A Modular Probe Strategy for Drug Localization, Target Identification

Subscriber access provided by the University of Exeter

Article

A modular probe strategy for drug localization, target identification and target occupancy measurement on single cell level Anna Rutkowska, Douglas W Thomson, Johanna Vappiani, Thilo Werner, Katrin M Mueller, Lars Dittus, Jana Krause, Marcel Muelbaier, Giovanna Bergamini, and Marcus Bantscheff ACS Chem. Biol., Just Accepted Manuscript • DOI: 10.1021/ acschembio.6b00346 • Publication Date (Web): 06 Jul 2016 Downloaded from http://pubs.acs.org on July 8, 2016

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

ACS Chemical Biology is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 23

TOC Figure target identification clickprobe

drug

CLICK

r.i.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58

ACS Chemical Biology

m/z compound localization

target occupancy target

ACS Paragon Plus Environment


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 2 of 23


A modular probe strategy for drug localization, target identification and target occupancy measurement on single cell level Anna Rutkowska1, Douglas W. Thomson1, Johanna Vappiani, Thilo Werner, Katrin M. Mueller, Lars Dittus, Jana Krause, Marcel Muelbaier, Giovanna Bergamini2* and Marcus Bantscheff2* Cellzome GmbH, A GlaxoSmithKline company, Meyerhofstrasse 1, D- 69117 Heidelberg, Germany

1) 2) these authors contributed equally *) Authors for correspondence: [email protected]; [email protected]

Abstract Late stage failures of candidate drug molecules are frequently caused by off-target effects or inefficient target engagement in vivo. In order to address these fundamental challenges in drug discovery, we developed a modular probe strategy based on bioorthogonal chemistry that enables the attachment of multiple reporters to the same probe in cell extracts and live cells. In a systematic evaluation we identified the inverse electron demand Diels−Alder reac-on between transcyclooctene labeled probe molecules and tetrazine-tagged reporters to be the most efficient bioorthogonal reaction for this strategy. Bioorthogonal biotinylation of the probe allows the identification of drug targets in a chemoproteomics competition binding assay using quantitative mass spectrometry. Attachment of a fluorescent reporter enables monitoring of spatial localization of probes as well as drug-target co-localization studies. Finally, direct target occupancy of unlabeled drugs can be determined at single cell resolution by competitive binding with fluorescently labeled probe molecules. The feasibility of the modular probe strategy is demonstrated with non-covalent PARP inhibitors.

Keywords: bioorthogonal chemistry, target identification, target engagement, drug discovery, imaging, click chemistry, TCO, Tetrazine Declaration: The authors are employees of Cellzome GmbH and GlaxoSmithKline. The company funded the work.

1 ACS Paragon Plus Environment

Page 3 of 23

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Introduction Failure of candidate drug molecules in phase II or III clinical trials is amongst the greatest challenges faced by the pharmaceutical industry. Major factors contributing to failures are insufficient proof of target engagement leading to lack of efficacy as well as compound off-target activities leading to adverse events.1,2 Analysis of late stage clinical trials suggest that attrition could be reduced by more comprehensive compound characterization at preclinical stage.3 Chemical probes with excellent cellular activity and selectivity are also invaluable tools for target discovery and validation efforts and chemical biology studies in general.4–6 Target engagement is referred to as the ability of a drug to bind to a cellular target in living systems and is either measured directly or inferred from biomarkers for downstream pathway effects (e.g. phosphorylation of substrate proteins).7,8 Target occupancy measurement refers exclusively to the quantification of target protein directly bound by a drug molecule. Several techniques are currently available to directly quantify target occupancy in cells and tissues.7,8 The close proximity between a ligand and its target protein can be measured using fluorescence or bioluminescence resonance energy transfer (FRET and BRET).9,10 However, these assays require functionalization of both the bioactive molecule of interest and the target protein. Ligand-directed protein labeling is an emerging technology that monitors the interaction of derivatized compounds with endogenous proteins.11 General applicability, however is not yet established. Activity-based profiling enables target engagement measurement in cellular systems with covalently binding probes.12–16 Positron emission tomography (PET) imaging is used to measure target occupancy in vivo17 but requires the use of radio labeled compounds and has limited spatial resolution. Finally, the cellular thermal shift assay (CESTA),18 which is based on altered thermal stability of target proteins induced by binding of a compound,18,19 can monitor the binding of underivatized molecules to endogenous proteins. However not all proteins show a change in thermal stability upon ligand binding and single cell or subcellular resolution cannot be achieved.18,19 Hence, there is a strong need for methods measuring target occupancy at subcellular resolution for underivatized drugs binding to endogenous proteins. Probes designed by chemical functionalization of drugs with reporter tags such as biotin or fluorophores are powerful tools for the characterization of compound-proteins interactions.7,20,21 Bioorthogonal chemistry-enabling probes are particularly attractive since the selective reaction with different modules containing the respective reactive partner group allows testing these probes in a range of cellular assays.22–24 Here we demonstrate that by applying functionalized probes as reporter for target binding in a competition binding format in live cells, it is also possible to measure target occupancy of underivatized drug molecules. 2 ACS Paragon Plus Environment


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 4 of 23

Up to now, more than 20 different bioorthogonal reactions have been published, and significant progress has been made in optimizing reaction rates and selectivity.22,23 Despite these efforts, the reported examples of bioorthogonal reactions for imaging of small molecule-protein binding in cells are mainly restricted to highly over-expressed proteins and metabolites or covalent inhibitors.25,26 Moreover, most bioorthogonal reactions do not perform very well when carried out in live systems because of low reaction yields or increased side-reactions . A notable exception are inverse electron demand Diels Alder (IEA-DA) reactions e.g. of trans-cyclooctenes with monosubstituted tetrazines that have recently been reported to be efficient in living cells.26,27 In this study, we developed a strategy that allows identification of drug mode-of-action and target occupancy measurement of underivatized drugs under physiological conditions, using a single probe molecule (Figure 1). The strategy combines bioorthogonal chemistry with high resolution imaging and mass spectrometry to visualize and quantify drug-target binding in live cells and to identify target and off-targets. Occupancy of an endogenous cellular target with an underivatized drug is measured by the dose-dependent reduction of fluorescence signal originating from a functionalized probe in a competitive binding experiment. The feasibility of our approach was evaluated using non-covalent inhibitors of poly(ADP-ribose)-polymerase 1 (PARP1).28,29


Page 5 of 23

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Results and Discussion Design and synthesis of tool molecules We devised a strategy that enables (1) target/off-target identification; (2) compound localization and co-localization with target in the cell and (3) measurement of target occupancy of underivatized drugs using a single modular probe (Figure 1). The strategy is based on a bioorthogonal chemistryenabling probe (click-probe) derived from a drug molecule of interest that can be functionalized in situ either with tags for affinity purification of target proteins or with fluorophores for high resolution imaging.

