University of Groningen
Novel peptide replicators from dynamic combinatorial libraries
Altay, Yigit
DOI:
10.33612/diss.90041906
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Altay, Y. (2019). Novel peptide replicators from dynamic combinatorial libraries. University of Groningen. https://doi.org/10.33612/diss.90041906
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296 5. Sustaining a Distribution of Replicators Out of Equilibrium
[25] Wintner, E. A.; Rebek, J. Acta Chem. Scand. 1992, 50, 469-485. [26] Sadownik, J. W.; Mattia, E.;
Nowak, P.; Otto, S. Nat. Chem. 2016, 8, 264 - 269.
[27] Eigen, M. Naturwissenschaften 1971, 58, 465-523.
[28] Eigen, M.; McCaskill, J.; Schus-ter, P. J. Phys. Chem. 1988, 92, 6881-6891.
[29] Eigen, M. Steps towards Life: a Per-pective on Evolution; Oxford Univ. Press: 1992.
[30] Nowak, M. A. Trends Ecol. Evol. 1992, 7, 118-121.
[31] Østman, B.; Olson, R. “Using fit-ness landscapes to visualize evolu-tion in acevolu-tion”, 2014.
[32] Otto, S.; Furlan, R.; Sanders, J. Science 2002, 297, 590-593.
Manuscript in preparation.
Chapter 6
Optical Identification of Self-Replicating
Molecules
“The book of chemistry is not just to be read; it is to be written”
Jean-Marie Lehn
Abstract
Systems chemistry and dynamic combinatorial chemistry offer a wide range of applications of complex molecular systems from ligand identification to self-replication. The development of self-replicating molecules emerging from dy-namic combinatorial libraries has reached a point where statistical analysis on systems is becoming increasingly important. Such analysis requires repetitive sampling and the analysis time associated with the currently used techniques (chromatography, NMR) is prohibitive. In this chapter we show that a com-binatorial fluorescent molecular sensor can successfully discriminate between differently sized replicators made from the same building block as well as same sized replicators with minor structural differences. This method dramatically reduces demands on analysis time and sample amounts compared to currently used methods, enabling experiments on replicators to be performed in a parallel and high-throughput manner.
298 6. Optical Identification of Self-Replicating Molecules
6.1
Introduction
D
ynamic combinatorial chemistry (DCC)1–3 is attracting attention for well over two decades. However, analytical tools that can be used for library analysis remain very limited.4 Analysis of dynamic combinatorial libraries (DCLs) requires quantitative methods that can screen complex molecular mixtures containing large numbers of compounds. So far, liquid chromatography (generally coupled to a mass spectrometer) is by far the most widely used daily analysis technique for DCLs. Ultra performance liquid chromatography (UPLC) instruments provide an excellent solution over high performance liquid chromatography (HPLC) instruments with a shorter run time and with a small sample/injection volume and concentration required for analysis (Table 6.1). However, a single UPLC analysis of a DCL still takes 15 min on average and this becomes a major bottleneck if the statistical analysis of hundreds if not thousands of replicates of an experiment is to be conducted.3There is a growing need for a faster analysis method for DCLs as the need of statistical analysis become more and more crucial.Table 6.1: Comparison of typical parameters of different techniques for the analysis of a single sample. Volumes and concentrations are calculated based on an analysis of a library that is 3.8 mM on building block, as an example.
Parameters Instruments
HPLC UPLC Fluorescence
Plate Reader Run Time 45 min 15 min <1 min
Sampling Volume 50µL 10µL 0.5µL
Injection Volume 20µL 5µL
-Concentration ˜1000µm 100 ´200 µm 30µm
In contrast to chromatographic methods, a fluorescence assay could in principle be a rapid and non-destructive way of monitoring DCLs. Fluorescence assays are widely used to analyze the aggregation state of proteins.5–7 For example, thioflavin T (ThT)8,9 assays are widely used to characterize the β-sheet structure of replicator fibrils that emerge from DCLs. Although ThT can readily sense fibril formation, it cannot distinguish between different “species” and therefore is not suitable for identifying differently sized macrocycles or the same sized macrocycles of different structure. Small molecular sensors, such as ThT, are designed for the detection of specific analytes. In contrast, differential sensors are cross-reactive and thus, they can interact with different components of the DCLs to produce emission patterns
6.1. Introduction 299
that could be used to identify the composition.10–13Furthermore, fluorescence spec-troscopy requires approximately 20 times less sampling volume and analysis can be done at about one order of magnitude lower concentrations compared to liquid chromatography (Table 6.1). So, the design of a differential fluorescent probe that combines distinct probes is a promising approach on the way to fast analysis.
