Late metabolic precursors for selective aromatic residue labeling

Late metabolic precursors for selective aromatic residue labeling In recent years, we developed a toolbox of heavy isotope containing compounds, which serve as metabolic amino acid precursors in the E. coli-based overexpression of aromatic residue labeled proteins. Our labeling techniques show excellent results both in terms of selectivity and isotope incorporation levels. They are additionally distinguished by low sample pro- duction costs and meet the economic demands to further implement protein NMR spectroscopy as a routinely used method in drug development processes. Different isotopologues allow for the assembly of optimized protein samples, which fulfill the requirements of various NMR experiments to elucidate protein structures, analyze conformational dynamics, or probe interaction surfaces. In the present article, we want to summarize the precursors we developed so far and give examples of their special value in the probing of protein–ligand interaction. Keywords Protein labeling · Aromatic residues · Protein overexpression · Chemical shift mapping · Ligand induced cross- correlation · Intrinsically disordered proteins Introduction given by the highly diverse set of possible pulse sequences, which can give information about structural properties, The structure and interplay of proteins determine the cell’s dynamic processes and the interaction with binding partners. proliferation, development, function and fate. A deep under- This information can be obtained under near native condi- standing of their complex conformational properties and tions from samples in aqueous buffer solution. However, the interaction networks represents the key issue to unravel the NMR-based elucidation of proteins is limited by sensitiv- principles of life at a molecular level. Only if the proper- ity and resolution issues (Ardenkjaer-Larsen et al. 2015), ties of the single nodes in e.g. protein signal cascades or which are partly compensated by constant improvement of metabolic networks are known and the interaction mecha- experimental techniques, hardware development and sample nisms understood, subtle changes leading to pathogenic preparation (Campbell 2013), especially concerning novel progression and disease development can be addressed by developments in protein isotope labeling techniques (Ohki developing non-endogenous therapeutic compounds. NMR and Kainosho 2008). 13 15 2 spectroscopy is one of the three main methods, next to X-ray Introducing C, N and H at defined atomic posi- diffraction and cryo-electron microscopy, to investigate the tions improves signal resolution and leads to spectra sim- properties of proteins at an atomic, or near-atomic resolu- plification. As a result, NMR signals are attributed to the tion (Banci et al. 2010). The special value of protein NMR is corresponding nuclei more easily and can be transferred to automated assignment algorithms (Güntert 2009). Highly selective labeling shifts the molecular weight limit of pro- * Roman J. Lichtenecker teins which are amenable to structure calculation based on roman.lichtenecker@univie.ac.at NMR data. The number of high quality structure restraints Institute of Organic Chemistry, University of Vienna, can be increased in this case resulting in more accurate Währinger Str. 38, 1090 Vienna, Austria protein structures. Furthermore, most of the diverse NMR Christian Doppler Laboratory for High-Content Structural experiments, which have been developed to probe protein Biology and Biotechnology, Department of Structural dynamics at different time scales require isolated spin sys - and Computational Biology, Max F. Perutz Laboratories, 13 1 tems (Ishima et al. 2001). The analysis of these C– H or University of Vienna, Dr-Bohr-Gasse 9, 1030 Vienna, Austria Vol.:(0123456789) 1 3 130 Journal of Biomolecular NMR (2018) 71:129–140 15 1 N– H spin pairs is greatly simplified due to the lack of addition, these residues are significantly overrepresented 13 13 13 1 one-bond C– C or three-bond C– H coupling, and thus at protein interfaces and play a prominent role in guiding allows for an accurate interpretation of the corresponding enzyme mechanisms (Bogan and Thorn 1998). The absence relaxation dispersion rates. The importance of protein NMR of a comprehensive toolbox of amino acid precursors for in the drug development process is constantly increasing as selective aromatic residue isotope labeling inspired us to this method provides valuable information about binding identify novel compounds, which show effective cell-uptake sites and large interaction surfaces (Pellecchia et al. 2002). and well-defined in-vivo conversion to the target residues in However, protein NMR is associated with high costs and E. coli overexpression systems. still far from being a high throughput method. Highly selec- tive, economic protein labeling can improve the situation by decreasing the minimal sample concentrations required for Precursor identification certain NMR experiments. Two main complementary methods have been developed Early metabolic precursors (biosynthetic intermediates to implement defined protein isotope patterns. In cell-based upstream of the shikimate- or the pentose phosphate path- approaches, a host organism is grown in media containing way) have been applied to achieve a certain isotope distribu- suitable isotopologues of metabolic amino acid precursors. tion in the corresponding target residues. Isotopologues of After cellular uptake, these compounds are converted into d -glucose (Teilum et al. 2006; Lundström et al. 2007, 2009a, the target residues within their metabolic pathways in- b; Weininger et al. 2012a, 2013), glycerol (Ahlner et al. vivo. Such overexpression systems have been described for 2015; LeMaster and Kushlan 1996; Takeuchi et al. 2008), prokaryotic (E. coli) (Hoogstraten and Johnson 2008; Mon- d -erythrose (Kasinath et al. 2013, 2015; Weininger 2017b), dal et al. 2013), as well as eukaryotic cells (yeast, insect cell- d -ribose (Weininger 2017a), acetate (Wand et al. 1995) and lines) (Morgan et al. 2000; Takahashi and Shimada 2010). pyruvate (Guo et al. 2009; Lee et al. 1997; Lundström et al. Especially when early metabolic intermediates are used as 2008; Milbradt et al. 2015; Robson et al. 2018) have been labeled nutrients, the danger of cross-labeling to unwanted particularly used to reduce unwanted J coupling in NMR- CC positions is very high, thus resulting in unselective isotope based analysis of protein dynamics. These methods have patterns. Cross-labeling is avoided in the second method, been frequently applied by the biomolecular NMR commu- which uses cell lysates in-vitro to generate the target pro- nity, since the corresponding precursors are commercially teins from isotope containing amino acids (Kainosho et al. available and additional synthetic organic chemistry is not 2006; Kainosho and Güntert 2009; Staunton et al. 2006; needed. However, a significant degree of cross-labeling can- Takeda et al. 2010; Torizawa et al. 2004, 2005). These cell- not be avoided when using early metabolic precursors, which free methods lead to very selective labeling patterns, but not only leads to heavy isotope incorporation at unwanted their use is often still hampered by high costs and limited atomic positions, but also results in labeling of others than applicability (Casteleijn et al. 2013). the target amino acids. Since the compounds mentioned The introduction of late α-ketoacid metabolic precur- above are central to the biosynthesis of all four proteinogenic sors for valine, isoleucine and leucine (Gardner and Kay aromatic residues, generating residue-selective isotope pat- 1998; Goto et al. 1999; Lichtenecker et al. 2004, 2013a, terns is impossible. In addition, the poor selectivity causes b), as well as methionine (Fischer et al. 2007) resulted in limited maximal isotope incorporation levels, which is to hitherto unrivaled labeling selectivity in cell-based protein some extent compensated by supplying increased precursor overexpression. Further development led to techniques of concentrations in the overexpression media. The resulting stereoselective methyl labeling in leucine, valine or iso- high consumption rate of isotope labeled compounds is a leucine (Ayala et al. 2012; Gans et al. 2010) and extended serious expense factor and limits the sample throughput of selective labeling to alanine and threonine (Ayala et  al. protein NMR spectroscopy. 