Dose-dependent competitive binding with underivatized drug applied in the

chemoproteomics assay allows the determination of target and off-target affinity. When applied on live cells, competitive binding studies in combination with imaging provide an accurate measurement of intracellular target affinity. In a first step, we sought to identify a bioorthogonal reaction that is compatible with all aspects of the outlined strategy. We therefore evaluated a subset of reactions reported to have fast kinetics, high specificity and chemical stability under physiological conditions representing three mechanisms and a total of 6 different reactions (Table 1): 1) the Inverse electron demand Diels-Alder reaction (IEA-DA) between tetrazine (Tz) and either trans-cyclooctene (TCO and TCO*)30,31 or bicycle[6.1.0]nonyne (BCN)32 2) the strain promoted azide alkyne cycloaddition (SPAAC) between an azide and either bicycle[6.1.0]nonyne (BCN) or dibenzocyclooctyl (DBCO)33 3) Copper assisted Huisgen azide-alkyne cycloaddition (CuAAC).34,35 As a model system we chose Olaparib (AZD2281), a non-covalent inhibitor of PARP1 recently approved for the treatment of advanced ovarian cancer,36 since bioorthogonal chemistry-enabling probes derived from Olaparib have been previously reported for target identification and target co-localization studies.37,38 Examples of significant side reactions between bioorthogonal moieties and cellular proteins have been previously reported, limiting their use both in live cells and cell extracts.39,40 We therefore investigated the reactivity of compounds 13-17 (Table S1) containing the bioorthogonal moieties tetrazine (Tz), methyl-tetrazine (Me-Tz), azide, TCO* and BCN with proteins in cell extract (Supporting Information). Streptavidin beads were loaded with biotinylated compounds, incubated with cell extract and washed. Non-covalently bound proteins were eluted with SDS buffer followed by trypsinization while covalently bound proteins were directly trypsinized on the streptavidin matrix (Figure S1). Isobaric mass tag-based quantitative mass spectrometry was used to identify and quantify proteins captured with 13-17 in comparison to the non-reactive control compounds 19 and 20 (Table S1, S4 and Figure S1). Little or no covalent protein binding was observed for all moieties with the exception of a small number of proteins enriched on the BCN containing compound 17 (Supplementary Figure S1). For further studies, we derivatized Olaparib with alkyne, cylooctene or



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 6 of 23

azide moeities and coupled the reporters to azide, Tz and Me-Tz in order to minimize unspecific background. The click-probe molecules 2-9 were synthesized following previously reported synthetic routes (Supporting Information).28,37,41 Affinities of these click-probes for endogenous PARP1 were evaluated in a lysate-based competition binding assay using sepharose-linked PARP inhibitor (Table 1, Figure S2). Increasing free inhibitor concentrations led to dose-dependent reduction in PARP1-binding to the sepharose matrix and was quantified by immunodetection following previously described procedures.42,43 In general, smaller groups such as azide and alkyne were modifying the compound properties less than larger groups such as TCO and TCO* and BCN. Compounds with an alkyl chain spacer between the ligand and TCO, TCO* or BCN moieties compared to those without, were less hydrophobic, more soluble and retained higher target affinity likely because of reduced steric hindrance (compounds 3, 5 and 7 versus 2, 4 and 6, respectively).

Target identification In a first application we evaluated the click-probes in affinity enrichment experiments using cell extracts. Click-probes 2-9 (Table 1) were incubated for 1 hour at 4°C with cell extracts. Subsequently, neutravidin beads loaded with biotin coupled to the respective bioorthogonally reactive partner group, were added and captured PARP1 was quantified by immunostaining. All variants of the IED-DA were performing superior to the other reactions (Figure 2a, Table 1 and Figure S3). Importantly, affinity enrichment of PARP1 with TCO, TCO* and BCN functionalized probes containing alkyl chain spacer (3, 5 and 7) resulted in better yields than with respective probes without spacer (2, 4 and 6). When the less reactive Me-Tz was used instead of Tz the enrichment efficiency of the bioorthogonal reaction was significantly lower with short reaction times (Figure S3a). The only other bioorthogonal reaction that resulted in significant PARP1 enrichment was the SPAAC between azide 8 and DBCO (Figure 2a).33 The amount of affinity purified PARP1 could be significantly increased by using nuclear extract containing higher PARP1 concentration as compared to total cell lysates (Figure S3b). The SPAAC reaction between the BCN and azide groups did not efficiently capture PARP1 up to 90 minutes reaction time. Two well established protocols using THPTA/sodium ascorbate or TBTA/TCEP as ligand/reducing reagent pair were tested for CuAAC.44,45 However, in our hands application of these methods to a non-covalent probe did not provide selective enrichment of endogenous PARP1 and yielded only unspecific background (Figure 2a). Parameters such as incubation time, temperatures and compound concentrations were evaluated but no significant improvement could be achieved. Based on these initial results, we chose to focus on the IED-DA reactions for further development of the target identification assay. 5 ACS Paragon Plus Environment

