An NMR Biochemical Assay for Fragment-Based Drug Discovery

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An NMR biochemical assay for fragment-based drug discovery: evaluation of an inhibitor activity on spermidine synthase of Trypanosoma cruzi Kazuhiko Yamasaki, Osamu Tani, Yukihiro Tateishi, Eiki Tanabe, Ichiji Namatame, Tatsuya Niimi, Koji Furukawa, and Hitoshi Sakashita J. Med. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jmedchem.5b01769 • Publication Date (Web): 16 Feb 2016 Downloaded from http://pubs.acs.org on February 17, 2016

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Journal of Medicinal Chemistry

An NMR biochemical assay for fragment-based drug discovery: evaluation of an inhibitor activity on spermidine synthase of Trypanosoma cruzi Kazuhiko Yamasaki1,*, Osamu Tani1, Yukihiro Tateishi2, Eiki Tanabe2, Ichiji Namatame2, Tatsuya Niimi2, Koji Furukawa1, and Hitoshi Sakashita1 1

Biomedical Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1 Higashi, Tsukuba, 305-8566, Japan. 2 Drug Discovery Research, Astellas Pharma Inc., 21 Miyukigaoka, Tsukuba, 305-8585, Japan. ABSTRACT: Although NMR in fragment-based drug discovery is utilized almost exclusively to evaluate physical binding between molecules, it should be also a powerful tool for biochemical assay, evaluating inhibitory effect of compounds on enzymatic activity. Time-dependent spectral change in real-time monitoring or inhibitor concentration-dependent spectral change after constant-time reaction was processed by factor analysis, by which reaction rate or IC50 value was obtained. Applications to spermidine synthase of Trypanosoma cruzi, which causes Chagas disease, are described.

INTRODUCTION Fragment-based drug discovery (FBDD) is a well-practiced rational scheme for development of inhibitory drugs against target proteins1. ‘Fragments’ with low molecular weight (typically less than 300) are selected from library on the basis of physical binding with the target protein or inhibitory activities in a biochemical assay. In most cases, crystal structures of the complexes of the protein and selected fragments are determined and used for the rational design for optimization of the compound by means of medicinal chemistry. NMR is the most versatile spectroscopy and is utilized effectively in FBDD, especially at the initial screening stage2. Binding of fragments to the target protein can be detected by observing the spectra either of the fragments or the proteins. The proteins to be observed are usually labeled by stable isotope (13C and 15N), and methods involving the isotope resonance, such as heteronuclear single-quantum coherence spectroscopy (HSQC), are employed3, 4. Then, changes in the spectra of the protein upon adding a fragment or a fragment mixture are used to evaluate the interaction. For observing the fragments, methods such as saturation transfer difference5 and waterLOGSY6 experiments are used to effectively select fragments with ability to bind to the protein, where fragments may be mixed in order to accelerate the screening of the library. As described, the above NMR approaches adopted in FBDD are focused almost exclusively on physical binding, but not on the biochemical assay. By detecting the peaks of substrates and products, NMR should be effectively used also for the enzymatic assay. In the present study, we made efforts to apply NMR to biochemical assay, which should be incorporated in the FBDD process. We adopted two protocols for evaluation of enzymatic reaction and inhibitor activity. The first protocol is based on a real-time monitoring of the reaction com-

bined with factor analysis (FA)7 of the spectra, which has advantages in accurately estimating the activity. Merits in combination of real-time NMR and FA have been demonstrated for a system of protein folding8. The second protocol is based on a constant-time batch reaction on 96-well plate, involving incubation and stopping within a thermal cycler unit, which was also processed with FA. The second one has advantages in accelerating the fragment screening, especially when the spectrometer is equipped with an automatic sample changer. As the target protein, we used spermidine synthase (E.C. number 2.5.1.16) of a parasitic protozoan Trypanosoma cruzi. T. cruzi causes Chagas disease, which infects eight millions of people mostly in Latin America, and kills ~10,000 people per year9. Two clinically used drugs for Chagas disease, nifurtimox and benznidazole, are effective in acute phase, although tend to be unsatisfactory in the chronic phase9. In addition, they have a number of side effects and are genotoxic, precluding treatments for pregnant women. Therefore, efforts to discover new drugs against T. cruzi should be continued. Spermidine synthase (SpdS) is involved in polyamine biosynthesis and catalyzes a reaction involving two substrates and two products, putrescine + decarboxylated S-adenosylmethionine (dcSAM) → spermidine + methylthioadenosine (MTA) SpdS of T. cruzi is highly expressed at the life-cycle stage of amastigote, which exists in the infected human cells (TritrypDB: http://tritrypdb.org/)10 and is most related to the chronic phase of Chagas disease. In addition, its tertiary structure has been determined (PDB entries 3BWB and 3BWC; Bosch, J., and Hol, W. G. J, manuscript not available). Several competitive inhibitors for SpdS are known, among which trans-4-methylcyclohexylamine (4MCHA) shows a relatively high activity, with an IC50 value of 1.7 µM against porcine SpdS11, 12. Also, the crystal structure of malaria parasite SpdS