2009; Velyvis et al. 2012). The assembly of CHD methyl In order to address the issues mentioned above, we iden- groups (Chaykovski et al. 2003; Ollerenshaw et al. 2005; tified late metabolic precursors for aromatic residue labe- Weininger et al. 2012b) provides optimized isotope patterns ling. Phenylpyruvate and (4-hydroxyphenyl)pyruvate are to probe for conformational changes. Compared to all these the substrates of the transaminase catalyzed conversion to advanced techniques of aliphatic residue labeling (reviewed the corresponding target amino acids l -phenylalanine and by Kerfah et al. 2015), the methods to introduce defined l -tyrosine, respectively (Scheme  1) (Lichtenecker et  al. isotope patterns into aromatic residues extensively lagged 2013c). These two compounds represent the only non-chiral behind for many years. This is all the more surprising, intermediates in the corresponding biosynthetic pathway and because phenylalanine, tyrosine, tryptophan and histidine are thus ideal structurally simple targets for isotopologue are regarded as sensitive reporters of protein dynamics, as synthesis (Lichtenecker 2014). The α-ketoacid derivative well as being valuable sources of structural restraints. In of tryptophan, indolepyruvate, is not part of the amino acid 1 3 Journal of Biomolecular NMR (2018) 71:129–140 131 biosynthesis, but the first intermediate in the correspond- Precursor synthesis ing degradation pathway. However, we could identify this compound as a selective precursor for tryptophan labeling Scheme 2 summarizes the precursors we used for aromatic (Schörghuber et al. 2015). The reversible character of the residue labeling so far. These compounds have been prepared corresponding transaminase EC 2.6.1.27 reaction leads to via multistep organic synthesis, which we optimized in terms efficient conversion of the precursor to the target residue of robustness, yields, labeling selectivity and costs (see the in this case. In order to access isotopologues of the indole corresponding literature for details). We used commercially side-chain, we tested structurally more simple compounds available sources of C as starting materials or reagents, for their use in selective tryptophan labeling. Considering such as isotopologues of acetone, glycine, potassium cya- the irreversibility of the anthranilate synthase EC 4.1.3.27 nide and formaldehyde (Lichtenecker 2014; Lichtenecker catalyzed elimination of pyruvate from chorismate, we could et  al. 2015). Deuterium patterns have been exclusively provide evidence that isotope patterns in anthranilate, as well derived from deuterium oxide, which is the cheapest source 2 13 as indole can be transferred to the tryptophan side-chain of H available. 1- C labeled precursors 1, 4, 6 and 14 have without losing heavy isotopes in the shikimate pathway been applied to probe for labeling selectivity and precur- (Schörghuber et al. 2015, 2017a). Regarding histidine labe- sor uptake in diverse model protein overexpression systems. ling, we focused on the first intermediate of the minor deg- Their straightforward synthesis (1, 4 and 6 are prepared from radation pathway, imidazolepyruvate. Again, the reversible [1- C]glycine in three steps) renders them economic tools transaminase EC 2.6.1.38 reaction ensured an effective in- for residue-selective backbone-labeling to be used for e.g. vivo conversion to the target residue. In this case we applied unambiguous signal assignment in high molecular-weight the stable enol-tautomer of imidazolepyruvate as a labeling protein complexes. precursor (Schörghuber et al. 2017b). All of the identified The Phe-precursors 2 and 3, the Tyr-precursor 5, as precursor compounds mentioned showed highly selective well as the Trp-precursors 9, 10, 12 and 13 display well- 13 1 labeling of the corresponding target residues in absence of defined deuteration patterns leading to isolated C– H any cross-labeling to undesired atomic positions. spins. These systems are devoid of any additional scalar couplings, which otherwise distort relaxation rate analy- 1 2 sis. Highly regioselective H/ H exchange was performed on electron-rich aromatic rings in acidic deuterium oxide shikimate COO pathway glycolysis D-erythrose EC 4.1.3.27 NH chorismate D-glucose + pyruvate pentosephosphate- EC 5.4.99.5 pathway anthranilate indole D-ribose-5- prephenate EC 4.2.1.20 phosphate EC 1.3.1.12 EC 4.2.1.51 L-tryptophan EC 2.6.1.38 COO - - COO COO L-histidine EC 2.6.1.27 EC 4.3.1.3 HO COO (4-hydroxyphenyl) urocanate phenylpyruvate imidazolepyruvate pyruvate EC 2.6.1.58 EC 2.6.1.5 indolepyruvate L-phenylalanine L-tyrosine L-glutamate His-pathway Trp-pathway Phe- and Tyr-pathway Scheme 1 Outline of the aromatic amino acid metabolism in E. coli 1 3 phenylalanine tyrosine labelling tryptophan labelling histidinelabelling labelling 132 Journal of Biomolecular NMR (2018) 71:129–140 Scheme 2 Late metabolic pre- O O cursor compounds for aromatic D D [1- C]glycine - - 2 2 residue labeling. Commercially COO H O COO H O 2 2 D D 13 - COO available isotope sources are D D D D denoted in grey italics 13 13 C C H H D C D [2- C]acetone [1,3- C ]acetone D H 1 2 3 O O [1- C]glycine COO 13 - COO H O D D 13 13 C C H H [1,3- C ]acetone OH 2 OH [1,3- C ]acetone [1- C]glycine [ C]potassium- cyanide H 13 - COO D C N N [ N]ammonium- H H D chloride H O 6 89 [ N]ammonium- chloride 2 2 - - H O H O - 2 COO 2 COO COO 15 + H H + + NH NH 3 D NH 13 13 3 H O 2 C N 13 D C D H H 13 13 [2- C]acetone H [1,3- C ]acetone [2- C]acetone H 2 H D 10 11 12 13 OH 13 OH [1- C]glycine 13 - COO COO [ C]formaldehyde HN HN C under elevated reaction temperatures. All these com- Precursor uptake and labeling selectivity pounds can be accessed from one common synthetic intermediate (isotopologues of 4-nitrophenol 17 and 19), Effective uptake of isotope labeled precursors by the overex- which is a significant advantage from an economic point pressing organism is of utmost importance, since this factor of view (Scheme 3). Labeled histidines are important sen- determines the highest possible isotope incorporation level at sors for protein dynamics and help to elucidate the pK certain precursor concentrations in the corresponding media. values of the imidazole ring (Hansen and Kay 2014; Hass Isotope incorporation at a given concentration may vary with et al. 2008). The ε- C His-precursor 15 exhibits an inher- different target proteins as a function of protein size, number 13 1 ently isolated C– H spin system and was developed to of target residues and overexpression conditions. We identi- provide an optimal isotope pattern to probe this unique fied the following precursor concentrations as being required heteroaromatic side-chain. Compound 15 can be prepared in the E.coli overexpression media to achieve near-quantita- via a straightforward 5-step route starting from [ C]for- tive to quantitative isotope incorporation at the target atomic maldehyde (Schörghuber et al. 2017b). positions: 60–150  mg/L phenylpyruvate, 80–200  mg/L 1 3 Journal of Biomolecular NMR (2018) 71:129–140 133 Scheme 3 Synthesis of Phe-, 7 steps 8 steps 25% 21% Tyr- and Trp-precursors via the common synthetic intermedi- ates [2,6- C ]4-nitrophenol 16 6 steps nitromalon- nitromalon- and [1- C]4-nitrophenol 19. NO NO 43% aldehyde, aldehyde, 6 steps For more details concerning O NaOH, 65% O NaOH, 65% 32% synthetic routes and concepts, 13 10 5 steps 13 13 see the corresponding literature 13 C C H C 29% 3 13 CH 3 H H (Lichtenecker 2014; Schörghu- ber et al. 2015, 2017a) OH OH 17 19 6 steps 8 steps 39% 27% 4-hydroxyphenylpyruvate (Lichtenecker et  al. 2013c), Miyanoiri et al. 2011; Vuister et al. 1994). The concentra- 20–60 mg/L