Page 7 of 23

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


We next devised a strategy for target identification of Olaparib by competitive binding with clickprobes and quantitative mass spectrometry. Similar to previous studies using tool compounds immobilized on a sepharose matrix,43,46 live cells or cell extracts were incubated with free inhibitor over a range of concentrations and a fixed concentration of the corresponding click-probe. Then, streptavidin beads loaded with the corresponding biotinylated bioorthogonal moiety were added, and targets were eluted. Quantitative mass spectrometry was used to identify affinity-captured targets and to measure drug dose-dependent reduction in target binding to the corresponding probe. This setup has several advantages over previously published strategies using very similar Olaparib-derived probe molecules:38 1) It enables the identification of targets of the underivatized compound of interest and not only of the probe. 2) Specific binding of proteins to the drug is readily distinguished from unspecific binding to the bioorthogonal probe or the solid support. 3) Dosedependent experiments enable to determine target affinities. 4) One probe can be used to affinityrank different competitor molecules and to determine selectivity for all probe-captured targets. In a first experiment, cell extract was incubated with the TCO click-probe (3) in the presence or absence of Olaparib (Figure S3c). The quantitative mass spectrometry-based analysis of the proteins specifically competed by Olaparib identified PARP1 as its main target (Figure 2b). Additionally, the close off-targets PARP2 and PARP16, and PARP1 complex members like XCCR5/6 were identified, which is in agreement with previous reports about Olaparib selectivity.38,47 The absolute amount of PARP1 enriched on the click-probe exceeded those of other PARP family members by approximately two orders of magnitude (TOP3 method, Table S2).48 This might be in part explained by the more than 100 fold higher expression levels of PARP1 as compared to PARP2 and PARP16 in HeLa cells (Figure S4).49 Next we investigated how efficiently PARP1 is captured by click-probes 3, 5 and 7 following cellular treatment. HeLa cells were incubated with 1 µM of each probe, subsequently lysed and the bioorthogonal reaction was performed with neutravidin beads functionalized with biotinylated-Tz (13). Immunostaining with PARP1 antibody of SDS eluted proteins produced comparable signals for all three click-probes (Figure 2c). Finally, the target affinity of Olaparib was determined in an intracellular competition experiment using 1 µM of click-probe 3 and a serial dilution array of Olaparib. Immunoblotting and quantitative mass spectrometry analysis determined a PARP1 pEC50 of 8.8 (Figure 2d and S3). These data are in good agreement with lysate-based competitive binding experiments. Signal intensities obtained in cell-based experiments were generally lower than in the lysate experiments and PARP1 was the only Olaparib target identified. These data confirm that in HeLa cell-based experiments the by far predominant fraction of proteinbound Olaparib probe is associated with PARP1.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 8 of 23

In summary, the results obtained in target identification experiments identified probes functionalized with TCO, TCO* or BCN as the most efficient target capturing tools when used in an IED-DA reaction with Tz-modified biotin. The quantitative mass spectrometry-based competition binding method established here is a homogeneous assay enabling the determination of target affinities reflecting the affinity in live cells.

Compound localization in cells Next, we investigated different click-probes in confocal imaging experiments for visualizing subcellular staining and co-localization with PARP1. HeLa cells were incubated with click-probes 2-9 at 2 µM final concentration for 1 hour. The cells were then washed, fixed and permeabilized. Subsequently, the bioorthogonal reaction with the corresponding reactive moiety coupled to a dye reporter was performed. We chose to fix and permeabilize cells because most commercially available reporter-dyes are not plasma membrane permeant and copper assisted click reactions need to be carried out in fixed cells.50–52 Dyes that have been reported to permit intracellular labeling of live cells (TAMRA, fluorescein and BODIPY derivatives)26,53 require extensive washing procedures over several hours to lower the unspecific background, which in case of non-covalent compounds could significantly reduce the efficiency of labeling by washing out the probe. The application of either SPAAC or CuAAC (including picolyl azide)52 reactions resulted in unspecific staining of entire cells rather than the expected nuclear staining54,55 (Figures S5 and S6). This is likely due to low efficiency of the reactions in cells and unspecific interactions between the reporter compounds (dye or bioorthogonal moiety) and cellular components.39,40 In contrast, the IED-DA reaction between TCO (3) and Tz produced specific nuclear staining, which correlated with the cellular localization of PARP1 (Figures 3, S5 and S6). The observed dot-like structures suggest accumulation of PARP1 in nucleoli in line with previous reports.54,55 Nucleolar staining by immunofluorescence was weaker than the probe staining, most probably due to low accessibility of the epitope recognized by the antibody.56 In agreement with the target identification experiments, the inclusion of an alkyl chain spacer between the ligand and bioorthogonal moiety significantly improved signal-to-background ratio in the imaging assay (Figure S6a). The nuclear staining in experiments with TCO* and BCN, was weaker than that with TCO (Figure S6a and Table 1). Further attempts to reduce background showed that only TCO click-probe (3) gave specific staining with Me-Tz-Cy5 dye confirming the superiority of TCO for this application (Figure S5b). Notably, following cell fixation more than 60 % of this probe was still intracellulary bound after washing for up to 6 h as compared to less than 5 % in the absence of fixation (Figure S11).


Page 9 of 23

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Recently reported new versions of trans-cyclooctene (Ag-sTCO, sTCO, dTCO)26,57,58 might enable further improvements in live cell applications but these are not commercially available to date. To summarize, of the tested reagents the bioorthogonal IED-DA between TCO and Tz was the best system for high-resolution imaging of compound-target intracellular co-localization.

Measurement of target occupancy Next, we devised cell-based competition binding assays that enable measurement of target occupancy for covalent and non-covalent compounds using fluorescent probes (Figure S7). Similarly to the target identification assay, a fixed concentration of click-probe and increasing concentrations of a drug of interest compete for binding to the target protein in the live cells. By measuring the residual fluorescent signal of the click-probe EC50 values of the competitor compound can be determined. We started by investigating the compatibility of SPAAC and IED-DA reactions with target occupancy measurements of the covalent Bruton's tyrosine kinase (BTK) inhibitor Ibrutinib (10, table S1). Ibrutinib was recently approved for the treatment of mantle cell lymphoma and chronic lymphocytic leukemia59 and target engagement assays have been reported based on CuAAC-probes and in-gel fluorescence staining.15,16 BV-173 cells were incubated with click-probes 11 (azide) or 12 (TCO) (Figure 4a) at 100 nM in absence or presence of 5 µM Ibrutinib. After cell lysis, probe 11 was reacted with DBCO-functionalized Cy-5 dye and probe 12 was reacted with tetrazine-functionalized Cy-5 dye prior to SDS gel electrophoresis. While both approaches yielded selective staining of BTK, strong background staining was observed for the SPAAC reaction whereas the IED-DA led to substantially better signal-to-background levels (Figure 4b). Incubation of cell samples with Ibrutinib over a range of concentrations and quantification of dose-dependent reduction of the fluorescence signal of either click-probes 11 or 12 allowed a pEC50 of 8.8 to be determined, in line with reported cellular activity of this drug (Figures 4 and S8).15,16 We then rationalized that similar assays combined with imaging of intact cells would enable the measurement of target occupancy also for non-covalent inhibitors such as Olaparib (Figure S7). Moreover, high resolution imaging could enable target occupancy measurements with single cell resolution rather than producing an average value of a heterogeneous population. We focused on the IED-DA reaction with click-probe 3 as this gave the most intense staining in the compound localization studies. Cell samples were treated with 3 at 1 µM, which is the minimum amount required for a robust fluorescent signal and with Olaparib (1) over a concentration range. The bioorthogonal reaction with the dye containing a Tz moiety was then performed on fixed and 8 ACS Paragon Plus Environment