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in the complex with 4MCHA is available13. We therefore used this inhibitor as the application target in developing the NMR protocols for biochemical assay. RESULTS AND DISCUSSION Real-time NMR observation of the SpdS reaction. A part of the NMR spectrum of the substrate mixture was shown in Fig. 1A. The peaks at 1.76 and 3.02 ppm originate from putrescine (marked “p” in the figure), while those at 2.17, 2.92, 2.95, and 3.04 ppm originate from dcSAM (marked “d”), as revealed by separately measured spectra (data not shown). Among them, two singlet peaks at 2.92 and 2.95 ppm are assigned to the S-methyl protons of dcSAM, which was chemically synthesized as racemic mixture with regard to the chirality at the sulfur atom; these are the only singlet peaks in the present region and the chemical shifts are close to those of Sadenosylmethionine possessing nearly the same chemical environment (2.96 ppm and 3.01 ppm)14. For Sadenosylmethionine, the downfield peak originates from the S diastereomer that is biologically active, while the other is from the R diastereomer that is biologically inactive14, 15. This is also the case with N-acetyl dcSAM, which was derived as a metabolite of dcSAM16. Therefore, we applied these distinctive assignments also to dcSAM (Fig. 1A). By adding enzyme, the intensities of the peaks of substrate molecules decreased as reaction proceeds, except for the R diastereomer of dcSAM (Fig. 1A). Thus, it was clearly seen that also for SpdS, the S diastereomer is active while the other is inactive. This is fully consistent with previous biochemical observations showing that the separated S diastereomer is twice as active as the chemically synthesized racemic mixture17, 18 and crystal structures of the SpdS-dcSAM complexes containing the S diastereomer13, 19. Concurrently with the decrease in the substrate-originated peaks, new peaks such as those at 1.79, 2.11, 2.13, 3.06, and 3.10 ppm arise and increase in their intensities, among which those except for a singlet peak at 2.11 ppm originate from spermidine (marked “s”), as shown by the spectrum of this molecule (data not shown; peaks of MTA may be degenerated in part). The singlet peak at 2.11 ppm was assigned to that of the S-methyl protons of MTA (marked “m”), because this is only the singlet peak in this region and its chemical shift is very close to that of methionine possessing a similar chemical environment around the S atom (2.13 ppm)20. In order to analyze the spectral change, we employed a protocol based on FA (see equations 1 to 3 in the Experimental Section)7. The merits of FA in combination with real-time NMR are that we can deal with spectra consisting of a large number of data points simultaneously and that we can separate the factor relevant for time-dependent change from those related to baseline instability and/or noise8. The factor with the largest eigenvalue (the first factor) clearly showed a timedependent spectral change reflecting the substrate-product conversion (Fig. 1B, C). Namely, the positive and negative peaks in the loading vector of the first factor coincide with those of substrates and products, respectively, which is clearly seen by comparing Figs 1A and 1B. The time dependence in the score vector can be fitted by an exponential curve (Fig. 1C), yielding the rate constant, 0.064 min–1. In contrast, the other factors with much smaller eigenvalues (< 1.8% of that of the first factor; the second factor, etc.) are not much time dependent. Considering that dispersive peaks appear in the loading vector of the second factor (2.11 ppm and 2.92 ppm; red in