indolepyruvate, 12–30 mg/L indole (Schörghu- tions required can even be further decreased when using ber et al. 2015), 8–30 mg/L anthranilic acid (Schörghuber auxotrophic expression strains (Lin et al. 2011; Yang et al. et al. 2017a), and 50–100 mg/L imidazolepyruvate (Schör- 2015). Other reports indicate that the use of labeled amino ghuber et al. 2017b). This data has been deduced from labe- acids in E. coli-based overexpression systems is to some ling efficiency plots, which were obtained by overexpressing extent limited by metabolic product feedback control mecha- the corresponding protein sample in presence of different nisms, which may lead to decreased isotope uptake, retarded precursor concentrations. The low amount of late metabolic cell growth or cross-labeling (Krishnarjuna et  al. 2011; precursors required to achieve maximal heavy isotope con- O’Grady et al. 2012; Rowley 1953). In the case of aromatic tents is in sharp contrast to labeling methods using early residues, Phe, Tyr and Trp have shown to inhibit the E. coli metabolic intermediates. Examples from literature report DHAP synthase isoenzymes, which control the carbon flow concentrations of 1–4 g/L in this case, leading to isotope into the shikimate pathway (Herrmann 1995). Additionally, enrichment of 30–75% at the desired atomic positions in certain levels of amino acid concentrations affect the transla- Phe, Tyr, Trp or His-residues (e.g. Kasinath et al. 2013; Wei- tion machinery, thereby slowing down growth rates (Avci- ninger 2017b). These values are far from the quantitative lar-Kucukgoze et al. 2016). Besides, organic synthesis of isotope labeling, which we observed when applying the late complex isotope patterns in the case of amino acids is con- metabolic precursor compounds illustrated in Scheme 2. siderably elaborate and expensive, due to the required imple- Using single atom C-labeled early metabolic precursors mentation of at least one center of chirality, as well as the 12 13 15 induces a certain pattern of C/ C isotopes, but despite of need of introducing N by additional synthetic steps if nitro- improving selectivity by exploiting auxotrophic organisms gen-15 labeling is desired (Miyanoiri et al. 2011). In contrast (e.g. LeMaster and Kushlan 1996) or supplying the growth to that, N-labeling of the target residues is straightforward media with enzyme inhibitors (e.g. Tong et al. 2008) a cer- in the case of applying metabolic amino acid precursors by tain degree of cross-labeling cannot be ruled out. In various adding N-salts to the expression media. In order to reduce applications of our precursor toolbox, we did not observe synthetic efforts, more elaborate commercially available any isotope scrambling so far. Our experiments indicate isotope sources can be applied. Phenylalanine, for instance, that any isotope pattern, which can be implemented onto the has been prepared from labeled tyrosine in two steps (Wang structures shown in Scheme 2 will quantitatively be trans- et al. 1999). The simplified synthesis, however, comes along ferred to the corresponding target residue. Most importantly, with increased costs for the starting compound. In a recently this is also true for patterns of (non-solvent exchangeable) published noteworthy economic approach, labeled phenyla- deuterium atoms. Consequently, late metabolic precursors lanine was produced in E. coli from glycerol and secreted of aromatic residues can be applied to introduce aromatic into the growth medium. The thus isolated amino acid sub- ring protons into protein samples with high overall deute- sequently served as an isotope source in recombinant E. coli rium levels. In this case, uniform deuterium labeling can be protein overexpression (Ramaraju et al. 2017). However, achieved using deuterium oxide together with H-containing the application of amino acids in cell-based overexpression early metabolic isotope sources such as [all- H]glucose. required the addition of metabolic inhibitors and unlabeled Another strategy to achieve well-defined isotope patterns amino acids in order to obtain high isotope incorporation in protein samples applies labeled amino acids as additives levels also in this case. One literature reported protocol to the overexpression media. Examples from literature show makes use of shikimic acid to generate protonated aromatic that amino acid concentrations in the low mg/L range may residues in an otherwise uniformly C-protein (Rajesh et al. result in high incorporation levels (Kemple et  al. 1994; 2003). It can be considered as rather improbable that this 1 3 134 Journal of Biomolecular NMR (2018) 71:129–140 strategy will be transferred from reverse-labeling to selec- originate from residues in close contact to the binding site tive C-labeling in aromatic residues in future, due to the (Tyr97, Tyr139 and Trp81). The third shifting tyrosine reso- required synthesis of C-shikimic acid. nance is very likely caused by Tyr98, which is in close con- Table 1 gives a -by no means exhaustive- overview con- tact to Tyr97 and thus also influenced by ligand binding. cerning the various strategies of aromatic residue labeling Importantly, strong CSPs in the proton dimension of selec- in E. coli based and cell-free systems published so far. The tively labeled sites provide crucial information about the data shown shall illustrate the differences in selectivity, pre- proximity of aromatic ring-systems of interacting ligands. cursor concentrations needed, synthetic effort and isotope CSPs induced in the tryptophan spectrum (Fig. 2a) show incorporation levels. only marginal differences between the three tested ligands. Only one of the compounds induces a strong upfield shift in the proton dimension of the η2-position of Trp81, indicating Applying late metabolic aromatic precursor a binding mode, which places an aromatic ring-system on η2 compounds to investigate proteins and their top of H (Fig. 2a, magenta spectrum). interaction sites Ligand induced cross‑correlation rates Chemical shift mapping In additional experiments, we employed selective Trp 13 ε3 13 η2 We chose bromodomain 1 of bromodomain-containing pro- C / C labeling on Brd4-BD1 to evaluate the effect tein 4 (Brd4-BD1) as an example to highlight the benefits of different ligands on the Chemical Shift Anisotropy of labeling isolated positions in aromatic side-chains. Brd4 (CSA)–Dipol-Dipol (DD) cross correlation rate (CCR) η of is a chromatin reader that binds to acetylated lysines in his- the labeled carbon nuclei. As mentioned before, the Brd4- tones and has proven to be a promising cancer target in the BD1 system comprises three tryptophans, one of which pharmaceutical industry (Zeng and Zhou 2002; Sanchez (Trp81) is embedded in a hydrophobic pocket that is targeted et al. 2014). We already described Trp-labeled Brd4-BD1 by various inhibitor molecules (Jung et al. 2014). Cross cor- in previous work (Schörghuber et al. 2017a), and we want relation between CSA and DD interactions in a system of to elaborate on the application of selective aromatic labe- coupled 1/2 spins can yield valuable information about local ling for probing ligand interaction further using this system. electronic structure and dynamics (Brutscher 2000; Kumar 1 13 Figure 1 compares the H– C HSQC spectrum of uniformly et al. 2000). Therefore, we chose precursor 12 to generate 13 13 ε3 1 13 η2 1 C-labeled Brd4-BD1 (Fig. 1a) with the spectra of either exclusive C – H/ C – H spin pairs in the target residues. 