Figure 6.1: (a) Chemical structures of peptide building blocks 1, 2 and 3; (b) schematic representation of the evolution of a dynamic combinatorial library; (c) chemical structure of a combinatorial fluorescent molecular sensor that integrates a bis-KLVFF peptide and three fluorescent reporters: ThT (blue), SRB (green), and sCy5 (magenta); (d) Normalized excitation (dotted line) and emission spectra (solid line) of ThT, SRB, and sCy5 (data taken from a previously published study);13(e) FRET processes that can occur when exciting the
298 6. Optical Identification of Self-Replicating Molecules
6.1
Introduction
D
ynamic combinatorial chemistry (DCC)1–3 is attracting attention for well over two decades. However, analytical tools that can be used for library analysis remain very limited.4 Analysis of dynamic combinatorial libraries (DCLs) requires quantitative methods that can screen complex molecular mixtures containing large numbers of compounds. So far, liquid chromatography (generally coupled to a mass spectrometer) is by far the most widely used daily analysis technique for DCLs. Ultra performance liquid chromatography (UPLC) instruments provide an excellent solution over high performance liquid chromatography (HPLC) instruments with a shorter run time and with a small sample/injection volume and concentration required for analysis (Table 6.1). However, a single UPLC analysis of a DCL still takes 15 min on average and this becomes a major bottleneck if the statistical analysis of hundreds if not thousands of replicates of an experiment is to be conducted.3There is a growing need for a faster analysis method for DCLs as the need of statistical analysis become more and more crucial.Table 6.1: Comparison of typical parameters of different techniques for the analysis of a single sample. Volumes and concentrations are calculated based on an analysis of a library that is 3.8 mM on building block, as an example.
Parameters Instruments
HPLC UPLC Fluorescence
Plate Reader Run Time 45 min 15 min <1 min
Sampling Volume 50µL 10µL 0.5µL
Injection Volume 20µL 5µL
-Concentration ˜1000µm 100 ´200 µm 30µm
In contrast to chromatographic methods, a fluorescence assay could in principle be a rapid and non-destructive way of monitoring DCLs. Fluorescence assays are widely used to analyze the aggregation state of proteins.5–7 For example, thioflavin T (ThT)8,9 assays are widely used to characterize the β-sheet structure of replicator fibrils that emerge from DCLs. Although ThT can readily sense fibril formation, it cannot distinguish between different “species” and therefore is not suitable for identifying differently sized macrocycles or the same sized macrocycles of different structure. Small molecular sensors, such as ThT, are designed for the detection of specific analytes. In contrast, differential sensors are cross-reactive and thus, they can interact with different components of the DCLs to produce emission patterns
6.1. Introduction 299
that could be used to identify the composition.10–13Furthermore, fluorescence spec-troscopy requires approximately 20 times less sampling volume and analysis can be done at about one order of magnitude lower concentrations compared to liquid chromatography (Table 6.1). So, the design of a differential fluorescent probe that combines distinct probes is a promising approach on the way to fast analysis.
Figure 6.1: (a) Chemical structures of peptide building blocks 1, 2 and 3; (b) schematic representation of the evolution of a dynamic combinatorial library; (c) chemical structure of a combinatorial fluorescent molecular sensor that integrates a bis-KLVFF peptide and three fluorescent reporters: ThT (blue), SRB (green), and sCy5 (magenta); (d) Normalized excitation (dotted line) and emission spectra (solid line) of ThT, SRB, and sCy5 (data taken from a previously published study);13(e) FRET processes that can occur when exciting the
300 6. Optical Identification of Self-Replicating Molecules In this study, we use a combinatorial fluorescent molecular sensor14–17 that was
developed by Hatai et al.13 in the Margulies research group to analyze the
compo-sition of DCLs made from peptide 1, 2 and 3. The structure of the sensor consists of synthetic receptors and fluorescent reporters: two short peptide chains with the sequence of KLVFF, which are known to bind amyloids,18 and three fluorescent
probes (thioflavin T (ThT), sulforhodamine B (SRB) and sulfo-Cy5 (sCy5)) that are known to form a F¨orster resonance energy transfer (FRET) donor-acceptor system which increases the efficiency of generated emission patterns.19 We now show that
the sensor is able to interact differently with the different components of the DCLs and the generated fluorescence emission patterns can be used to analyze the library composition.
6.2
Results and Discussion
We chose the most widely studied peptide 1 to study the discrimination efficiency of the combinatorial molecular sensor. For that purpose we set up three different libraries of peptide 1 in borate buffer (3.8 mM, in 50 mM borate buffer): the first library was mechanically agitated for two weeks under slow air oxidation to reach full conversion into 16, the second library was fully oxidized with perborate (3.8 mM)
immediately after the library was set up to obtain a mixture containing mostly 13
and 14. Lastly we set up a fresh library prior to measurements to have a library
dominated by 11. Libraries of peptides 2 and 3 were set up to form replicators
in borate buffer (3.8 mM, in 50 mM borate buffer) and only the resulting octamer replicators were used in our experiments. The monomer of peptide 1, 11, and the
cyclic trimer-tetramer mixture, 13-14, do not self-assemble and they stay in solution
as fully solvated building blocks and macrocycles. In contrast, replicators 16, 28 and
38 are known to self-assemble and form fibrillar structures.20
The ability of the sensor to discriminate between the different replicators and the components of the library was tested using the patterns obtained by measuring flu-orescence intensity changes at eleven representative emission channels (Figure 6.2a). We observed significant fluorescence enhancement for the monomer, 11, only when
the SRB is excited directly. For the 13-14mixture, we observed very strong emission
from the SRB (and sCy5 to a lesser extent) resulting from direct excitation of the fluorophore as well as from energy transfer. Samples containing the replicators (16,
28 and 38) that self-assemble into fibers showed strong emission from the direct
ex-citation of the ThT unit of the sensor. The observed increase in emission at 672 nm shows efficient energy transfer from ThT to sCy5 via SRB. The corresponding linear discriminant analysis (LDA) map in Figure 6.2b clearly shows that not only repli-cators of different size but also replirepli-cators of the same size having minor structural
6.2. Results and Discussion 301 variations in the sequence can be distinguished readily.
Figure 6.2: a) Patterns obtained by measuring fluorescence intensity changes in the pres-ence of libraries made from 1, 2 and 3 at eleven representative emission channels (λexc. =
400 and 530 nm), b) corresponding LDA plot. The fluorescent data for each analyte consists of five repeats.
In order to confirm that the sensor can be used to track the emergence of replica-tors, we prepared libraries having different ratios (Table 6.2) of 13-14and 16 which
302 6. Optical Identification of Self-Replicating Molecules
Table 6.2: Composition of libraries representing different stages of emergence of a replica-tor. These libraries were prepared by mixing a fully oxidized 16 library with a fully oxidized
13-14 library.
No. Library Composition, % 16 13-14 1 100 0 2 75 25 3 50 50 4 25 75 5 0 100
Figure 6.3: a) Patterns obtained by measuring intensity changes of libraries specified in Table 6.2 at eleven representative emission channels (λexc. = 400 and 530 nm), b)
6.3. Conclusions 303 When ThT is excited directly, we observed a decrease in the emission intensity of the ThT unit as the composition of the library went from pure 16 to pure 13
-14. Similarly, the emission intensity of the SRB unit, resulting from energy transfer,
increased as the composition of the library went from pure 16 to pure 13-14 having
the highest emission with the library that contains 25% 16. Emission of the SRB
when the ThT is excited is almost as strong as when the SRB is directly excited. This shows that energy transfer is very efficient. We observed the energy transfer from ThT to sCy5 via SRB to a lesser extent, but with a similar trend observed as for the energy transfer from ThT to SRB. Emission intensities at 674 nm (both resulting from energy transfer) for λexc. = 400 and λexc. = 530 nm are almost identical. The
corresponding linear discriminant analysis (LDA) map in Figure 6.3b clearly shows that the emergence of a replicator can be tracked using the combinatorial fluorescent sensor as the DCLs of 1 with different compositions can be distinguished from each other quite clearly.