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Fig. 1B), which coincide with sharp peaks originating form the methyl protons of MTA and the R-diastereomer of dcSAM, the second factor is likely to be relevant mainly for the instability in chemical shifts of these peaks. Other factors with further smaller eigenvalues may be relevant for baseline instability, as only baseline differences are seen in loading vectors for these factors (Fig. 1B). After a treatment with simple eigenanalysis (or principal factor analysis) as described above, further rotational operations involving multiple factors, such as target factor analysis, are generally required in order to obtain interpretable “real” factors7. However, such operations are not necessary in the present study, because we isolated only a single factor relevant for enzymatic reaction. Alternatively to the above, we may analyze the signal intensities of the respective peaks of substrate or product, in order to evaluate the reaction rate. However, it is necessary to select a data point representative of the peak, although the peak consists of several points. Also, analysis of a single point directly suffers from spectral noise and may cause difference in the rates derived from different peaks. Therefore, the present protocol treating the spectrum as multipoint data to obtain a single reaction rate is rather simple, which should yield less biased and more accurate results. Evaluation of an inhibitor based on real-time NMR. By using the above real-time NMR method combined with FA, we evaluated an inhibitor, 4MCHA. As the concentration of 4MCHA increases, the rate obtained by the FA treatment decreases (Fig. 2). The relationship between the concentration and rate was well fitted to equation 4 in the Experimental Section, which was based on the mechanism for a competitive inhibitor21, yielding a value of the inhibitor concentration causing 50% inhibition (IC50) of 0.62 µM. 4MCHA is the competitive inhibitor against putrescine, but not against dcSAM11, and it indeed binds to the putrescine-binding pocket of SpdS in the crystal structure13. Considering the above mechanism, the equations (equations 4–6) that involve a single substrate are suitable in the present case. For porcine SpdS, a significantly larger IC50 value of 1.7 µM for 4MCHA was obtained in a previous study11. Without considering the origins of the enzyme, the difference in the IC50 value is mainly caused by that in the substrate concentration: i.e., 1.0 mM for the previous study, while 0.5 mM for the experiment shown in Fig. 2. This is because IC50 is keenly related to the substrate concentration (S) used in the experiment, or is proportional to it under an extreme condition, S >> Michaelis constant (Km), as in equation 621. This is nearly the case in the previous study for porcine SpdS, where putrescine concentration was ten-times larger than Km11. Evaluation of an inhibitor by constant-time reaction. The above method to evaluate the IC50 value by real-time NMR is time-consuming, taking ~1h of successive NMR measurements for each concentration point, and therefore several hours at least for a single inhibitor. In order to make use of the NMR-based biochemical assay in FBDD, an alternative timesaving method should be applied. We introduced a system of a constant-time batch reaction on a 96-well plate. The reaction was initiated by mixing solutions of substrates and enzymes, and stopped by heat denaturation of enzyme. Incubation for reaction and heating for denaturation are performed within a thermal cycler device. Then NMR measurements were carried out for the respective samples separately.


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Difference in the inhibitor concentration causes differences in the reaction rate and thereby in NMR spectral intensities of substrate and product. By applying FA for spectral regions, the score vector for the first factor with the largest eigenvalue showed significant dependency on the inhibitor concentration (Fig. 3A). This factor corresponds to the inhibitory effect on the enzymatic reaction, as seen in the loading vector that shows positive and negative signs for the substrate and product peaks, respectively (Fig. 3B). This score vector was fitted to a combination of equations expressing the mechanism for a competitive inhibitor (equations 4 and 7 in the Experimental Section)21. In contrast to the real-time method, we simply need to take spectra without time limitation. Therefore, we may enhance the signal to noise ratio by data accumulation, and thereby decrease the substrate concentration. Thus we obtained a smaller IC50 value of 0.093 µM for a smaller substrate concentration of 50 µM, compared with those in the real-time NMR method (IC50 of 0.62 µM for 0.5 mM of substrate concentration; note that IC50 is keenly related or may be nearly proportional to the substrate concentration, as described; see equation 6). It should be pointed out technically that the reaction time should be set within an appropriate range in order to observe the effect of inhibitor by a measure of difference in the NMR signal intensity. If we intend to maximize the difference in the intensity at the IC50 concentration point, the reaction time should be set to ln 4 / V0, where V0 is the rate in the absence of inhibitor, as calculated for the time (t) at which e. − e is maximum. By utilizing an automatic sample changer, the present scheme drastically reduces the manual labor, and is likely to be suitable for fragment screening. In the present application, we used 16 measurements with different inhibitor concentrations each taking ~30 min, in order to obtain an IC50 value as accurate as possible, under a condition with a low substrate concentration. However, for a simple assay at the screening stage, we can use a higher concentration of substrate and fewer points for inhibitor concentration, so that the respective measurement time and points may be safely reduced to 5 min and 5–10, respectively. Thus, 0.5–1 hours should be required to evaluate a single compound, and screening of a fragment library of 1,000 compounds will take 20–40 days. The time for the screening will be drastically reduced if we use mixtures of compounds, e.g., 2–4 days for 100 mixture samples each containing 10 compounds. In this case, when we find a hit for a mixture sample, with a low apparent IC50 value, subsequent analyses on the individual compounds should be conducted, in order to identify the compound with inhibitory effect. Moreover, concentration of compounds might be fixed in the initial screening, which will further reduce the time by 1/5~1/10 compared with the above method. Also in this case, FA should be applicable effectively, by dealing with results of many compounds simultaneously and arraying them into a matrix. After this qualitative analysis, only the compounds with positive results should be subjected to the quantitative evaluation of IC50. Comparisons of NMR biochemical assay with other methods in FBDD. Conventional biochemical assays are mostly based on fluorescence detection, which frequently suffer from false positives1. A part of them come from the optical properties of the compounds, interfering with the fluorescence development and/or detection that reflect the inhibitory effects on the enzyme. Also, all enzymes do not have fluorescence-

detectable substrate-product system, which can be rescued occasionally by introducing a cascade of multienzyme reactions. Indeed, for SpdS, we utilized such multi-step reaction system22. Obviously this may suffer from inhibitory effects on the other enzyme(s) relevant for the fluorescence-developing reaction. The NMR-based biochemical assay in the present study is based on the simple observation of 1H-NMR signals from substrate and/or product. Therefore, it is easy to construct the system, unless the substrates or products lack detectable protons, which is free from the false positives described above for the conventional biochemical assay. We should mention that 19 F-NMR has been effectively used for the biochemical assay in FBDD23. Although 19F-detection gives very simple NMR spectra, which is easier to analyze, substrates should be modified to incorporate fluorine atoms. The present protocol using 1 H-NMR spectra may deal with unmodified substrate; the FA treatment facilitates the interpretation of the relatively complex spectra. Note that the NMR biochemical assay, like other methods, should suffer from false positives caused by irreversible reactions between compound and enzyme, occasionally forming covalent bonds24. At the moment, NMR-based methods in FBDD are used almost exclusively to evaluate the physical binding between compounds and target protein, which are largely divided into two categories, i.e., protein-detecting methods and liganddetecting methods2. The former typically employ stable isotope-labeled protein and detect change in isotope-involving spectra upon binding of compounds3, 4. For such measurements, 200–500 µM of protein and equal or larger amounts of compounds are required for a conventional NMR spectrometer (these concentrations may be reduced to 20–50 µM using a sensitivity-enhanced cryogenic probe2). The latter methods require much less amount of protein, 0.5–5 µM, and 40–50 times higher amounts of compounds2, 5. In the present methods, we used even lower amount, 44 nM, of protein and up to 40 µM of inhibitor compound in the constant-time reaction method shown in Fig. 3 (the concentration of the inhibitor may be safely reduced to 10 µM), although these amounts depend largely on the activities of enzyme and inhibitor. In addition, the existing NMR methods for physical binding have false positives, due to binding of compounds to sites other than the substrate-binding site, without inhibitory activity in most cases. Also, the ligand-detecting methods have false negatives for high affinity systems, e.g., with KD of 10–9 M, because the binding effect was detected on the peaks of free ligands, on the premise of a fast equilibrium between the bound and free states; consequently, systems with KD of 10–4– 10–5 M is suitable5, 6. The present method for NMR biochemical assay is free from these false positives and negatives. On the other hand, the present method has limitation in that it may be applicable only to enzymes, as a matter of course, but not to binding proteins, e.g., receptors. It is also affected by solubility and stability of substrates, products, and enzymes, which may be overcome by selection of solvents or supplement of additives, such as detergents. Considering that the merits and demerits of the NMR biochemical assay are significantly different from others, we believe that this method may be included in a repertoire of the methods usable in FBDD. It should be especially powerful for the systems in which fluorescence detection cannot be applied even by introducing multi-step reactions. We now started to adopt the NMR biochemical assay to evaluate inhibitory ef-



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fects of several compounds on T. cruzi SpdS in an effort to develop drugs for Chagas disease (Tanabe et al., to be published elsewhere). An example for a fragment, 2H-1,4benzothiazin-3-amine, was shown in Fig. S1 in the Supplementary Material, with an IC50 value of ~100 µM. For this compound, as well as others, crystal structures in complex with the protein were obtained, showing the binding/inhibition mechanism22; this compound binds to the putrescine binding site, where flipping of a Tyr residue was induced to form a different shape of binding pocket from that for 4MCHA. EXPERIMENTAL SECTION Sample preparation. The following protocol for the sample preparation is essentially as described previously22. The DNA that codes for spermidine synthase (E.C. number 2.5.1.16) of T. cruzi strain CL Brener (NCBI code XP_811272.1) was chemically synthesized with the codon usage optimized for Escherichia coli (Thermo Fisher Scientific Inc.). After PCR amplification with primers designed so as to include an additional MetAlaHisHisHisHisHisHis sequence at the N terminus, the DNA was incorporated between the NdeI and XhoI sites of expression vector pET-30b (Merck Millipore). The protein was expressed by E. coli strain BL21(DE3) in LB medium at 30 °C and purified by column chromatography, such as Ni-NTA superflow (Qiagen), Resource Q (GE Healthcare), and Superdex 75 (GE Healthcare). The protein concentration was evaluated by A280 value using an extinction coefficient 35,410 M–1cm–1, as calculated by numbers of tryptophan and tyrosine residues, without considering cystines. Real-time NMR and FA. 0.25–1.0 mM dcSAM (racemic mixture on the chirality at the sulfur atom; Peptide Institute, Inc., Osaka, Japan) and 0.1–0.5 mM putrescine (MP Biochemicals, Santa Ana, CA) were dissolved in 100 mM sodium phosphate buffer (pH 7.0) containing 0–10% dimethylsulfoxide-d6 (DMSO-d6; Cambridge Isotope Laboratories Inc., Andover, MA), 5% D2O, 20 µM sodium 2,2-dimethyl-2silapentane-5-sulfonate (DSS; Sigma-Aldrich), and 0–6.75 µM 4MCHA (Tokyo Chemical Industry, Co. LTD., Tokyo, Japan). Three to four minutes after initiating the reaction by adding enzyme at 10–50 µg/mL (0.29–1.45 µM) in an NMR tube of 500 µL solution, a series of 1D 1H NMR measurements each taking five minutes (60 min in total) were carried out successively on an Avance III 500 spectrometer (Bruker BioSpin, Rheinstetten, Germany; 500.13 MHz for 1H) at 25 °C, where water suppression was achieved by 3-9-19 pulse sequence with gradient25. After baseline correction, the spectra were transformed to text files in the format of JCAMP-DX ver. 6.0 (http://www.jcamp-dx.org/). The major regions of the spectra including the peaks of the substrates and products were analyzed through FA7, by inhouse Fortran 90 programs calling IMSL 6.0 subroutines (Visual Numerics, Houston, TX) after compiled by Pro Fortran 13.0 (Absoft, Rochester Hills, MI). The time dependency of the NMR signal intensity in the selected spectral region was composed as data matrix D, with rows representing the chemical shifts and columns representing the reaction times. In the data matrix, the intensity was mean-centered along with the time axis and data points with change in the intensity less than three-times the root mean square (r.m.s.) noise were excluded. For normalization, elements were divided by r.m.s. noise. Then, covariance matrix Z, Z = DT D (1)