13 ε3 13 η2 13 ε Trp( C / C )- or Tyr( C )-labeled Brd4-BD1 (Fig. 1b, This pattern eliminates scalar coupling contributions from ζ2 ζ3 blue and red spectrum). Figure 1b shows six tryptophan- and nearby C –H and C –H pairs. In order to calculate CCRs 13 ε3 13 η2 ε3 η2 seven tyrosine resonances according to the three C / C -for Trp81 and Trp81 we utilized a coupled version of a 13 ε 1 13 labeled tryptophans, as well as the seven C -labeled tyros- constant time H– C HSQC to extract peak intensities for ines present in the Brd4-BD1 sequence. All the signals are the upfield (I ) and downfield (I ) components of the C + − well-defined and devoid of any splitting due to additional doublets, which allows for the calculation of correspond- scalar couplings. On the contrary, the tryptophan resonances ing cross-correlation rates. Figure 3 displays the twelve sig- of the uniformly labeled sample barely exceed the noise nals that emanate from the three tryptophan residues pre- ε3 threshold and all aromatic side-chain signals are affected by sent. Highlighted are the 1D slices for both Trp81C and η2 strong J couplings to neighboring positions. Especially Trp81C showing the upfield (+) components in red, and CC the Tyr-signals suffer from substantial signal overlap, which the downfield (−) components in blue. The ratio of peak severely restricts their use for ligand induced chemical shift intensities (I /I ) is related to the CCR (η) via ln(I /I ) = 2Tη + − + − perturbation studies. where T is the mixing time in the NMR experiment during Figure  2 illustrates the chemical shift perturbations which cross correlated relaxation is active (Brutscher 2000). (CSPs), which have been induced by three different ligands Figure 4 shows 2D spectra and extracted 1D traces in the 1 13 13 ε3 13 η2 in H– C HSQC spectra of Trp( C / C )-labeled Brd4- presence of a small molecule ligand and their corresponding 13 ε ε3 η2 BD1 (Fig. 2a) and Tyr( C )-labeled Brd4-BD1 (Fig. 2b). η values. CCR rates for T rp81 and T rp81 were deter- −1 The corresponding protein samples were overexpressed in mined to 46.5 and 50.2 s . Interestingly, these rates were ε3 −1 E. coli using precursor 12 (20 mg/L medium), or precursor smaller than in the apo-state of BRD4 (T rp81 : 50.8 s ; η2 −1 5 (100 mg/L medium) containing minimal medium, respec- Trp81 : 53.3 s ) presumably due to subtle changes of the tively. The low-molecular weight ligands added target the CSA tensor and/or local conformational dynamics. binding cleft of Brd4-BD1, which is lined by one tryptophan (Trp81) as well as two tyrosine residues (Tyr97 and Tyr139). The spectra reveal that the only resonances to be affected 1 3 Journal of Biomolecular NMR (2018) 71:129–140 135 Table 1 Overview of published protocols concerning aromatic residue protein labeling n.d. no data available, prec. conc. precursor concentration, prot. prec. protonated precursor, bact. prod. bacterial production, com. sup. commer- cial suppliers, amino acids are depicted by one letter code Expression in a succinate dehydrogenase deficient E. coli strain Together with 2 g/L deuterated pyruvate c 13 Additional supply of N aH CO Reverse labeling using protonated precursor e 13 Overexpressing organism lacks succinate- and malate dehydrogenase; addition of NaH CO f 13 Incorporation rates can be maximized to 75% by addition of C-isotopologues of glucose Application of a shikimate auxotroph h 13 Precursor produced in E. coli medium containing [2- C]glycerol Addition of glyphosate and unlabeled amino acids to prevent cross labeling and increase precursor uptake Synthesized from labeled tyrosine For the exact isotopic patterns of these precursors see the literature cited An auxotrophic overexpression host was used 1 3 136 Journal of Biomolecular NMR (2018) 71:129–140 1 13 Fig. 1 a H– C HSQC spec- (a) (b) trum of uniformly C-labeled 1 13 Brd4-BD1. b H– C HSQC spectra of selectively 13 ε3 13 η2 Trp( C / C ) (blue) and 13 ε Tyr( C ) (red) labeled Brd4- BD1. Samples were expressed and purified as described before (Schörghuber et al. 2017a). Spectra were acquired on a 600 MHz spectrometer at 298 K on a sample of 0.1 mM protein concentration at pH 7.5 1 13 Fig. 2 CSPs observed in H- C HSQC spectra of selectively magenta spectra). The binding cleft of Brd4-BD1 is shown (red 13 ε3 13 η2 13 ε Trp( C / C )-labeled Brd4-BD1 (a) and Tyr( C )-labeled Brd4- arrow) highlighting the proximal Tyrosine (Tyr97, Tyr98, Tyr139) BD1 (b) after the addition of three different ligands (red, blue and and Tryptophan residues (Trp81) (c) development (Zhang et al. 2015). The acquisition of struc- Structural restraints in intrinsically disordered proteins tural restraints to identify potential preformation of specific secondary structure elements in the unbound state, as well Highly selective aromatic residue labeling holds promise as their conformational stabilization upon ligand binding, is however still a very challenging task (Konrat 2014). Figure 5 to yield valuable additional distance information through well-defined NOE signals, even in the case of structurally shows a C-NOESY-HSQC strip of an intrinsically disor- dered N-terminal fragment (residues 50-171) of Yes-asso- flexible protein regions or intrinsically disordered pro- teins (IDPs). Various research groups are just beginning to ciated protein (YAP). This region was identified to contain the binding site to the transcription factor TEAD (Vassilev explore the potential of IDPs as important targets in drug 1 3 Journal of Biomolecular NMR (2018) 71:129–140 137 Fig. 5 Left A strip from a C-NOESY-HSQC spectrum of the uniformly N and selec- tively phenylalanine labeled IDP YAP (50-171). The strip is assigned to Phe95/96-H and exhibits NOEs to Leu91-H and Leu91-H . Right A strip from a N-NOESY-HSQC of the same protein assigned to Leu91-H . Spectra were aquired at 800 MHz, 298 K on a sample of 1.0 mM protein concentration 13 15 at pH 6. C and N chemical shifts are indicated in the top region of the slices 1 13 Fig. 3 Coupled H– C HSQC spectrum of selectively 13 ε3 13 η2 Trp( C / C )-labeled Brd4-BD1 with 1D slices for Trp81 down- field (blue) and upfield (red) components. Samples were prepared and measured as denoted in Fig. 1 et al. 2001). The YAP/TEAD interaction regulates the Hippo pathway, which is deregulated in various cancers and there- fore represents a promising target for cancer therapy (Liu et al. 2012). A recent study indicates propensities for the preformation of an α-helix and an N-terminal β-strand in YAP50-171 in its unbound state (Feichtinger et al. 2018). These partially preformed secondary structural elements, together with an omega-loop (residues 86-100), form the interacting surface upon TEAD binding. For the omega- loop, no structural preformation was anticipated so far. In order to further investigate the potential preformation of cer- tain structural elements in this IDP, a uniformly N-YAP 50-171 sample was additionally labeled using compound 3 in the corresponding growth medium. Significant long-range ε3 Fig. 4 Overlay of the up- and downfield slices extracted for Trp81C ς γ (side-chain) NOEs between Phe95/96-H and Leu91-H η2 (top) and Trp81C (bottom) in the presence of Ligand 1 with their and Leu91-H were observed (Fig. 5). This data shows that, corresponding η values. Samples were prepared and measured as denoted in Fig. 1 although YAP is largely unfolded in absence of its binding partner, very selective labeling can identify direct distance 1 3 138 Journal of Biomolecular NMR (2018) 71:129–140 Economy and the National Foundation for Research, Technology and proximities and thus long-range structural preformation of Development is gratefully acknowledged. the Ω-loop region (residues 86-100). This property was not perceived by analyzing chemical shift data via secondary Open Access This article is distributed under the terms of the Crea- structure propensity score calculation (Marsh et al. 2006) in tive Commons Attribution 4.0 International License (http://creat iveco previous studies (Feichtinger et al. 2018). mmons.or g/licenses/b y/4.0/), which permits unrestricted use, distribu- tion, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Conclusion To conclude this article, we want to summarize the various reasons, which make us think that our ensemble of heavy References isotope containing aromatic compounds can be consid- Ahlner A, Andresen C, Khan SN, Kay LE, Lundström P (2015) Frac- ered as a valuable tool for the NMR-based investigation of tional enrichment of proteins using [2- C]-glycerol as the car- structure and dynamics in different proteins, as well as the bon source facilitates measurement of excited state Cα chemical NMR-guided drug development process. The use of meta- shifts with improved sensitivity. J Biomol NMR 62:341–351 bolic amino acid precursors downstream of the shikimic acid Ardenkjaer-Larsen JH, Boebinger GS, Comment A, Duckett S, Edi- son AS, Engelke F, Griesinger C, Griffin RG, Hilty C, Maeda H, pathway ensures for highly selective labeling with maximum Parigi G, Prisner T, Ravera E, van Bentum J, Vega S, Webb A, incorporation rates. 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Abstract