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

permeabilized cells and an Olaparib concentration-dependent decrease of fluorescent staining was measured on individual cell level using confocal microscopy (Figure 5a). By quantification of the fluorescence intensity of several hundred nuclei per condition, an average cellular PARP1 pEC50 9.2 was determined for Olaparib (Figure 5b). Cells showing little or no fluorescent signal were predominantly identified as mitotic cells which had an altered localization of both PARP1 and the click-probe 3 because of the nuclear membrane breakdown (Figure S9a).60 It has to be noted that the concentration of probe used in the target engagement experiments enabled the measurement of low nanomolar intracellular potency for Olaparib indicating that its binding equilibrium with the target was only marginally perturbed by click probe 3. We then used click-probe 3 to measure target occupancy of other structurally distinct PARP1 inhibitors having different potencies in lysate-based assays, Rucaparib (23)61 and PJ34 (24)62 (Table S1). The target affinities measured for these compounds in live cells were lower than that for Olaparib, in agreement with the values obtained in lysate (Figure 5c and S9). This data suggests that this assay enables ranking of compounds by their ability to penetrate into the cell and bind to their cellular target. Finally, we explored the use of FACS to measure dose-dependent target occupancy in single cells. Although subcellular resolution is not possible by FACS, this method presents the advantage of high throughput measurements in suspension cells. Jurkat cells were incubated with a fixed concentration of click-probe 3 and a range of concentrations of either Olaparib, Rucaparib or PJ34. The derived pEC50 values were in good agreement to those determined using fluorescence microscopy, demonstrating the suitability of FACS for this assay (Figure 5d and S10). FACS based quantification of target occupancy could be particularly attractive in clinical research as measurements can be automated and the sensitivity of the technique enables analysis of patient samples. Further optimization of this methodology for in vivo monitoring of target could enable the development of novel biomarkers.

Conclusions The ability to directly correlate target occupancy with any cellular effect induced by a drug represents a powerful way to assess translation across systems, from in vitro models to in vivo studies, with the potential to significantly reduce attrition in the drug discovery processes. In this respect bioorthogonal chemistry opens new exciting perspectives for basic and drug discovery research. We systematically evaluated a number of bioorthogonal reactions for compatibility with a modular probe strategy that enables the attachment of multiple reporter moieties to the same probe in cell extracts and live cells. In line with previous reports we identified the IED-DA reaction between TCO 9 ACS Paragon Plus Environment

Page 10 of 23

Page 11 of 23

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


and Tz tagged molecules as the most suitable for our purposes enabling efficient bioorthogonal reactions in live cells with excellent selectivity.26,27 Co-incubation of cells with underivatized PARP inhibitor and the derived click-probe enabled the identification by quantitative mass spectrometry of the click-probe targets that are also bound by the free drug. Importantly, relative quantification of proteins identified PARP1 to be substantially more abundant after affinity enrichment as compared to other PARP family members displaying similar affinities. These data indicated that the fluorescence signal observed when using an imaging readout, was predominantly deriving from PARP1. In agreement with this, confocal microscopy showed excellent co-localization of the click-probe and PARP1. In a cellular competitive binding assay, the fraction of PARP1 occupied by the free drug could then be quantified in each single cell by measuring the loss of fluorescence signal of the corresponding dyecoupled click-probe either by microscopy or FACS. In contrast to the target identification assay, the fluorescence detection methods are applied on fixed cells which have largely preserved intracellular protein localization. Furthermore, this approach allowed ranking of different inhibitors in cells using the same probe which could be valuable to support lead optimization efforts. It should be noted, though, that expanding the described strategy for measuring target occupancy to other probes and targets requires a level of probe characterization similar to what we have described above for PARP1 clickprobes. This includes the analysis of target and off-target expression, probe selectivity as well as probe target co-localization in the cell system of choice.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 12 of 23

Methods See Supporting information for additional methods. Target identification assays. Compounds 2-7 (1 µM) and Olaparib (10-20 µM) were spiked into HeLa lysate and incubated for 1 h at 4°C. Streptavidin beads pre-incubated with respective biotincompounds (13-15, 17,18, 30mM stock in DMSO) were equilibrated in lysis buffer, loaded onto a 96well filter plate (Millipore) and incubated with cell extract to enable the respective bioorthogonal reactions. IED-DA: 30 min at 4°C, SPAAC: 45min at room temperature (RT), CuAAC: 90min at RT in the presence of a) CuSO4 (0.2 mM), THPTA (1 mM), sodium ascorbate (2 mM) or b) CuSO4 (1mM), TBTA (0.1 mM) and TCEP (1 mM). Beads were then washed three times with lysis buffer and eluted with 75µL of 2X-LDS sample buffer with DTT. Eluted proteins were separated on NuPAGE 4-12% (Invitrogen), transferred to a membrane and immunostained for PARP1 (Santa Cruz, sc-25780). Blots were analyzed on an Odyssey Scanner (LI-COR). For protein staining the Pierce Silver Stain kit (Thermo Scientific) was used. For target identification in compound-treated cells, HeLa cells were incubated for 1 hour with media containing 1 µM compound 3 and various concentrations of Olaparib (compound 1, 400nM – 0.098nM; dilution: 1/8). Cells were then washed, pelleted and lysed. The affinity enrichment and analysis was performed as described above. Procedures for sample preparation, quantitative mass spectrometry and data analysis are detailed in the Supporting information. Imaging assay. HeLa cells were incubated for 1 hour with media containing compounds 2-9 (2 µM). Cells were then washed with fresh medium and PBS to remove unbound compound. After fixation with 4% paraformaldehyde and permeabilization (0.5% Triton/PBS) the respective bioorthogonal reaction with reporter-dye was performed at 25°C. For IED-DA reaction cells were incubated with 100 nM Tetrazine-Cy5 for 5 min at RT. Cells were then washed 5 times with PBS containing 0.1% Tween and Hoechst staining was performed. Images were acquired with a Zeiss LSM 780 microscope with excitation at 633nm and 405nm. The data was analyzed using ImageJ. Cellular target occupancy measurement. Experiments were performed as described above but cells were treated with media containing compound 3 (1 µM) and a concentration range of Olaparib (starting concentration 0.25 µM), Rucaparib (1.25 µM) or PJ34 (10 µM) applying 1:5 dilution steps for a total of 8 data point. For microscopy read-out: 6 to 8 images were recorded per condition and data was analyzed using the ImageJ and the CellProfiler software. Mean fluorescence intensity of labeled probe (Cy5 channel) was measured for each nucleus and these values were used for pEC50 calculation (Graph Pad Prism software). Concentration-response curves were fitted using a four-parameter non11 ACS Paragon Plus Environment

Page 13 of 23

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


linear regression fitting module. For FACS read-out: Cells were excited with a red laser (635 nm) and Cy5 fluorescence was detected using a 660/20 band pass filter (FL4-H channel). A total of 20,000 events were collected for each sample, and the forward- and side-scatter properties were used to exclude dead cells and debris during analysis. A gate for Cy5-positive cells was defined in a FL1H/FL4-H scatter plot and the percentage of Cy5-positive cells among all cells was calculated based on the number of events recorded within that gate. The data were analyzed using GraphPad Prism as described above.

Acknowledgments We would like to thank M. Klös-Hudak, and T. Rudi for help with sample preparation, M. Boesche for operating LC-MS instruments; C. Tischer from ALMF EMBL for imaging analysis; Carola Doce for data analysis; A. Rueger for synthesis of compound 12; J. Stuhlfauth, N. Garcia-Alltrieth and K. Bess for cells and lysates.

Author Contributions AR designed experiments and performed the microscopy assay, JV performed affinity enrichment experiments. DT and MM designed and synthesized compounds KM, LD and JK contributed to experiments. TW performed mass spectrometry analysis. GB and MB conceptualized the study. AR, JV, DT, TW, GB and MB analyzed data, AR, DT, GB and MB wrote the manuscript.

Supporting Information: Detailed Materials and Method section; structure and synthesis of all compounds used in the study, supplementary Figures, supplementary datasets detailing results of all proteomics experiments. This material is available free of charge via the Internet http://pubs.acs.org.

All authors are employees are employees and/or shareholders of Cellzome GmbH and GlaxoSmithKline. The companies funded the work.



O NH N

Table 1. Structures of click- probes and summary of results

O N F

N

R O

Compound

R

number 1 (Olaparib)

2

TCO

PARP1

Chrom

Solubility

pIC50

logD

(µM)

Reaction names and bioorthogonal moiety on reporter1)

8.8 ±0.7

2.4

453

na2)

6.9 ±0.7

5.5

76

7.5 ±0.2

3.7

266

6.6 ±0.4

5.4

51

8.0 ±0.7

3.7

307

+++

++

6.5 ±0.3

n.d.

n.d.

++

+

+++

+

-

-

+/++

-

-

-

-

-

Efficiency in target identification assay

Signal intensity in compound visualization assay

Na

Na

++

++

+++

+++

+

+

TCO 3

4

TCO*

TCO* 5

6

BCN

tetrazine

IED-DA1)

BCN 7

7.1 ±0.3

3.5

203

SPAAC1)

Azide DBCO

Azide

8

8.6 ±0.7

2.5

376 Alkyne CuAAC1)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 14 of 23

Alkyne 9

8.9 ±0.8

1.7

Azide

483

1)

IED-DA: the Inverse electron demand Diels-Alder; SPAAC: strain promoted azide alkyne cycloaddition; CuAAC:

2)

na: not applicable

Copper assisted Huisgen azide-alkyne cycloaddition


Page 15 of 23

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 1. A single functionalized probe containing a bioorthogonal moiety (click-probe) can be used for three different assays in live cells: (1) target/off-target identification; (2) compound colocalization with the target protein, (3) measurement of target occupancy of unmodified compounds. For target identification, cells are incubated with unmodified drug at a range of concentrations, then washed and lysed. The subsequent click reaction with affinity-reporters enables the identification of drug targets and off-targets in an affinity enrichment-based chemoproteomics approach. Attachment of a fluorophore to the click-probe allows localization of the probe inside cells by confocal microscopy and target occupancy is determined by measuring the reduction of the localized fluorescence signal in the presence of unmodified drug.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 16 of 23

Figure 2. Target and off-target identification assay. a) Comparison of the efficiency of IED-DA, SPAAC and CuAAC reactions in the affinity enrichment assay. HuT78 nuclear lysate was incubated with the indicated click-probes (3, 8, 9) and subsequently the bioorthogonal partner groups coupled to biotin and immobilized on neutravidin beads was added. Enrichment of PARP1 was detected in the elution fractions by immunostaining and quantified by densitometry. The target enrichment efficiency was calculated from Parp1 signal intensities achieved with each probe relative to the clickprobe 3 and biotin-Tz experiment. In the CuAAC reactions, unspecific binding of the target could be observed even in the absence of the click-probes. b) Identification of Olaparib targets. HeLa lysate was incubated with click-probe 3 (1 µM) in the presence or absence of Olaparib (20 µM). Affinity enrichment was performed using the IED-DA reaction between click-probe 3 and biotin-Tz. Captured proteins were trypsinized and analyzed by quantitative mass spectrometry. The scatter plot displays altered relative abundance of identified proteins in the presence of Olaparib as compared to vehicle. The size of the closed circles represents the amounts of affinity enriched protein based on signal intensity in the mass spectrometer. c) Comparison of different IED-DA reactions for target identification after cellular treatment. HeLa cells were treated with 1µM click-probe 3, 5 or 7. After lysis and affinity enrichment using biotin-Tz coupled neutravidin beads, eluates were analyzed using immunostaining. d) Cellular PARP1 affinity of Olaparib. HeLa cells were treated with 1 µM clickprobe 3 in the presence of different concentrations of Olaparib (0-400 nM). After cell lysis and target enrichment using the IED-DA reaction with biotin-Tz coupled streptavidin beads, bound proteins were analyzed by quantitative mass spectrometry. The plot shows the resulting competition binding curve of PARP1 with pIC50=8.8 for Olaparib (n=1; replicate reported in Figure S3f).


Page 17 of 23

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 3. Compound localization. HeLa cells were treated with 2 μM click-probe 3 for 60 min followed by fixation, permeabilization and click reaction with 100 nM Cy5-Tz for 5 min. Subsequently, immunofluorescence staining with anti-PARP1 antibody and Alexa488 conjugated secondary antibody was performed overnight. Representative fluorescent images recorded after excitation at 633nm (Cy5, left panel) and at 488 nm (Alexa 488, right panel) are shown. The plasma membrane of an exemplary cell is marked with dashed line. Scale bar = 25 μm.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 18 of 23

Figure 4. Target occupancy assay for covalent compounds. a) Click-probes derived from Ibrutinib; b) Comparison of signal-to-noise levels between SPAAC and IED-DA reactions for in-gel fluorescence staining of the Ibrutinib target BTK. BV-173 lysate was treated with click-probe 11 or 12 and Ibrutinib as indicated. Subsequently, dye-reporters Cy5.5-DBCO or Cy5-Tz were added and click reactions were performed. Fluorescently labeled proteins were resolved by SDS-PAGE and detected via in-gel fluorescence. c) Target occupancy measurement. BV173 cells were treated for 60 min with vehicle control, 0.1 μM click-probe 11 or 12 in the presence of different concentrations of Ibrutinib (0 – 25 nM) followed by washing, lysis and in vitro click reaction with Cy5.5-DBCO or Cy5-Tz, respectively. Fluorescently labeled proteins were resolved by SDS-PAGE and detected via in-gel fluorescence. The competition binding curve was derived from the fluorescent intensity of the band corresponding to BTK (Figure S8).


Page 19 of 23

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 5. Cellular target occupancy assays for non-covalent PARP1 inhibitors. a) Fluorescent images of HeLa cells treated for 60 min with DMSO or 1 μM click-probe 3 in the presence of the indicated concentrations of Olaparib followed by fixation, permeablization and click reaction with 100 nM Cy5Tz for 5 min. Scale bar = 50 μm. b) Box plot showing mean fluorescence of individual nuclei (n=300520) at different concentrations of Olaparib. The distribution of individual values is shown as histograms superimposed on the box plot. Plotted data are derived from one representative experiment performed as described in (a). c) Competition binding curves of Olaparib (black squares), Rucaparib (red circles) and PJ34 (blue triangles) derived from the fluorescence signal obtained by confocal microscopy of one representative experiment performed as described in (a) (three independent experiments in Figure S9c). d) Flow cytometric analysis of Jurkat cells treated as in (a). Representative graphs showing cells treated with DMSO (left panel) or click-probe 3 labeled cells (right panel). Competition binding curves for Olaparib, Rucaparib, and PJ34 were calculated based on the percentage of Cy5-positive cells (FL4-H) among all cells as defined by the gate boundaries indicated in the graphs.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 20 of 23

References (1) Arrowsmith, J., and Miller, P. (2013) Trial Watch: Phase II and Phase III attrition rates 2011-2012. Nat. Rev. Drug Discov. 12, 569–569. (2) Allison, M. (2012) Reinventing clinical trials. Nat. Biotechnol. 30, 41–49. (3) Morgan, P., Van Der Graaf, P. H., Arrowsmith, J., Feltner, D. E., Drummond, K. S., Wegner, C. D., and Street, S. D. A. (2012) Can the flow of medicines be improved? Fundamental pharmacokinetic and pharmacological principles toward improving Phase II survival. Drug Discov. Today 17, 419–424. (4) Arrowsmith, C. H., Audia, J. E., Austin, C., Baell, J., Bennett, J., Blagg, J., Bountra, C., Brennan, P. E., Brown, P. J., Bunnage, M. E., Buser-Doepner, C., Campbell, R. M., Carter, A. J., Cohen, P., Copeland, R. A., Cravatt, B., Dahlin, J. L., Dhanak, D., Edwards, A. M., Frederiksen, M., Frye, S. V., Gray, N., Grimshaw, C. E., Hepworth, D., Howe, T., Huber, K. V. M., Jin, J., Knapp, S., Kotz, J. D., Kruger, R. G., Lowe, D., Mader, M. M., Marsden, B., Mueller-Fahrnow, A., Müller, S., O’Hagan, R. C., Overington, J. P., Owen, D. R., Rosenberg, S. H., Ross, R., Roth, B., Schapira, M., Schreiber, S. L., Shoichet, B., Sundström, M., Superti-Furga, G., Taunton, J., Toledo-Sherman, L., Walpole, C., Walters, M. A., Willson, T. M., Workman, P., Young, R. N., and Zuercher, W. J. (2015) The promise and peril of chemical probes. Nat. Chem. Biol. 11, 536–541. (5) Bunnage, M. E., Chekler, E. L. P., and Jones, L. H. (2013) Target validation using chemical probes. Nat. Chem. Biol. 9, 195–199. (6) Frye, S. V. (2010) The art of the chemical probe. Nat. Chem. Biol. 6, 159–161. (7) Simon, G. M., Niphakis, M. J., and Cravatt, B. F. (2013) Determining target engagement in living systems. Nat. Chem. Biol. 9, 200–205. (8) Schürmann, M., Janning, P., Ziegler, S., and Waldmann, H. (2016) Small-Molecule Target Engagement in Cells. Cell Chem. Biol. 0. (9) Sun, Y., Hays, N. M., Periasamy, A., Davidson, M. W., and Day, R. N. (2012) Chapter nineteen Monitoring Protein Interactions in Living Cells with Fluorescence Lifetime Imaging Microscopy, in Methods in Enzymology (conn, P. M., Ed.), pp 371–391. Academic Press. (10) Robers, M. B., Dart, M. L., Woodroofe, C. C., Zimprich, C. A., Kirkland, T. A., Machleidt, T., Kupcho, K. R., Levin, S., Hartnett, J. R., Zimmerman, K., Niles, A. L., Ohana, R. F., Daniels, D. L., Slater, M., Wood, M. G., Cong, M., Cheng, Y.-Q., and Wood, K. V. (2015) Target engagement and drug residence time can be observed in living cells with BRET. Nat. Commun. 6, 10091. (11) Tsukiji, S., and Hamachi, I. (2014) Ligand-directed tosyl chemistry for in situ native protein labeling and engineering in living systems: from basic properties to applications. Curr. Opin. Chem. Biol. 21, 136–143. (12) Cohen, M. S., Hadjivassiliou, H., and Taunton, J. (2007) A clickable inhibitor reveals contextdependent autoactivation of p90 RSK. Nat. Chem. Biol. 3, 156–160. (13) Shi, H., Zhang, C.-J., Chen, G. Y. J., and Yao, S. Q. (2012) Cell-Based Proteome Profiling of Potential Dasatinib Targets by Use of Affinity-Based Probes. J. Am. Chem. Soc. 134, 3001–3014. (14) Yang, P.-Y., Liu, K., Ngai, M. H., Lear, M. J., Wenk, M. R., and Yao, S. Q. (2010) Activity-Based Proteome Profiling of Potential Cellular Targets of Orlistat − An FDA-Approved Drug with Anti-Tumor Activities. J. Am. Chem. Soc. 132, 656–666. (15) Lanning, B. R., Whitby, L. R., Dix, M. M., Douhan, J., Gilbert, A. M., Hett, E. C., Johnson, T. O., Joslyn, C., Kath, J. C., Niessen, S., Roberts, L. R., Schnute, M. E., Wang, C., Hulce, J. J., Wei, B., Whiteley, L. O., Hayward, M. M., and Cravatt, B. F. (2014) A road map to evaluate the proteome-wide selectivity of covalent kinase inhibitors. Nat. Chem. Biol. 10, 760–767. (16) Liu, N., Hoogendoorn, S., Kar, B. van de, Kaptein, A., Barf, T., Driessen, C., Filippov, D. V., Marel, G. A. van der, Stelt, M. van der, and Overkleeft, H. S. (2015) Direct and two-step bioorthogonal probes for Bruton’s tyrosine kinase based on ibrutinib: a comparative study. Org. Biomol. Chem. 13, 5147–5157. (17) Hargreaves, R. J., and Rabiner, E. A. (2014) Translational PET imaging research. Neurobiol. Dis. 61, 32–38.


Page 21 of 23

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(18) Molina, D. M., Jafari, R., Ignatushchenko, M., Seki, T., Larsson, E. A., Dan, C., Sreekumar, L., Cao, Y., and Nordlund, P. (2013) Monitoring Drug Target Engagement in Cells and Tissues Using the Cellular Thermal Shift Assay. Science 341, 84–87. (19) Savitski, M. M., Reinhard, F. B. M., Franken, H., Werner, T., Savitski, M. F., Eberhard, D., Molina, D. M., Jafari, R., Dovega, R. B., Klaeger, S., Kuster, B., Nordlund, P., Bantscheff, M., and Drewes, G. (2014) Tracking cancer drugs in living cells by thermal profiling of the proteome. Science 346, 1255784. (20) Su, Y., Ge, J., Zhu, B., Zheng, Y.-G., Zhu, Q., and Yao, S. Q. (2013) Target identification of biologically active small molecules via in situ methods. Curr. Opin. Chem. Biol. 17, 768–775. (21) Lee, J., and Bogyo, M. (2013) Target deconvolution techniques in modern phenotypic profiling. Curr. Opin. Chem. Biol. 17, 118–126. (22) Lang, K., and Chin, J. W. (2014) Bioorthogonal Reactions for Labeling Proteins. ACS Chem. Biol. 9, 16–20. (23) Patterson, D. M., Nazarova, L. A., and Prescher, J. A. (2014) Finding the Right (Bioorthogonal) Chemistry. ACS Chem. Biol. 9, 592–605. (24) Sletten, E. M., and Bertozzi, C. R. (2011) From Mechanism to Mouse: A Tale of Two Bioorthogonal Reactions. Acc. Chem. Res. 44, 666–676. (25) Grammel, M., and Hang, H. C. (2013) Chemical reporters for biological discovery. Nat. Chem. Biol. 9, 475–484. (26) Murrey, H. E., Judkins, J. C., am Ende, C. W., Ballard, T. E., Fang, Y., Riccardi, K., Di, L., Guilmette, E. R., Schwartz, J. W., Fox, J. M., and Johnson, D. S. (2015) Systematic Evaluation of Bioorthogonal Reactions in Live Cells with Clickable HaloTag Ligands: Implications for Intracellular Imaging. J. Am. Chem. Soc. 137, 11461–11475. (27) Rossin, R., van den Bosch, S. M., ten Hoeve, W., Carvelli, M., Versteegen, R. M., Lub, J., and Robillard, M. S. (2013) Highly Reactive trans-Cyclooctene Tags with Improved Stability for Diels–Alder Chemistry in Living Systems. Bioconjug. Chem. 24, 1210–1217. (28) Menear, K. A., Adcock, C., Boulter, R., Cockcroft, X., Copsey, L., Cranston, A., Dillon, K. J., Drzewiecki, J., Garman, S., Gomez, S., Javaid, H., Kerrigan, F., Knights, C., Lau, A., Loh, V. M., Matthews, I. T. W., Moore, S., O’Connor, M. J., Smith, G. C. M., and Martin, N. M. B. (2008) 4-[3-(4Cyclopropanecarbonylpiperazine-1-carbonyl)-4-fluorobenzyl]-2H-phthalazin-1-one: A Novel Bioavailable Inhibitor of Poly(ADP-ribose) Polymerase-1. J. Med. Chem. 51, 6581–6591. (29) Rouleau, M., Patel, A., Hendzel, M. J., Kaufmann, S. H., and Poirier, G. G. (2010) PARP inhibition: PARP1 and beyond. Nat. Rev. Cancer 10, 293–301. (30) Nikić, I., Plass, T., Schraidt, O., Szymański, J., Briggs, J. A. G., Schultz, C., and Lemke, E. A. (2014) Minimal Tags for Rapid Dual-Color Live-Cell Labeling and Super-Resolution Microscopy. Angew. Chem. Int. Ed. 53, 2245–2249. (31) Blackman, M. L., Royzen, M., and Fox, J. M. (2008) Tetrazine Ligation: Fast Bioconjugation Based on Inverse-Electron-Demand Diels−Alder Reac-vity. J. Am. Chem. Soc. 130, 13518–13519. (32) Dommerholt, J., Schmidt, S., Temming, R., Hendriks, L. J. A., Rutjes, F. P. J. T., van Hest, J. C. M., Lefeber, D. J., Friedl, P., and van Delft, F. L. (2010) Readily Accessible Bicyclononynes for Bioorthogonal Labeling and Three-Dimensional Imaging of Living Cells. Angew. Chem. Int. Ed. 49, 9422–9425. (33) Debets, M. F., Berkel, S. S. van, Schoffelen, S., Rutjes, F. P. J. T., Hest, J. C. M. van, and Delft, F. L. van. (2010) Aza-dibenzocyclooctynes for fast and efficient enzyme PEGylation via copper-free (3+2) cycloaddition. Chem. Commun. 46, 97–99. (34) Rostovtsev, V. V., Green, L. G., Fokin, V. V., and Sharpless, K. B. (2002) A Stepwise Huisgen Cycloaddition Process: Copper(I)-Catalyzed Regioselective “Ligation” of Azides and Terminal Alkynes. Angew. Chem. Int. Ed. 41, 2596–2599. (35) Wang, Q., Chan, T. R., Hilgraf, R., Fokin, V. V., Sharpless, K. B., and Finn, M. G. (2003) Bioconjugation by Copper(I)-Catalyzed Azide-Alkyne [3 + 2] Cycloaddition. J. Am. Chem. Soc. 125, 3192–3193. 20 ACS Paragon Plus Environment


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 22 of 23

(36) Gunderson, C. C., and Moore, K. N. (2015) Olaparib: an oral PARP-1 and PARP-2 inhibitor with promising activity in ovarian cancer. Future Oncol. 11, 747–757. (37) Reiner, T., Earley, S., Turetsky, A., and Weissleder, R. (2010) Bioorthogonal Small-Molecule Ligands for PARP1 Imaging in Living Cells. ChemBioChem 11, 2374–2377. (38) Yang, K. S., Budin, G., Tassa, C., Kister, O., and Weissleder, R. (2013) Bioorthogonal Approach to Identify Unsuspected Drug Targets in Live Cells. Angew. Chem. Int. Ed. 52, 10593–10597. (39) Beatty, K. E., Fisk, J. D., Smart, B. P., Lu, Y. Y., Szychowski, J., Hangauer, M. J., Baskin, J. M., Bertozzi, C. R., and Tirrell, D. A. (2010) Live-Cell Imaging of Cellular Proteins by a Strain-Promoted Azide–Alkyne Cycloaddition. ChemBioChem 11, 2092–2095. (40) van Geel, R., Pruijn, G. J. M., van Delft, F. L., and Boelens, W. C. (2012) Preventing Thiol-Yne Addition Improves the Specificity of Strain-Promoted Azide–Alkyne Cycloaddition. Bioconjug. Chem. 23, 392–398. (41) Kim, E., Yang, K. S., Giedt, R. J., and Weissleder, R. (2014) Red Si–rhodamine drug conjugates enable imaging in GFP cells. Chem. Commun. 50, 4504–4507. (42) Bergamini, G., Bell, K., Shimamura, S., Werner, T., Cansfield, A., Müller, K., Perrin, J., Rau, C., Ellard, K., Hopf, C., Doce, C., Leggate, D., Mangano, R., Mathieson, T., O’Mahony, A., Plavec, I., Rharbaoui, F., Reinhard, F., Savitski, M. M., Ramsden, N., Hirsch, E., Drewes, G., Rausch, O., Bantscheff, M., and Neubauer, G. (2012) A selective inhibitor reveals PI3Kγ dependence of TH17 cell differentiation. Nat. Chem. Biol. 8, 576–582. (43) Bantscheff, M., Eberhard, D., Abraham, Y., Bastuck, S., Boesche, M., Hobson, S., Mathieson, T., Perrin, J., Raida, M., Rau, C., Reader, V., Sweetman, G., Bauer, A., Bouwmeester, T., Hopf, C., Kruse, U., Neubauer, G., Ramsden, N., Rick, J., Kuster, B., and Drewes, G. (2007) Quantitative chemical proteomics reveals mechanisms of action of clinical ABL kinase inhibitors. Nat. Biotechnol. 25, 1035– 1044. (44) Hong, V., Presolski, S. I., Ma, C., and Finn, M. G. (2009) Analysis and Optimization of CopperCatalyzed Azide–Alkyne Cycloaddition for Bioconjugation. Angew. Chem. Int. Ed. 48, 9879–9883. (45) Speers, A. E., and Cravatt, B. F. (2009) Activity-Based Protein Profiling (ABPP) and Click Chemistry (CC)-ABPP by MudPIT Mass Spectrometry. Curr. Protoc. Chem. Biol. 1, 29–41. (46) Bantscheff, M., Hopf, C., Savitski, M. M., Dittmann, A., Grandi, P., Michon, A.-M., Schlegl, J., Abraham, Y., Becher, I., Bergamini, G., Boesche, M., Delling, M., Dümpelfeld, B., Eberhard, D., Huthmacher, C., Mathieson, T., Poeckel, D., Reader, V., Strunk, K., Sweetman, G., Kruse, U., Neubauer, G., Ramsden, N. G., and Drewes, G. (2011) Chemoproteomics profiling of HDAC inhibitors reveals selective targeting of HDAC complexes. Nat. Biotechnol. 29, 255–265. (47) Wahlberg, E., Karlberg, T., Kouznetsova, E., Markova, N., Macchiarulo, A., Thorsell, A.-G., Pol, E., Frostell, Å., Ekblad, T., Öncü, D., Kull, B., Robertson, G. M., Pellicciari, R., Schüler, H., and Weigelt, J. (2012) Family-wide chemical profiling and structural analysis of PARP and tankyrase inhibitors. Nat. Biotechnol. 30, 283–288. (48) Silva, J. C., Gorenstein, M. V., Li, G.-Z., Vissers, J. P. C., and Geromanos, S. J. (2006) Absolute Quantification of Proteins by LCMSE A Virtue of Parallel ms Acquisition. Mol. Cell. Proteomics 5, 144– 156. (49) Wilhelm, M., Schlegl, J., Hahne, H., Gholami, A. M., Lieberenz, M., Savitski, M. M., Ziegler, E., Butzmann, L., Gessulat, S., Marx, H., Mathieson, T., Lemeer, S., Schnatbaum, K., Reimer, U., Wenschuh, H., Mollenhauer, M., Slotta-Huspenina, J., Boese, J.-H., Bantscheff, M., Gerstmair, A., Faerber, F., and Kuster, B. (2014) Mass-spectrometry-based draft of the human proteome. Nature 509, 582–587. (50) Hong, V., Steinmetz, N. F., Manchester, M., and Finn, M. G. (2010) Labeling Live Cells by CopperCatalyzed Alkyne−Azide Click Chemistry. Bioconjug. Chem. 21, 1912–1916. (51) Kennedy, D. C., Lyn, R. K., and Pezacki, J. P. (2009) Cellular Lipid Metabolism Is Influenced by the Coordination Environment of Copper. J. Am. Chem. Soc. 131, 2444–2445. (52) Uttamapinant, C., Tangpeerachaikul, A., Grecian, S., Clarke, S., Singh, U., Slade, P., Gee, K. R., and Ting, A. