected experiments is in general lower than proton detection, and this disadvantage is only moderately ameliorated with dedicated NMR probes. Furthermore, amide 1H chemical shift dispersion of IDPs is similar to carbonyl 13C’s29, and 2D 1HN– 15NH peaks are usually well resolved even for repetitive sequences of the same amino acid (Figure S2). Therefore, amide-amide correlation peaks in a 4D spectrum are expected to be resolved in most circumstances. In addition, matching of the 1HN and 15NH chemical shifts of connected residues is straightforward and can be automated. This assignment strategy has also been demonstrated in proton-detected solid-state NMR36-38. Despite the gain in resolution, every additional dimension in an nD experiment incurs sensitivity loss by √2, since amplitudemodulated (AM) quadrature signals have to be added for frequency discrimination. An nD NMR experiment can thus become sensitivity-limited by a factor of 2(n-1)/2, in addition to concomitant loss through multiple magnetization transfer steps. It is well known that sensitivity loss imposed by AM transfer can be recovered by employing coherence order-selective (COS) transfers between the evolution periods39-42. These COS transfers are normally up to twice as long as the AM transfers, and are therefore

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confined to slowly relaxing nuclei, which is exactly the case for IDPs whose transverse relaxation rates are normally small.

Figure 1. General principle of sensitivity enhancement by several coherence order-selective (COS) transfers. In an nD experiment, every COS transfer confers a maximal enhancement factor of √2 over amplitude-modulated (AM) transfer. The overall sensitivity enhancement via multiple COS transfers is independent of the order of combination with AM transfers. We show here, as a general principle in nD NMR experiments, that the overall enhancement of sensitivity gained from arbitrary numbers of COS transfer is independent of the order of combination with AM transfers (Figure 1). Conventionally in almost all pulse sequences that are gradient- and sensitivity-enhanced, there is only one COS transfer directly preceding the detection period, while all other transfers between chemical shift evolutions are AM types. Replacement of an AM transfer by a COS transfer between times ti and ti+1 implies that the four modulation functions necessary for pure phase spectrum: cos   cos  , sin   cos   , cos   sin   , and sin   sin   are replaced by    and

∓   in phase modulation. Mathematical derivation in the Supporting Information shows that such phase-modulated signals can be converted back to amplitude modulation while preserving the enhancement factor of √2. Conceptually, this is possible since the orthogonal Cartesian operators at the end of ti+1 is amplitude-modulated by a superposition of both Cartesian operators before ti+1 evolution and the phase modulation is thus propagated. Sensitivity-enhanced HSQC/TROSY-NOESY43-45 experiments implicitly used this principle without stating it in its general form. Hence, the general formulation opens up the possibility to use several COS steps as we introduce here to improve the sensitivity of two 4D amide-amide correlation experiments, which can be extended to other sequences especially for IDPs.

Figure 2. Maximum two-fold enhancement of sensitivity. (A) The 1D traces are projection along the indirect dimension of 2D APSY spectra projected with angles (α, β) = (+75°, +10°) from two versions of 4D HNcocaNH experiment, i.e. from Fiorito et al. that was modified to include water flip-back pulses (red) and the doubly sensitivity-enhanced experiment presented in this work (blue). The comparison was done on SLP-6541-330 (pH 7.2) and αsynuclein (pH 7.4) at 288 K. (B) The sensitivity gain for each peak found in the 2D APSY spectra in (A).

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4D HNcocaNH46 is very useful for 15N-HSQC spectral assignment of large IDPs, due to exceptional resolution and unambiguous sequential assignment based on matching two pairs of chemical shifts. We seek to enhance the robustness of the experiment by incorporating two COS transfers into a pulse sequence from Fiorito et al.22 (Figures S1A and C). By employing two refocused INEPT sequences39-42 between 1 and 2, and 3 and 4, the theoretical maximum of two-fold sensitivity enhancement can be achieved (Figure 2). Note that a specific scheme of data recombination is required prior to conventional processing of the doubly sensitivity-enhanced spectrum (Supporting Information). In IDPs, relatively fast amide-water exchange could dominate relaxation and render the COS transfers suboptimal for some residues. Nevertheless, the enhanced experiment has provided a median sensitivity gain of 1.6 for two proteins at neutral pH, while less than 3 % of the peaks experienced a reduction in sensitivity (Figure 2B). After incorporation of two COS transfers, the enhanced experiment has two additional INEPT periods and a spin echo that add up to 11.8 ms. Neglecting relaxations other than that due to solvent exchange, the advantage of sensitivity enhancement will disappear only when the exchange rate reaches 60 s-1. Residues with such a high solvent-exchange rate are usually severely broadened in a 15N-HSQC spectrum, making them less suitable for HN-based experiments.