In recent years, we developed a toolbox of heavy isotope containing compounds, which serve as metabolic amino acid precursors in the E. coli-based overexpression of aromatic residue labeled proteins. Our labeling techniques show excellent results both in terms of selectivity and isotope incorporation levels. They are additionally distinguished by low sample pro- duction costs and meet the economic demands to further implement protein NMR spectroscopy as a routinely used method in drug development processes. Different isotopologues allow for the assembly of optimized protein samples, which fulfill the requirements of various NMR experiments to elucidate protein structures, analyze conformational dynamics, or probe interaction surfaces. In the present article, we want to summarize the precursors we developed so far and give examples of their special value in the probing of protein–ligand interaction. Keywords Protein labeling · Aromatic residues · Protein overexpression · Chemical shift mapping · Ligand induced cross- correlation · Intrinsically disordered proteins Introduction given by the highly diverse set of possible pulse sequences, which can give information about structural properties, The structure and interplay of proteins determine the cell’s dynamic processes and the interaction with binding partners. proliferation, development, function and fate. A deep under- This information can be obtained under near native condi- standing of their complex conformational properties and tions from samples in aqueous buffer solution. However, the interaction networks represents the key issue to unravel the NMR-based elucidation of proteins is limited by sensitiv- principles of life at a molecular level. Only if the proper- ity and resolution issues (Ardenkjaer-Larsen et al. 2015), ties of the single nodes in e.g. protein signal cascades or which are partly compensated by constant improvement of metabolic networks are known and the interaction mecha- experimental techniques, hardware development and sample nisms understood, subtle changes leading to pathogenic preparation (Campbell 2013), especially concerning novel progression and disease development can be addressed by developments in protein isotope labeling techniques (Ohki developing non-endogenous therapeutic compounds. NMR and Kainosho 2008). 13 15 2 spectroscopy is one of the three main methods, next to X-ray Introducing C, N and H at defined atomic posi- diffraction and cryo-electron microscopy, to investigate the tions improves signal resolution and leads to spectra sim- properties of proteins at an atomic, or near-atomic resolu- plification. As a result, NMR signals are attributed to the tion (Banci et al. 2010). The special value of protein NMR is corresponding nuclei more easily and can be transferred to automated assignment algorithms (Güntert 2009). Highly selective labeling shifts the molecular weight limit of pro- * Roman J. Lichtenecker teins which are amenable to structure calculation based on roman.lichtenecker@univie.ac.at NMR data. The number of high quality structure restraints Institute of Organic Chemistry, University of Vienna, can be increased in this case resulting in more accurate Währinger Str. 38, 1090 Vienna, Austria protein structures. Furthermore, most of the diverse NMR Christian Doppler Laboratory for High-Content Structural experiments, which have been developed to probe protein Biology and Biotechnology, Department of Structural dynamics at different time scales require isolated spin sys - and Computational Biology, Max F. Perutz Laboratories, 13 1 tems (Ishima et al. 2001). The analysis of these C– H or University of Vienna, Dr-Bohr-Gasse 9, 1030 Vienna, Austria Vol.:(0123456789) 1 3 130 Journal of Biomolecular NMR (2018) 71:129–140 15 1 N– H spin pairs is greatly simplified due to the lack of addition, these residues are significantly overrepresented 13 13 13 1 one-bond C– C or three-bond C– H coupling, and thus at protein interfaces and play a prominent role in guiding allows for an accurate interpretation of the corresponding enzyme mechanisms (Bogan and Thorn 1998). The absence relaxation dispersion rates. The importance of protein NMR of a comprehensive toolbox of amino acid precursors for in the drug development process is constantly increasing as selective aromatic residue isotope labeling inspired us to this method provides valuable information about binding identify novel compounds, which show effective cell-uptake sites and large interaction surfaces (Pellecchia et al. 2002). and well-defined in-vivo conversion to the target residues in However, protein NMR is associated with high costs and E. coli overexpression systems. still far from being a high throughput method. Highly selec- tive, economic protein labeling can improve the situation by decreasing the minimal sample concentrations required for Precursor identification certain NMR experiments. Two main complementary methods have been developed Early metabolic precursors (biosynthetic intermediates to implement defined protein isotope patterns. In cell-based upstream of the shikimate- or the pentose phosphate path- approaches, a host organism is grown in media containing way) have been applied to achieve a certain isotope distribu- suitable isotopologues of metabolic amino acid precursors. tion in the corresponding target residues. Isotopologues of After cellular uptake, these compounds are converted into d -glucose (Teilum et al. 2006; Lundström et al. 2007, 2009a, the target residues within their metabolic pathways in- b; Weininger et al. 2012a, 2013), glycerol (Ahlner et al. vivo. Such overexpression systems have been described for 2015; LeMaster and Kushlan 1996; Takeuchi et al. 2008), prokaryotic (E. coli) (Hoogstraten and Johnson 2008; Mon- d -erythrose (Kasinath et al. 2013, 2015; Weininger 2017b), dal et al. 2013), as well as eukaryotic cells (yeast, insect cell- d -ribose (Weininger 2017a), acetate (Wand et al. 1995) and lines) (Morgan et al. 2000; Takahashi and Shimada 2010). pyruvate (Guo et al. 2009; Lee et al. 1997; Lundström et al. Especially when early metabolic intermediates are used as 2008; Milbradt et al. 2015; Robson et al. 2018) have been labeled nutrients, the danger of cross-labeling to unwanted particularly used to reduce unwanted J coupling in NMR- CC positions is very high, thus resulting in unselective isotope based analysis of protein dynamics. These methods have patterns. Cross-labeling is avoided in the second method, been frequently applied by the biomolecular NMR commu- which uses cell lysates in-vitro to generate the target pro- nity, since the corresponding precursors are commercially teins from isotope containing amino acids (Kainosho et al. available and additional synthetic organic chemistry is not 2006; Kainosho and Güntert 2009; Staunton et al. 2006; needed. However, a significant degree of cross-labeling can- Takeda et al. 2010; Torizawa et al. 2004, 2005). These cell- not be avoided when using early metabolic precursors, which free methods lead to very selective labeling patterns, but not only leads to heavy isotope incorporation at unwanted their use is often still hampered by high costs and limited atomic positions, but also results in labeling of others than applicability (Casteleijn et al. 2013). the target amino acids. Since the compounds mentioned The introduction of late α-ketoacid metabolic precur- above are central to the biosynthesis of all four proteinogenic sors for valine, isoleucine and leucine (Gardner and Kay aromatic residues, generating residue-selective isotope pat- 1998; Goto et al. 1999; Lichtenecker et al. 2004, 2013a, terns is impossible. In addition, the poor selectivity causes b), as well as methionine (Fischer et al. 2007) resulted in limited maximal isotope incorporation levels, which is to hitherto unrivaled labeling selectivity in cell-based protein some extent compensated by supplying increased precursor overexpression. Further development led to techniques of concentrations in the overexpression media. The resulting stereoselective methyl labeling in leucine, valine or iso- high consumption rate of isotope labeled compounds is a leucine (Ayala et al. 2012; Gans et al. 2010) and extended serious expense factor and limits the sample throughput of selective labeling to alanine and threonine (Ayala et  al. protein NMR spectroscopy. 2009; Velyvis et al. 2012). The assembly of CHD methyl In order to address the issues mentioned above, we iden- groups (Chaykovski et al. 2003; Ollerenshaw et al. 2005; tified late metabolic precursors for aromatic residue labe- Weininger et al. 2012b) provides optimized isotope patterns ling. Phenylpyruvate and (4-hydroxyphenyl)pyruvate are to probe for conformational changes. Compared to all these the substrates of the transaminase catalyzed conversion to advanced techniques of aliphatic residue labeling (reviewed the corresponding target amino acids l -phenylalanine and by Kerfah et al. 2015), the methods to introduce defined l -tyrosine, respectively (Scheme  1) (Lichtenecker et  al. isotope patterns into aromatic residues extensively lagged 2013c). These two compounds represent the only non-chiral behind for many years. This is all the more surprising, intermediates in the corresponding biosynthetic pathway and because phenylalanine, tyrosine, tryptophan and histidine are thus ideal structurally simple targets for isotopologue are regarded as sensitive reporters of protein dynamics, as synthesis (Lichtenecker 2014). The α-ketoacid derivative well as being valuable sources of structural restraints. In of tryptophan, indolepyruvate, is not part of the amino acid 1 3 Journal of Biomolecular NMR (2018) 71:129–140 131 biosynthesis, but the first intermediate in the correspond- Precursor synthesis ing degradation pathway. However, we could identify this compound as a selective precursor for tryptophan labeling Scheme 2 summarizes the precursors we used for aromatic (Schörghuber et al. 2015). The reversible character of the residue labeling so far. These compounds have been prepared corresponding transaminase EC 2.6.1.27 reaction leads to via multistep organic synthesis, which we optimized in terms efficient conversion of the precursor to the target residue of robustness, yields, labeling selectivity and costs (see the in this case. In order to access isotopologues of the indole corresponding literature for details). We used commercially side-chain, we tested structurally more simple compounds available sources of C as starting materials or reagents, for their use in selective tryptophan labeling. Considering such as isotopologues of acetone, glycine, potassium cya- the irreversibility of the anthranilate synthase EC 4.1.3.27 nide and formaldehyde (Lichtenecker 2014; Lichtenecker catalyzed elimination of pyruvate from chorismate, we could et  al. 2015). Deuterium patterns have been exclusively provide evidence that isotope patterns in anthranilate, as well derived from deuterium oxide, which is the cheapest source 2 13 as indole can be transferred to the tryptophan side-chain of H available. 1- C labeled precursors 1, 4, 6 and 14 have without losing heavy isotopes in the shikimate pathway been applied to probe for labeling selectivity and precur- (Schörghuber et al. 2015, 2017a). Regarding histidine labe- sor uptake in diverse model protein overexpression systems. ling, we focused on the first intermediate of the minor deg- Their straightforward synthesis (1, 4 and 6 are prepared from radation pathway, imidazolepyruvate. Again, the reversible [1- C]glycine in three steps) renders them economic tools transaminase EC 2.6.1.38 reaction ensured an effective in- for residue-selective backbone-labeling to be used for e.g. vivo conversion to the target residue. In this case we applied unambiguous signal assignment in high molecular-weight the stable enol-tautomer of imidazolepyruvate as a labeling protein complexes. precursor (Schörghuber et al. 2017b). All of the identified The Phe-precursors 2 and 3, the Tyr-precursor 5, as precursor compounds mentioned showed highly selective well as the Trp-precursors 9, 10, 12 and 13 display well- 13 1 labeling of the corresponding target residues in absence of defined deuteration patterns leading to isolated C– H any cross-labeling to undesired atomic positions. spins. These systems are devoid of any additional scalar couplings, which otherwise distort relaxation rate analy- 1 2 sis. Highly regioselective H/ H exchange was performed on electron-rich aromatic rings in acidic deuterium oxide shikimate COO pathway glycolysis D-erythrose EC 4.1.3.27 NH chorismate D-glucose + pyruvate pentosephosphate- EC 5.4.99.5 pathway anthranilate indole D-ribose-5- prephenate EC 4.2.1.20 phosphate EC 1.3.1.12 EC 4.2.1.51 L-tryptophan EC 2.6.1.38 COO - - COO COO L-histidine EC 2.6.1.27 EC 4.3.1.3 HO COO (4-hydroxyphenyl) urocanate phenylpyruvate imidazolepyruvate pyruvate EC 2.6.1.58 EC 2.6.1.5 indolepyruvate L-phenylalanine L-tyrosine L-glutamate His-pathway Trp-pathway Phe- and Tyr-pathway Scheme 1 Outline of the aromatic amino acid metabolism in E. coli 1 3 phenylalanine tyrosine labelling tryptophan labelling histidinelabelling labelling 132 Journal of Biomolecular NMR (2018) 71:129–140 Scheme 2 Late metabolic pre- O O cursor compounds for aromatic D D [1- C]glycine - - 2 2 residue labeling. Commercially COO H O COO H O 2 2 D D 13 - COO available isotope sources are D D D D denoted in grey italics 13 13 C C H H D C D [2- C]acetone [1,3- C ]acetone D H 1 2 3 O O [1- C]glycine COO 13 - COO H O D D 13 13 C C H H [1,3- C ]acetone OH 2 OH [1,3- C ]acetone [1- C]glycine [ C]potassium- cyanide H 13 - COO D C N N [ N]ammonium- H H D chloride H O 6 89 [ N]ammonium- chloride 2 2 - - H O H O - 2 COO 2 COO COO 15 + H H + + NH NH 3 D NH 13 13 3 H O 2 C N 13 D C D H H 13 13 [2- C]acetone H [1,3- C ]acetone [2- C]acetone H 2 H D 10 11 12 13 OH 13 OH [1- C]glycine 13 - COO COO [ C]formaldehyde HN HN C under elevated reaction temperatures. All these com- Precursor uptake and labeling selectivity pounds can be accessed from one common synthetic intermediate (isotopologues of 4-nitrophenol 17 and 19), Effective uptake of isotope labeled precursors by the overex- which is a significant advantage from an economic point pressing organism is of utmost importance, since this factor of view (Scheme 3). Labeled histidines are important sen- determines the highest possible isotope incorporation level at sors for protein dynamics and help to elucidate the pK certain precursor concentrations in the corresponding media. values of the imidazole ring (Hansen and Kay 2014; Hass Isotope incorporation at a given concentration may vary with et al. 2008). The ε- C His-precursor 15 exhibits an inher- different target proteins as a function of protein size, number 13 1 ently isolated C– H spin system and was developed to of target residues and overexpression conditions. We identi- provide an optimal isotope pattern to probe this unique fied the following precursor concentrations as being required heteroaromatic side-chain. Compound 15 can be prepared in the E.coli overexpression media to achieve near-quantita- via a straightforward 5-step route starting from [ C]for- tive to quantitative isotope incorporation at the target atomic maldehyde (Schörghuber et al. 2017b). positions: 60–150  mg/L phenylpyruvate, 80–200  mg/L 1 3 Journal of Biomolecular NMR (2018) 71:129–140 133 Scheme 3 Synthesis of Phe-, 7 steps 8 steps 25% 21% Tyr- and Trp-precursors via the common synthetic intermedi- ates [2,6- C ]4-nitrophenol 16 6 steps nitromalon- nitromalon- and [1- C]4-nitrophenol 19. NO NO 43% aldehyde, aldehyde, 6 steps For more details concerning O NaOH, 65% O