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where DT is the transposed matrix of D, was subjected to eigensystem analysis. The obtained sets of eigenvalues and eigenvectors correspond to respective “factors”. The selected eigenvectors are composed as column matrix , with rows representing separate factor(s) and columns representing the reaction time. By an operation = (2) was obtained, with rows representing the chemirow matrix cal shifts and columns representing the factors, where is the transformed matrix of . Note that is identical to the right inverse of , because the row vectors of , i.e., eigenvectors of Z, are orthonormal to one another. Thus, data matrix may be reconstructed as = (3) is the reconstructed data matrix employing selected where factors. The row vectors of matrix show time dependence regarding respective factors, and here called score vectors, while the show spectral profile for the faccolumn vectors of matrix tors, and here called loading vectors. By exponential fitting of the score vector for the factor relevant to the substrate/product conversion (see Fig. 1), the rate for the enzymatic reaction was determined. To estimate the IC50 value for the inhibitor, relationship between rate V and concentration of inhibitor [I] was fitted to an equation deduced from Cheng and Prusoff21, = [] (4)

where V0 is the rate in the absence of inhibitor, which is also treated as a variable in the fitting calculation. It should be noted that, in the original manuscript, V0 and IC50 in the above equation were described as [] = (5) []

where Vmax, [S], and Km stand for maximum velocity in the presence of infinite concentration of substrate, substrate concentration, and Michaelis constant of the substrate, respectively, and [] = !" (1 + ) (6)

where KI is dissociation constant between inhibitor and enzyme. The error level for was estimated by a Monte Calro simulation that randomizes the data as Gaussian distributions with the standard deviation of the initial fitting residuals. Constant-time batch reactions on the 96-well plate. 100 µL solutions of 100 mM sodium phosphate (pH 7.0), 100 µM dcSAM, 50 µM putrescine, 5% DMSO-d6, 100 µM DSS, 1.5– 2.0 µg/mL (44–59 nM) enzyme, and 0–40 µM 4MCHA or 0–4 mM 2H-1,4-benzothiazin-3-amine (Vitas-M Laboratory, Hong Kong) were placed in the wells of a 96-well plate designed for PCR. Incubation at 25 °C for 1 hour and heating at 80 °C for 30 s for stopping the reaction were performed in a thermal cycler (Biometra, Göttingen, Germany). Solutions are injected to NMR sample tubes together with 400 µL each of D2O, and set in the cartridge of 96 tubes for a SampleJet automatic sample changer (Bruker BioSpin). 1D 1H NMR measurements each taking ~30 min were carried out at 25 °C, automatically by ICON-NMR program module on the Avance III 500 spectrometer. FA calculation was carried out essentially as described above, while data matrix D is composed of the spectra obtained at different inhibitor concentrations. To estimate IC50,


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the score vector most influenced by the inhibition (see Fig. 3) was fitted to (7) Y = A ) + B where Y is the intensity in the selected score vector; V is the rate calculated by equation 4, as simultaneously incorporated in the fitting; t is the fixed reaction time; and A and B are variables for fitting, together with IC50. In this fitting, V0 in equation 4 is not a variable, but was determined by real-time NMR method as described above, in advance. The error level for was estimated as described above.

ASSOCIATED CONTENT Supporting Information An additional figure illustrating an inhibitor assay for a fragment compound 2H-1,4-benzothiazin-3-amine by the constant-time batch reaction method. This materials is available free of charge via the Internet at http://pubs.acs.org.

AUTHOR INFORMATION Corresponding Author *E-mail: [email protected]; Tel.: +81-298619473

ACKNOWLEDGMENT This project was supported by Leading Engine program for Accelerating Drug discovery (LEAD) of AIST. We thank members of the Consortium for Neglected Tropical Diseases founded by Astellas Pharma Inc., Drugs for Neglected Diseases initiative (DNDi), Tokyo Institute of Technology, High Energy Accelerator Research Organization, AIST, Nagasaki University, and University of Tokyo, especially, Tomohiko Yamaguchi, Yasushi Amano, and Kazuya Homboh of Astellas Pharma Inc. for helpful discussions and advice.