Figure 3. Sensitivity of 4D HNcocaNH and HNcocancaNH (xP-x) relative to 15N-HSQC. The sensitivity-enhanced HNcocaNH (red) and HNcocancaNH (x-P-x) (green) experiments were measured in a 2D fashion by evolving only the last two dimensions, and compared with the respective 15N-HSQC spectrum (blue). Data were acquired on 0.6 mM SLP-6541-330 at pH 7.2 (A) and 0.3 mM α-synuclein at pH 7.4 (B). Projections of the individual spectrum in (A) and (B) are shown in (C) and (D), respectively. Proline interrupts connectivity in the 4D HNcocaNH experiment. We propose here a new 4D experiment that contains two additional transfer steps to connect amides NHi-2 and NHi whose amino acids are separated by a proline (Figures S1B and D). This 4D HNcocancaNH (x-P-x) experiment leverages the sensitivity enhancement similarly to the enhanced 4D HNcocaNH. The pulse sequence is detailed in the Supporting Information. Specifically, during magnetization transfer across the proline’s 15N(i-1), it is difficult to suppress the effects of the scalar coupling of prolyl 13 δ C to 15N(i-1). Hence, optimal efficiency of the targeted transfer to 13Cα(i-2) is limited to about 40 % (Figure S1E). In spite of this limitation as well as relaxation loss during additional transfer delays, 2D spectra of the experiment showing the expected peaks could be obtained within reasonable measurement time (Figure 3). Peaks in the 15N-HSQC spectrum of α-synuclein exhibit more uniform intensity compared to those of SLP-6541-330. Therefore, it is advisable to acquire the 4D HNcocancaNH (x-P-x) experiment

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Journal of the American Chemical Society with 10-12 times the numbers of scans of 4D HNcocaNH for proteins with a broad range of peak intensity in the 15N-HSQC spectrum. For the assignment of SLP-6541-330, sensitivity-enhanced 4D HNcocaNH and HNcocancaNH (x-P-x) experiments were measured with the APSY approach on a 0.7 mM 13C, 15N-uniformly labeled sample at pH 6.0 and 288 K (Supporting Information). Projection spectra of the 4D experiments can be analyzed by GAPRO21, which provides two separate 4D peaklists with high precision. Sequential assignment can then be performed using a MATLAB script that matches two pairs of 1HN and 15NH chemical shifts of correlated spin systems, while taking into account the number of supports47. All non-prolyl residues except for Q302-H304 have been successfully assigned (Figures 4A, 4B and S3), as confirmed by amino acid-selective HSQC experiments48. Out of the 33 pairs of x-P-x connectivity (x = non-proline) expected from the sequence, 31 pairs were determined directly from the second 4D experiment (Figures 4A and C).

84 % of the non-prolyl residues, which accounts for almost all observable peaks in the 15N-HSQC spectrum (Figure S4). Chemical shift changes in the protein between pH 6 and pH 7.2 are limited to the residues close to histidine (Figure S5). Several 13C-detected CON-based experiments have been demonstrated to be useful for the assignment of IDPs containing prolines29-33. As a comparison, we have applied our method to a sample of 0.3 mM α-synuclein at pH 7.4 and successfully assigned 92 % of its non-prolyl residues50 within 41 hours of measurement time (Supporting Information). Previous studies using CON-based experiments to assign α-synuclein30,32,35 were performed on samples at a concentration of 1.0-1.2 mM and at pH 6.5-6.8, which took several days of measurement time. Therefore, the HN-based method is indeed very efficient and may become advantageous for proteins that are only stable for limited time or at low concentration. A recently proposed 3D/5D experiment that relies on isotropic mixing via 3J(C’,C’) coupling to correlate multiple carbonyls to individual amide can be useful for proteins with many stretches of contiguous prolines51,52. Furthermore, there are other strategies to overcome interruption by proline that are based on Hα-53-55 or HN-detected56,57 experiments. Nonetheless, matching two pairs of chemical shifts from correlated amides is straightforward, and hence the sensitivity-enhanced 4D experiments represent an attractive tool for sequential assignment of large IDPs. Although proline-rich peptides have been studied extensively by NMR, structural investigation of large IDPs with wide span of proline-rich regions is hindered by the technical difficulty of residue-specific resonance assignment. We have demonstrated here a simple and robust method to assign proline-rich IDPs that should only be minimally limited by protein size. This method has the potential to accelerate NMR studies of large IDPs. The general sensitivity enhancement principle can be applied to other pulse sequences used for assignment and NMR investigations of IDPs.

ASSOCIATED CONTENT Data Deposition The assigned chemical shifts have been deposited to BMRB with the accession number 27228.

Supporting Information Supporting information and figures, the pulse program for both experiments, and the python script to recombine FIDs are available free of charge on the ACS Publications website.

AUTHOR INFORMATION Figure 4. Residue-specific assignment of SLP-6541-330. (A) Amino acid sequence of SLP-6541-330 labeled as assigned (black), unassigned (grey), and proline (red). x-P-x connectivity that were determined from sensitivity-enhanced HNcocancaNH (x-P-x) are highlighted by blue-colored boxes. (B) A subset of 2D APSY spectra of sensitivity-enhanced HNcocaNH experiment that were analyzed to assign SLP-6541-330. The full set is detailed in the Supporting Information. (C) A subset of 2D APSY spectra of sensitivity-enhanced HNcocancaNH (x-P-x) experiment. (D) Population of random coil as well as of different secondary structures of SLP-6541-330 as determined by δ2D. With the assignment of amide resonances, the chemical shifts of 13Cα, 13Cβ and 13C’ can be easily obtained from 3D HNCACB and HNcaCO experiments. Based on these chemical shifts, δ2D49 analysis indicates that SLP-6541-330 is largely random coil with 27 % population of polyproline II helix (Figure 4D). We have also measured the 4D experiments on a sample at pH 7.2 and assigned

Corresponding Author *[email protected] *[email protected]

Notes The authors declare no competing financial interests.

ACKNOWLEDGMENT This work was supported by the MPG and the DFG (SFB 860 project B5 to J.W. and C.G.). Shengqi Xiang is acknowledged for an introduction to APSY. We thank Claudia Schwiegk for excellent technical work on protein expression and purification, and Melanie Wegstroth for the α-synuclein sample.