Note that this molecular sensor approach cannot be used to identify replicators in a DCL that is made from a novel building block as the analysis is based on reference to previously determined “fingerprints” of previously identified replicators. However, after a DCL has been characterized with standard protocols and methods, fluores-cence measurements can dramatically reduce the time to analyze samples. We noted that the emission fingerprints of 16 in Figure 6.2a and 6.3a differed significantly.
This difference is possibly due to the “age” of the libraries. The experiments cor-responding to Figure 6.2a are done with libraries older than one month and those corresponding to Figure 6.3a are done with freshly prepared libraries. This confirms previous (unpublished) observations made in our group that the CD spectrum of replicator samples can change with time, even though the molecular composition re-mains constant. Thus, the fluorescence array not only reports on replicator identity but also on its mode of assembly.
Compared to chromatographic analysis, fluorimetric analysis reduces the mini-mum concentration of the sample from 100µm - 200 µm to 30 µm, and the minimum amount of sampling volume from 10µL to 0.5 µL which might be further decreased with optimization. Furthermore, the analysis time of a single DCL is reduced from about 15 min to a less than 1 min.
6.3
Conclusions
In conclusion, rapid analysis of mixtures of replicators and their precursors has been demonstrated using the differential sensing ability of the combinatorial molecular sensor. Replicators that have different macrocycle sizes (16 and 28/38) can be
304 6. Optical Identification of Self-Replicating Molecules
differences in their peptide sequence (28 and 38). Unlike with a simple fluorescent sensor such as ThT, which responds in essentially the same way to different self-assembled structures, the emergence of replicators can now be followed optically as the sensor can successfully track libraries that contains various intermediates. Re-placement of chromatographic analysis by fluorimetric analysis reduces the minimum concentration of the sample and the minimum sampling volume. Additionally, the shortened analysis time for a single library now allows analysis of large numbers of samples in a short time. This enables statistical analysis and parallel monitoring of samples of replicators.
6.4
Acknowledgements
Dr. J. Hatai and Dr. L. Motiei are acknowledged for the synthesis of the sensor and in-depth discussions on analysis and interpretation of the data. G. M. Santi-ago is gratefully acknowledged for proof-reading this chapter and for giving precious feedback.
6.5. Materials and Methods 305
6.5
Materials and Methods
6.5.1
Materials
Doubly distilled water was used in all experiments. Boric anhydride (Sigma-Aldrich) and sodium hydroxide (Merck Chemicals) were utilized for buffer preparation and pH adjustments. For UPLC measurements, UPLC grade acetonitrile, water and trifluoroacetic acid were purchased from Biosolve BV.
Peptides 1, 2 and 3 were purchased from Cambridge Peptides Ltd. with a purity higher than 95%. The combinatorial sensor 4 was synthesized by the Margulies research group following published procedures.13
6.6
Determination of the Sensor Concentration
Freeze-dried sensor that was kept at -20˝C in an eppendorf tube was centrifuged (5000 rpm, 2-3 min) to collect all the sample at the bottom. Then 20µL dry DMSO was added (Stock A). To prepare the working solution of stock B, 1µL of Stock A was diluted with 9µL dry DMSO. On a Thermo Scientific NanoDrop instrument, 2 µL of stock B was placed and spectra were taken between 400-800 nm or only at 556 nm (3 replicates). From all the measurements blank spectra were subtracted. The concentration of Stock B was calculated using the extinction coefficient of 76ˆ103 M-1cm-1 at 556 nm. If the absorbance of Stock B at 556 nm was too high (above 1.0) or too low, the volume was adjusted and the procedure was repeated.
6.7
Fluorescence Assays
Fluorescence was measured using a BioTek Synergy H1 microplate reader, in black flat-bottom polystyrene 96-well microplate (Corning). Linear discriminant analysis (LDA) was performed using XLSTAT version 2014.1.01.
The fluorescence spectra were recorded within 1 hour of incubation with different replicator assemblies (30µm) at 4˝C using 2µm sensor. These experiments were per-formed in five replicates. LDA was applied to discriminate between the fluorescence patterns generated at the following excitation and emission wavelengths: λex: 440 nm, λem: 490, 540, 562, 574, 592, 630, 650, 674, 700 nm; and λex: 530 nm, λem: 592 and 674 nm.