ABBREVIATIONS 4MCHA, trans-4-methylcyclohexylamine; dcSAM, decarboxylated S-adenosylmethionine; DMSO, dimethylsulfoxide; FA, factor analysis; FBDD, fragment-based drug discovery; HSQC, heteronuclear single-quantum coherence spectroscopy; IC50, the inhibitor concentration causing 50% inhibition; Km, Michaelis constant; MTA, methylthioadenosine; SpdS, Spermidine synthase

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Anal. Chem. 2013, 85, 9439-9443. (9) World Health Organization. Research priorities for Chagas disease, human African trypanosomiasis and leishmaniasis. W. H. O. Tech. Rep. Ser. 2012, 975, i-xii,1-100. (10) Aslett, M.; Aurrecoechea, C.; Berriman, M.; Brestelli, J.; Brunk, B. P.; Carrington, M.; Depledge, D. P.; Fischer, S.; Gajria, B.; Gao, X.; Gardner, M. J.; Gingle, A.; Grant, G.; Harb, O. S.; Heiges, M.; HertzFowler, C.; Houston, R.; Innamorato, F.; Iodice, J.; Kissinger, J. C.; Kraemer, E.; Li, W.; Logan, F. J.; Miller, J. A.; Mitra, S.; Myler, P. J.; Nayak, V.; Pennington, C.; Phan, I.; Pinney, D. F.; Ramasamy, G.; Rogers, M. B.; Roos, D. S.; Ross, C.; Sivam, D.; Smith, D. F.; Srinivasamoorthy, G.; Stoeckert, C. J., Jr.; Subramanian, S.; Thibodeau, R.; Tivey, A.; Treatman, C.; Velarde, G.; Wang, H. TriTrypDB: a functional genomic resource for the Trypanosomatidae. Nucleic Acids Res. 2010, 38, D457462. (11) Shirahata, A.; Morohoshi, T.; Samejima, K. Trans-4methylcyclohexylamine, a potent new inhibitor of spermidine synthase. Chem. Pharm. Bull. (Tokyo) 1988, 36, 3220-3222. (12) Shirahata, A.; Morohohi, T.; Fukai, M.; Akatsu, S.; Samejima, K. Putrescine or spermidine binding site of aminopropyltransferases and competitive inhibitors. Biochem. Pharmacol. 1991, 41, 205-212. (13) Dufe, V. T.; Qiu, W.; Muller, I. B.; Hui, R.; Walter, R. D.; AlKaradaghi, S. Crystal structure of Plasmodium falciparum spermidine synthase in complex with the substrate decarboxylated Sadenosylmethionine and the potent inhibitors 4MCHA and AdoDATO. J. Mol. Biol. 2007, 373, 167-177. (14) Stolowitz, M. L.; Minch, M. J. S-Adenosyl-L-methionine and Sadenosyl-L-homocysteine, an NMR-study. J. Am. Chem. Soc. 1981, 103, 6015-6019. (15) Cornforth, J. W.; Reichard, S. A.; Talalay, P.; Carrell, H. L.; Glusker, J. P. Determination of the absolute configuration at the sulfonium center of S-adenosylmethionine. Correlation with the absolute configuration of the diastereomeric S-carboxymethyl-(S)-methionine salts. J. Am. Chem. Soc. 1977, 99, 7292-7300. (16) Wagner, J.; Hirth, Y.; Piriou, F.; Zakett, D.; Claverie, N.; Danzin, C. N-Acetyl decarboxylated S-adenosylmethionine, a new metabolite of decarboxylated S-adenosylmethionine: isolation and characterization. Biochem. Biophys. Res. Commun. 1985, 133, 546-553. (17) Samejima, K.; Nakazawa, Y. Action of decarboxylated Sadenosylmethionine analogs in the spermidine-synthesizing system from rat prostate. Arch. Biochem. Biophys. 1980, 201, 241-246. (18) Dejima, H.; Kobayashi, M.; Takasaki, H.; Takeda, N.; Shirahata, A.; Samejima, K. Synthetic decarboxylated S-adenosyl-L-methionine as a substrate for aminopropyl transferases. Biol. Pharm. Bull. 2003, 26, 10051008. (19) Wu, H.; Min, J.; Ikeguchi, Y.; Zeng, H.; Dong, A.; Loppnau, P.; Pegg, A. E.; Plotnikov, A. N. Structure and mechanism of spermidine synthases. Biochemistry 2007, 46, 8331-8339. (20) Wüthrich, K. NMR of Proteins and Nucleic Acids. John Wiley & Sons, Inc.: New York, 1986; p 17. (21) Cheng, Y.; Prusoff, W. H. Relationship between the inhibition constant (K1) and the concentration of inhibitor which causes 50 per cent inhibition (I50) of an enzymatic reaction. Biochem. Pharmacol. 1973, 22, 3099-3108. (22) Amano, Y.; Namatame, I.; Tateishi, Y.; Honboh, K.; Tanabe, E.; Niimi, T.; Sakashita, H. Structural insights into the novel inhibition mechanism of Trypanosoma cruzi spermidine synthase. Acta Crystallogr. D Biol. Crystallogr. 2015, 71, 1879-1889. (23) Dalvit, C.; Ardini, E.; Flocco, M.; Fogliatto, G. P.; Mongelli, N.; Veronesi, M. A general NMR method for rapid, efficient, and reliable biochemical screening. J. Am. Chem. Soc. 2003, 125, 14620-14625. (24) Rishton, G. M. Nonleadlikeness and leadlikeness in biochemical screening. Drug Discovery Today 2003, 8, 86-96. (25) Piotto, M.; Saudek, V.; Sklenar, V. Gradient-tailored excitation for single-quantum NMR spectroscopy of aqueous solutions. J. Biomol. NMR 1992, 2, 661-665.



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Figure 2. Inhibitor assay based on real-time NMR. (A) The FA score vectors of the first factors (as in Fig. 1C) for enzymatic reaction in the absence (closed circle) or presence of the inhibitor 4MCHA (0.25 µM: open circle; 0.75 µM: closed square; 2.25 µM: open square; and 6.75 µM: triangle). In this experiment, a solution of 1 mM dcSAM and 0.5 mM putrescine was treated with 0.29 µM enzyme. Intensity was normalized to r.m.s. noise. Exponential curve fitting was used to obtain the rate constants. (B) Relation between inhibitor concentration and rate constants. By curve fitting according to equation 4 shown in the Experimental Section, an IC50 value of 0.62 (± 0.02) µM was derived.

Figure 1. A real-time NMR method detecting the enzymatic reaction. (A) 500 MHz-NMR spectra of the substrate mixture (upper, black; 0.25 mM dcSAM and 0.1 mM putrescine) and those during the reaction (lower), where the initiation time of the measurements are 3 min (dark blue) to 73 min (red) after adding enzyme (1.45 µM), each being separated by 5 min. The peaks due to putrescine, dcSAM, spermidine, and MTA are labeled with p, d, s, and m, respectively. For the methyl proton of dcSAM, R and S configurations around the sulfur atom are indicated in parenthesis. Arrows in the lower panel shows time-dependent decrease and increase in the peak intensities. (B) Loading vectors in factor analysis (FA), representing spectral profile of the respective factors (see Experimental Section). Those relevant for the five largest eigenvalues are selected. The region including the peak due to DMSO (2.67 ppm; marked * in (A)) has been excluded in FA. (C) Score vectors in FA representing time dependence of the factors with the five largest eigenvalues. The kinetic rate constant of the enzymatic reaction was obtained by exponential curve fitting of the score vectors of the first factor. In (B) and (C), intensities are normalized to r.m.s. noise.

Figure 3. Inhibitor assay for 4MCHA based on the constant-time batch reaction. Score vectors (A) and loading vectors (B) of the first (black), second (red), third (blue), fourth (green) and fifth (yellow) factors ordered by eigenvalue. As in Figs. 1 and 2, intensity was normalized to r.m.s. noise. In (B), the left and right panels include peaks originating from S-methyl protons of dcSAM and MTA, respectively (see Fig. 1). In this experiment, a solution of 100 µM dcSAM and 50 µM putrescine was treated with 44 nM enzyme. By curve fitting according to equations 4 and 7 shown in the Experimental Section, an IC50 value of 0.093 (± 0.014) µM was derived. Note that the midpoint of this curve corresponds to a concentration where the peak intensity equals to the average of those in full inhibition and no inhibition, but not to that where the rate constant is half of that in no inhibition–i.e., IC50.


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An NMR Biochemical Assay for Fragment-Based Drug Discovery

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