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REFERENCES (1) Morgan, A. A.; Rubenstein, E. PLoS One 2013, 8, e53785. (2) Theillet, F. X.; Kalmar, L.; Tompa, P.; Han, K. H.; Selenko, P.; Dunker, K. A.; Daughdrill, G. W.; Uversky, V. N. Intrinsically Disord Proteins 2013, 1, e24360. (3) Kay, B. K.; Williamson, M. P.; Sudol, M. FASEB J 2000, 14, 231. (4) Williamson, M. P. Biochem J 1994, 297, 249. (5) Wienands, J.; Schweikert, J.; Wollscheid, B.; Jumaa, H.; Nielsen, P. J.; Reth, M. J Exp Med 1998, 188, 791. (6) Fu, C.; Turck, C. W.; Kurosaki, T.; Chan, A. C. Immunity 1998, 9, 93. (7) Pappu, R.; Cheng, A. M.; Li, B.; Gong, Q.; Chiu, C.; Griffin, N.; White, M.; Sleckman, B. P.; Chan, A. C. Science 1999, 286, 1949. (8) Minegishi, Y.; Rohrer, J.; Coustan-Smith, E.; Lederman, H. M.; Pappu, R.; Campana, D.; Chan, A. C.; Conley, M. E. Science 1999, 286, 1954. (9) Engelke, M.; Pirkuliyeva, S.; Kühn, J.; Wong, L.; Boyken, J.; Herrmann, N.; Becker, S.; Griesinger, C.; Wienands, J. Sci Signal 2014, 7, ra79. (10) Oellerich, T.; Grønborg, M.; Neumann, K.; Hsiao, H. H.; Urlaub, H.; Wienands, J. Mol Cell Proteomics 2009, 8, 1738. (11) Oellerich, T.; Bremes, V.; Neumann, K.; Bohnenberger, H.; Dittmann, K.; Hsiao, H. H.; Engelke, M.; Schnyder, T.; Batista, F. D.; Urlaub, H.; Wienands, J. EMBO J 2011, 30, 3620. (12) Sattler, M.; Schleucher, J.; Griesinger, C. Prog Nucl Magn Reson Spectrosc 1999, 34, 93. (13) Motáčková, V.; Nováček, J.; Zawadzka-Kazimierczuk, A.; Kazimierczuk, K.; Zídek, L.; Sanderová, H.; Krásný, L.; Koźmiński, W.; Sklenář, V. J Biomol NMR 2010, 48, 169. (14) Hyberts, S. G.; Arthanari, H.; Robson, S. A.; Wagner, G. J Magn Reson 2014, 241, 60. (15) Mobli, M.; Hoch, J. C. Prog Nucl Magn Reson Spectrosc 2014, 83, 21. (16) Kim, S.; Szyperski, T. J Am Chem Soc 2003, 125, 1385. (17) Atreya, H. S.; Eletsky, A.; Szyperski, T. J Am Chem Soc 2005, 127, 4554. (18) Kupče, E.; Freeman, R. J Am Chem Soc 2003, 125, 13958. (19) Coggins, B. E.; Venters, R. A.; Zhou, P. J Am Chem Soc 2004, 126, 1000. (20) Venters, R. A.; Coggins, B. E.; Kojetin, D.; Cavanagh, J.; Zhou, P. J Am Chem Soc 2005, 127, 8785. (21) Hiller, S.; Fiorito, F.; Wüthrich, K.; Wider, G. Proc Natl Acad Sci U S A 2005, 102, 10876. (22) Fiorito, F.; Hiller, S.; Wider, G.; Wüthrich, K. J Biomol NMR 2006, 35, 27. (23) Hiller, S.; Wasmer, C.; Wider, G.; Wüthrich, K. J Am Chem Soc 2007, 129, 10823. (24) Narayanan, R. L.; Dürr, U. H.; Bibow, S.; Biernat, J.; Mandelkow, E.; Zweckstetter, M. J Am Chem Soc 2010, 132, 11906. (25) Orekhov, V. Y.; Ibraghimov, I. V.; Billeter, M. J Biomol NMR 2001, 20, 49. (26) Jaravine, V. A.; Zhuravleva, A. V.; Permi, P.; Ibraghimov, I.; Orekhov, V. Y. J Am Chem Soc 2008, 130, 3927. (27) Kazimierczuk, K.; Zawadzka, A.; Koźmiński, W. J Magn Reson 2009, 197, 219. (28) Piai, A.; Hošek, T.; Gonnelli, L.; ZawadzkaKazimierczuk, A.; Koźmiński, W.; Brutscher, B.; Bermel, W.; Pierattelli, R.; Felli, I. C. J Biomol NMR 2014, 60, 209. (29) Nováček, J.; Zawadzka-Kazimierczuk, A.; Papoušková, V.; Zídek, L.; Sanderová, H.; Krásný, L.; Koźmiński, W.; Sklenář, V. J Biomol NMR 2011, 50, 1.

Page 4 of 6

(30) Bermel, W.; Bertini, I.; Felli, I. C.; Gonnelli, L.; Koźmiński, W.; Piai, A.; Pierattelli, R.; Stanek, J. J Biomol NMR 2012, 53, 293. (31) Nováček, J.; Janda, L.; Dopitová, R.; Zidek, L.; Sklenář, V. J Biomol NMR 2013, 56, 291. (32) Bermel, W.; Felli, I. C.; Gonnelli, L.; Koźmiński, W.; Piai, A.; Pierattelli, R.; Zawadzka-Kazimierczuk, A. J Biomol NMR 2013, 57, 353. (33) Pantoja-Uceda, D.; Santoro, J. J Biomol NMR 2014, 59, 43. (34) Gil, S.; Hošek, T.; Solyom, Z.; Kümmerle, R.; Brutscher, B.; Pierattelli, R.; Felli, I. C. Angew Chem Int Ed Engl 2013, 52, 11808. (35) Bermel, W.; Bertini, I.; Felli, I. C.; Lee, Y. M.; Luchinat, C.; Pierattelli, R. J Am Chem Soc 2006, 128, 3918. (36) Andreas, L. B.; Stanek, J.; Le Marchand, T.; Bertarello, A.; Cala-De Paepe, D.; Lalli, D.; Krejčíková, M.; Doyen, C.; Öster, C.; Knott, B.; Wegner, S.; Engelke, F.; Felli, I. C.; Pierattelli, R.; Dixon, N. E.; Emsley, L.; Herrmann, T.; Pintacuda, G. J Biomol NMR 2015, 62, 253. (37) Xiang, S.; Grohe, K.; Rovó, P.; Vasa, S. K.; Giller, K.; Becker, S.; Linser, R. J Biomol NMR 2015, 62, 303. (38) Fraga, H.; Arnaud, C. A.; Gauto, D. F.; Audin, M.; Kurauskas, V.; Macek, P.; Krichel, C.; Guan, J. Y.; Boisbouvier, J.; Sprangers, R.; Breyton, C.; Schanda, P. Chemphyschem 2017, 18, 2697. (39) Cavanagh, J.; Palmer, A. G.; Wright, P. E.; Rance, M. J Magn Reson 1991, 91, 429. (40) Palmer, A. G.; Cavanagh, J.; Wright, P. E.; Rance, M. J Magn Reson 1991, 93, 151. (41) Kay, L. E.; Keifer, P.; Saarinen, T. J Am Chem Soc 1992, 114, 10663. (42) Schleucher, J.; Sattler, M.; Griesinger, C. Angew Chem, Int Ed Engl 1993, 32, 1489. (43) Brutscher, B.; Boisbouvier, J.; Pardi, A.; Marion, D.; Simorre, J. P. J Am Chem Soc 1998, 120, 11845. (44) Zhu, G.; Xia, Y.; Sze, K. H.; Yan, X. J Biomol NMR 1999, 14, 377. (45) Kühn, J.; Wong, L. E.; Pirkuliyeva, S.; Schulz, K.; Schwiegk, C.; Fünfgeld, K. G.; Keppler, S.; Batista, F. D.; Urlaub, H.; Habeck, M.; Becker, S.; Griesinger, C.; Wienands, J. Sci Signal 2016, 9, ra66. (46) Grzesiek, S.; Anglister, J.; Ren, H.; Bax, A. J Am Chem Soc 1993, 115, 4369. (47) Support is calculated by GAPRO as the number of subspaces from the projections that intersect at a particular point in the nD spectrum. A real nD peak is likely to have a higher number of supports. (48) Schubert, M.; Smalla, M.; Schmieder, P.; Oschkinat, H. J Magn Reson 1999, 141, 34. (49) Camilloni, C.; De Simone, A.; Vranken, W. F.; Vendruscolo, M. Biochemistry 2012, 51, 2224. (50) Residues M1-D2, G7-K10, G14, S42-K43, G51, and N65 were not assigned since their amide peaks in the 15N-HSQC spectrum were either too weak or not detectable at all. L8 peak was intense but G7 and S9 peaks were almost undetectable. (51) Yoshimura, Y.; Kulminskaya, N. V.; Mulder, F. A. J Biomol NMR 2015, 61, 109. (52) Żerko, S.; Byrski, P.; Włodarczyk-Pruszyński, P.; Górka, M.; Ledolter, K.; Masliah, E.; Konrat, R.; Koźmiński, W. J Biomol NMR 2016, 65, 193. (53) Mäntylahti, S.; Aitio, O.; Hellman, M.; Permi, P. J Biomol NMR 2010, 47, 171. (54) Mäntylahti, S.; Hellman, M.; Permi, P. J Biomol NMR 2011, 49, 99. (55) Yao, X.; Becker, S.; Zweckstetter, M. J Biomol NMR 2014, 60, 231.

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Journal of the American Chemical Society (56) Liu, X.; Yang, D. J Biomol NMR 2013, 57, 83. (57) Hellman, M.; Piirainen, H.; Jaakola, V. P.; Permi, P. J Biomol NMR 2014, 58, 49.

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