304 6. Optical Identification of Self-Replicating Molecules
differences in their peptide sequence (28 and 38). Unlike with a simple fluorescent sensor such as ThT, which responds in essentially the same way to different self-assembled structures, the emergence of replicators can now be followed optically as the sensor can successfully track libraries that contains various intermediates. Re-placement of chromatographic analysis by fluorimetric analysis reduces the minimum concentration of the sample and the minimum sampling volume. Additionally, the shortened analysis time for a single library now allows analysis of large numbers of samples in a short time. This enables statistical analysis and parallel monitoring of samples of replicators.
6.4
Acknowledgements
Dr. J. Hatai and Dr. L. Motiei are acknowledged for the synthesis of the sensor and in-depth discussions on analysis and interpretation of the data. G. M. Santi-ago is gratefully acknowledged for proof-reading this chapter and for giving precious feedback.
6.5. Materials and Methods 305
6.5
Materials and Methods
6.5.1
Materials
Doubly distilled water was used in all experiments. Boric anhydride (Sigma-Aldrich) and sodium hydroxide (Merck Chemicals) were utilized for buffer preparation and pH adjustments. For UPLC measurements, UPLC grade acetonitrile, water and trifluoroacetic acid were purchased from Biosolve BV.
Peptides 1, 2 and 3 were purchased from Cambridge Peptides Ltd. with a purity higher than 95%. The combinatorial sensor 4 was synthesized by the Margulies research group following published procedures.13
6.6
Determination of the Sensor Concentration
Freeze-dried sensor that was kept at -20˝C in an eppendorf tube was centrifuged (5000 rpm, 2-3 min) to collect all the sample at the bottom. Then 20µL dry DMSO was added (Stock A). To prepare the working solution of stock B, 1µL of Stock A was diluted with 9µL dry DMSO. On a Thermo Scientific NanoDrop instrument, 2 µL of stock B was placed and spectra were taken between 400-800 nm or only at 556 nm (3 replicates). From all the measurements blank spectra were subtracted. The concentration of Stock B was calculated using the extinction coefficient of 76ˆ103 M-1cm-1 at 556 nm. If the absorbance of Stock B at 556 nm was too high (above 1.0) or too low, the volume was adjusted and the procedure was repeated.
6.7
Fluorescence Assays
Fluorescence was measured using a BioTek Synergy H1 microplate reader, in black flat-bottom polystyrene 96-well microplate (Corning). Linear discriminant analysis (LDA) was performed using XLSTAT version 2014.1.01.
The fluorescence spectra were recorded within 1 hour of incubation with different replicator assemblies (30µm) at 4˝C using 2µm sensor. These experiments were per-formed in five replicates. LDA was applied to discriminate between the fluorescence patterns generated at the following excitation and emission wavelengths: λex: 440 nm, λem: 490, 540, 562, 574, 592, 630, 650, 674, 700 nm; and λex: 530 nm, λem: 592 and 674 nm.
306 6. Optical Identification of Self-Replicating Molecules
6.8
UPLC and LC-MS analyses
UPLC analyses were performed on a Waters Acquity UPLC I-class and H-class system equipped with a PDA detector. A reversed-phase UPLC column (Aeris 1.7µm. XB-C18 150ˆ 2.10 mm, purchased from Phenomenex) was used in the analyses of all samples, while UV absorbance was monitored at 254 nm. The column temperature was equilibrated at 35˝C prior to injections.
UPLC-MS analyses were performed using a Waters Acquity UPLC H-class system coupled to a Waters Xevo-G2 TOF. The mass spectrometer was operated under the following conditions: electrospray ionization mode: positive; capillary voltage: 2.5 kV; sampling cone voltage: 30 V; extraction cone voltage: 4.0 V. Samples were prepared by dissolving 10µL of a 3.8 mM library in 10 µL DMF and then further diluting them with 180µL UPLC grade water. The operating parameters were the following: eluent flow rate 0.3 mL/min; eluent A: UPLC grade water with 0.1 v% trifluoroacetic acid; eluent B: UPLC grade acetonitrile with 0.1 v% trifluoroacetic acid.
6.8.1
UPLC Methods
Libraries were analysed using the following method (linear gradient) and Phenomenex Aeris Peptide column.
Solvent A: ULC/MS grade water purchased from Biosolve (0.1 v% trifluoroacetic acid added)
Solvent B: ULC/MS grade acetonitrile purchased from Biosolve (0.1 v% triflu-oroacetic acid added)
Table 6.3: Elution profile used for UPLC analyses.
Time, min. A% B% 0.00 90 10 1.00 90 10 1.30 75 25 3.00 72 28 11.00 60 40 11.50 5 95 12.00 5 95 12.50 90 10 17.00 90 10
6.8. UPLC and LC-MS analyses 307
Figure 6.4: UPLC trace (monitored at 254 nm) of the monomer of peptide 1 (3.8 mM in 50 mM borate buffer, pH 8.2).
Figure 6.5: UPLC trace (monitored at 254 nm) of the product mixture (13-14) obtained
by oxidation of peptide 1 in a fully oxidized library (3.8 mM in 50 mM borate buffer, pH 8.2).
Figure 6.6: UPLC trace (monitored at 254 nm) of the hexamer 16obtained by air oxidation
306 6. Optical Identification of Self-Replicating Molecules
6.8
UPLC and LC-MS analyses
UPLC analyses were performed on a Waters Acquity UPLC I-class and H-class system equipped with a PDA detector. A reversed-phase UPLC column (Aeris 1.7µm. XB-C18 150 ˆ 2.10 mm, purchased from Phenomenex) was used in the analyses of all samples, while UV absorbance was monitored at 254 nm. The column temperature was equilibrated at 35˝C prior to injections.
UPLC-MS analyses were performed using a Waters Acquity UPLC H-class system coupled to a Waters Xevo-G2 TOF. The mass spectrometer was operated under the following conditions: electrospray ionization mode: positive; capillary voltage: 2.5 kV; sampling cone voltage: 30 V; extraction cone voltage: 4.0 V. Samples were prepared by dissolving 10µL of a 3.8 mM library in 10 µL DMF and then further diluting them with 180µL UPLC grade water. The operating parameters were the following: eluent flow rate 0.3 mL/min; eluent A: UPLC grade water with 0.1 v% trifluoroacetic acid; eluent B: UPLC grade acetonitrile with 0.1 v% trifluoroacetic acid.
6.8.1
UPLC Methods
Libraries were analysed using the following method (linear gradient) and Phenomenex Aeris Peptide column.
Solvent A: ULC/MS grade water purchased from Biosolve (0.1 v% trifluoroacetic acid added)
Solvent B: ULC/MS grade acetonitrile purchased from Biosolve (0.1 v% triflu-oroacetic acid added)
Table 6.3: Elution profile used for UPLC analyses.
Time, min. A% B% 0.00 90 10 1.00 90 10 1.30 75 25 3.00 72 28 11.00 60 40 11.50 5 95 12.00 5 95 12.50 90 10 17.00 90 10
6.8. UPLC and LC-MS analyses 307
Figure 6.4: UPLC trace (monitored at 254 nm) of the monomer of peptide 1 (3.8 mM in 50 mM borate buffer, pH 8.2).
Figure 6.5: UPLC trace (monitored at 254 nm) of the product mixture (13-14) obtained
by oxidation of peptide 1 in a fully oxidized library (3.8 mM in 50 mM borate buffer, pH 8.2).
Figure 6.6: UPLC trace (monitored at 254 nm) of the hexamer 16obtained by air oxidation
308 6. Optical Identification of Self-Replicating Molecules
Figure 6.7: UPLC traces (monitored at 254 nm) of the product mixtures obtained by mixing libraries of 13-14 (corresponding to Figure 6.5) and 16(corresponding to Figure 6.6)
at different ratios.
Figure 6.8: UPLC trace (monitored at 254 nm) of the octamer 28 obtained by oxidation
of peptide 2 in a 80 mol % pre-oxidized library (3.8 mM in 50 mM borate buffer, pH 8.2) after stirring at 1200 rpm for 14 days.
Figure 6.9: UPLC trace (monitored at 254 nm) of the octamer 38 obtained by oxidation
of peptide 3 in a 80 mol % pre-oxidized library (3.8 mM in 50 mM borate buffer, pH 8.2) after stirring at 1200 rpm for 14 days.
6.9. References 309
6.9
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