NaOH, 65% 32% synthetic routes and concepts, 13 10 5 steps 13 13 see the corresponding literature 13 C C H C 29% 3 13 CH 3 H H (Lichtenecker 2014; Schörghu- ber et al. 2015, 2017a) OH OH 17 19 6 steps 8 steps 39% 27% 4-hydroxyphenylpyruvate (Lichtenecker et  al. 2013c), Miyanoiri et al. 2011; Vuister et al. 1994). The concentra- 20–60 mg/L indolepyruvate, 12–30 mg/L indole (Schörghu- tions required can even be further decreased when using ber et al. 2015), 8–30 mg/L anthranilic acid (Schörghuber auxotrophic expression strains (Lin et al. 2011; Yang et al. et al. 2017a), and 50–100 mg/L imidazolepyruvate (Schör- 2015). Other reports indicate that the use of labeled amino ghuber et al. 2017b). This data has been deduced from labe- acids in E. coli-based overexpression systems is to some ling efficiency plots, which were obtained by overexpressing extent limited by metabolic product feedback control mecha- the corresponding protein sample in presence of different nisms, which may lead to decreased isotope uptake, retarded precursor concentrations. The low amount of late metabolic cell growth or cross-labeling (Krishnarjuna et  al. 2011; precursors required to achieve maximal heavy isotope con- O’Grady et al. 2012; Rowley 1953). In the case of aromatic tents is in sharp contrast to labeling methods using early residues, Phe, Tyr and Trp have shown to inhibit the E. coli metabolic intermediates. Examples from literature report DHAP synthase isoenzymes, which control the carbon flow concentrations of 1–4 g/L in this case, leading to isotope into the shikimate pathway (Herrmann 1995). Additionally, enrichment of 30–75% at the desired atomic positions in certain levels of amino acid concentrations affect the transla- Phe, Tyr, Trp or His-residues (e.g. Kasinath et al. 2013; Wei- tion machinery, thereby slowing down growth rates (Avci- ninger 2017b). These values are far from the quantitative lar-Kucukgoze et al. 2016). Besides, organic synthesis of isotope labeling, which we observed when applying the late complex isotope patterns in the case of amino acids is con- metabolic precursor compounds illustrated in Scheme 2. siderably elaborate and expensive, due to the required imple- Using single atom C-labeled early metabolic precursors mentation of at least one center of chirality, as well as the 12 13 15 induces a certain pattern of C/ C isotopes, but despite of need of introducing N by additional synthetic steps if nitro- improving selectivity by exploiting auxotrophic organisms gen-15 labeling is desired (Miyanoiri et al. 2011). In contrast (e.g. LeMaster and Kushlan 1996) or supplying the growth to that, N-labeling of the target residues is straightforward media with enzyme inhibitors (e.g. Tong et al. 2008) a cer- in the case of applying metabolic amino acid precursors by tain degree of cross-labeling cannot be ruled out. In various adding N-salts to the expression media. In order to reduce applications of our precursor toolbox, we did not observe synthetic efforts, more elaborate commercially available any isotope scrambling so far. Our experiments indicate isotope sources can be applied. Phenylalanine, for instance, that any isotope pattern, which can be implemented onto the has been prepared from labeled tyrosine in two steps (Wang structures shown in Scheme 2 will quantitatively be trans- et al. 1999). The simplified synthesis, however, comes along ferred to the corresponding target residue. Most importantly, with increased costs for the starting compound. In a recently this is also true for patterns of (non-solvent exchangeable) published noteworthy economic approach, labeled phenyla- deuterium atoms. Consequently, late metabolic precursors lanine was produced in E. coli from glycerol and secreted of aromatic residues can be applied to introduce aromatic into the growth medium. The thus isolated amino acid sub- ring protons into protein samples with high overall deute- sequently served as an isotope source in recombinant E. coli rium levels. In this case, uniform deuterium labeling can be protein overexpression (Ramaraju et al. 2017). However, achieved using deuterium oxide together with H-containing the application of amino acids in cell-based overexpression early metabolic isotope sources such as [all- H]glucose. required the addition of metabolic inhibitors and unlabeled Another strategy to achieve well-defined isotope patterns amino acids in order to obtain high isotope incorporation in protein samples applies labeled amino acids as additives levels also in this case. One literature reported protocol to the overexpression media. Examples from literature show makes use of shikimic acid to generate protonated aromatic that amino acid concentrations in the low mg/L range may residues in an otherwise uniformly C-protein (Rajesh et al. result in high incorporation levels (Kemple et  al. 1994; 2003). It can be considered as rather improbable that this 1 3 134 Journal of Biomolecular NMR (2018) 71:129–140 strategy will be transferred from reverse-labeling to selec- originate from residues in close contact to the binding site tive C-labeling in aromatic residues in future, due to the (Tyr97, Tyr139 and Trp81). The third shifting tyrosine reso- required synthesis of C-shikimic acid. nance is very likely caused by Tyr98, which is in close con- Table 1 gives a -by no means exhaustive- overview con- tact to Tyr97 and thus also influenced by ligand binding. cerning the various strategies of aromatic residue labeling Importantly, strong CSPs in the proton dimension of selec- in E. coli based and cell-free systems published so far. The tively labeled sites provide crucial information about the data shown shall illustrate the differences in selectivity, pre- proximity of aromatic ring-systems of interacting ligands. cursor concentrations needed, synthetic effort and isotope CSPs induced in the tryptophan spectrum (Fig. 2a) show incorporation levels. only marginal differences between the three tested ligands. Only one of the compounds induces a strong upfield shift in the proton dimension of the η2-position of Trp81, indicating Applying late metabolic aromatic precursor a binding mode, which places an aromatic ring-system on η2 compounds to investigate proteins and their top of H (Fig. 2a, magenta spectrum). interaction sites Ligand induced cross‑correlation rates Chemical shift mapping In additional experiments, we employed selective Trp 13 ε3 13 η2 We chose bromodomain 1 of bromodomain-containing pro- C / C labeling on Brd4-BD1 to evaluate the effect tein 4 (Brd4-BD1) as an example to highlight the benefits of different ligands on the Chemical Shift Anisotropy of labeling isolated positions in aromatic side-chains. Brd4 (CSA)–Dipol-Dipol (DD) cross correlation rate (CCR) η of is a chromatin reader that binds to acetylated lysines in his- the labeled carbon nuclei. As mentioned before, the Brd4- tones and has proven to be a promising cancer target in the BD1 system comprises three tryptophans, one of which pharmaceutical industry (Zeng and Zhou 2002; Sanchez (Trp81) is embedded in a hydrophobic pocket that is targeted et al. 2014). We already described Trp-labeled Brd4-BD1 by various inhibitor molecules (Jung et al. 2014). Cross cor- in previous work (Schörghuber et al. 2017a), and we want relation between CSA and DD interactions in a system of to elaborate on the application of selective aromatic labe- coupled 1/2 spins can yield valuable information about local ling for probing ligand interaction further using this system. electronic structure and dynamics (Brutscher 2000; Kumar 1 13 Figure 1 compares the H– C HSQC spectrum of uniformly et al. 2000). Therefore, we chose precursor 12 to generate 13 13 ε3 1 13 η2 1 C-labeled Brd4-BD1 (Fig. 1a) with the spectra of either exclusive C – H/ C – H spin pairs in the target residues. 13 ε3 13 η2 13 ε Trp( C / C )- or Tyr( C )-labeled Brd4-BD1 (Fig. 1b, This pattern eliminates scalar coupling contributions from ζ2 ζ3 blue and red spectrum). Figure 1b shows six tryptophan- and nearby C –H and C –H pairs. In order to calculate CCRs 13 ε3 13 η2 ε3 η2 seven tyrosine resonances according to the three C / C -for Trp81 and Trp81 we utilized a coupled version of a 13 ε 1 13 labeled tryptophans, as well as the seven C -labeled tyros- constant time H– C HSQC to extract peak intensities for ines present in the Brd4-BD1 sequence. All the signals are the upfield (I ) and downfield (I ) components of the C + − well-defined and devoid of any splitting due to additional doublets, which allows for the calculation of correspond- scalar couplings. On the contrary, the tryptophan resonances ing cross-correlation rates. Figure 3 displays the twelve sig- of the uniformly labeled sample barely exceed the noise nals that emanate from the three tryptophan residues pre- ε3 threshold and all aromatic side-chain signals are affected by sent. Highlighted are the 1D slices for both Trp81C and η2 strong J couplings to neighboring positions. Especially Trp81C showing the upfield (+) components in red, and CC the Tyr-signals suffer from substantial signal overlap, which the downfield (−) components in blue. The ratio of peak severely restricts their use for ligand induced chemical shift intensities (I /I ) is related to the CCR (η) via ln(I /I ) = 2Tη + − + − perturbation studies. where T is the mixing time in the NMR experiment during Figure  2 illustrates the chemical shift perturbations which cross correlated relaxation is active (Brutscher 2000). (CSPs), which have been induced by three different ligands Figure 4 shows 2D spectra and extracted 1D traces in the 1 13 13 ε3 13 η2 in H– C HSQC spectra of Trp( C / C )-labeled Brd4- presence of a small molecule ligand and their corresponding 13 ε ε3 η2 BD1 (Fig. 2a) and Tyr( C )-labeled Brd4-BD1 (Fig. 2b). η values. CCR rates for T rp81 and T rp81 were deter- −1 The corresponding protein samples were overexpressed in mined to 46.5 and 50.2 s . Interestingly, these rates were ε3 −1 E. coli using precursor 12 (20 mg/L medium), or precursor smaller than in the apo-state of BRD4 (T rp81 : 50.8 s ; η2 −1 5 (100 mg/L medium) containing minimal medium, respec- Trp81 : 53.3 s ) presumably due to subtle changes of the tively. The low-molecular weight ligands added target the CSA tensor and/or local conformational dynamics. binding cleft of Brd4-BD1, which is lined by one tryptophan (Trp81) as well as two tyrosine residues (Tyr97 and Tyr139). The spectra reveal that the only resonances to be affected 1 3 Journal of Biomolecular NMR (2018) 71:129–140 135 Table 1 Overview of published protocols concerning aromatic residue protein labeling n.d. no data available, prec. conc. precursor concentration, prot. prec. protonated precursor, bact. prod. bacterial production, com. sup. commer- cial suppliers, amino acids are depicted by one letter code Expression in a succinate dehydrogenase deficient E. coli strain Together with 2 g/L deuterated pyruvate c 13 Additional supply of N aH CO Reverse labeling using protonated precursor e 13 Overexpressing organism lacks succinate- and malate dehydrogenase; addition of NaH CO f 13 Incorporation rates can be maximized to 75% by addition of C-isotopologues of glucose Application of a shikimate auxotroph h 13 Precursor produced in E. coli medium containing [2- C]glycerol Addition of glyphosate and unlabeled amino acids to prevent cross labeling and increase precursor uptake Synthesized from labeled tyrosine For the exact isotopic patterns of these precursors see the literature cited An auxotrophic overexpression host was used 1 3 136 Journal of Biomolecular NMR (2018) 71:129–140 1 13 Fig. 1 a H– C HSQC spec- (a) (b) trum of uniformly C-labeled 1 13 Brd4-BD1. b H– C HSQC spectra of selectively 13 ε3 13 η2 Trp( C / C ) (blue) and 13 ε Tyr( C ) (red) labeled Brd4- BD1. Samples were expressed and purified as described before (Schörghuber et al. 2017a). Spectra were acquired on a 600 MHz spectrometer at 298 K on a sample of 0.1 mM protein concentration at pH 7.5 1 13 Fig. 2 CSPs observed in H- C HSQC spectra of selectively magenta spectra). The binding cleft of Brd4-BD1 is shown (red 13 ε3 13 η2 13 ε Trp( C / C )-labeled Brd4-BD1 (a) and Tyr( C )-labeled Brd4- arrow) highlighting the proximal Tyrosine (Tyr97, Tyr98, Tyr139) BD1 (b) after the addition of three different ligands (red, blue and and Tryptophan residues (Trp81) (c) development (Zhang et al. 2015). The acquisition of struc- Structural restraints in intrinsically disordered proteins tural restraints to identify potential preformation of specific secondary structure elements in the unbound state, as well Highly selective aromatic residue labeling holds promise as their conformational stabilization upon ligand binding, is however still a very challenging task (Konrat 2014). Figure 5 to yield valuable additional distance information through well-defined NOE signals, even in the case of structurally shows a C-NOESY-HSQC strip of an intrinsically disor- dered N-terminal fragment (residues 50-171) of Yes-asso- flexible protein regions or intrinsically disordered pro- teins (IDPs). Various research groups are just beginning to ciated protein (YAP). This region was identified to contain the binding site to the transcription factor TEAD (Vassilev explore the potential of IDPs as important targets in drug 1 3 Journal of Biomolecular NMR (2018) 71:129–140 137 Fig. 5 Left A strip from a C-NOESY-HSQC spectrum of the uniformly N and selec- tively phenylalanine labeled IDP YAP (50-171). The strip is assigned to Phe95/96-H and exhibits NOEs to Leu91-H and Leu91-H . Right A strip from a N-NOESY-HSQC of the same protein assigned to Leu91-H . Spectra were aquired at 800 MHz, 298 K on a sample of 1.0 mM protein concentration 13 15 at pH 6. C and N chemical shifts are indicated in the top region of the slices 1 13 Fig. 3 Coupled H– C HSQC spectrum of selectively 13 ε3 13 η2 Trp( C / C )-labeled Brd4-BD1 with 1D slices for Trp81 down- field (blue) and upfield (red) components. Samples were prepared and measured as denoted in Fig. 1 et al. 2001). The YAP/TEAD interaction regulates the Hippo pathway, which is deregulated in various cancers and there- fore represents a promising target for cancer therapy (Liu et al. 2012). A recent study indicates propensities for the preformation of an α-helix and an N-terminal β-strand in YAP50-171 in its unbound state (Feichtinger et al. 2018). These partially preformed secondary structural elements, together with an omega-loop (residues 86-100), form the interacting surface upon TEAD binding. For the omega- loop, no structural preformation was anticipated so far. In order to further investigate the potential preformation of cer- tain structural elements in this IDP, a uniformly N-YAP 50-171 sample was additionally labeled using compound 3 in the corresponding growth medium. Significant long-range ε3 Fig. 4 Overlay of the up- and downfield slices extracted for Trp81C ς γ (side-chain) NOEs between Phe95/96-H and Leu91-H η2 (top) and Trp81C (bottom) in the presence of Ligand 1 with their and Leu91-H were observed (Fig. 5). This data shows that, corresponding η values. Samples were prepared and measured as denoted in Fig. 1 although YAP is largely unfolded in absence of its binding partner, very selective labeling can identify direct distance 1 3 138 Journal of Biomolecular NMR (2018) 71:129–140 Economy and the National Foundation for Research, Technology and proximities and thus long-range structural preformation of Development is gratefully acknowledged. the Ω-loop region (residues 86-100). This property was not perceived by analyzing chemical shift data via secondary Open Access This article is distributed under the terms of the Crea- structure propensity score calculation (Marsh et al. 2006) in tive Commons Attribution 4.0 International License (http://creat iveco previous studies (Feichtinger et al. 2018). mmons.or g/licenses/b y/4.0/), which permits unrestricted use, distribu- tion, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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Journal of Biomolecular NMRSpringer Journals

Published: May 28, 2018

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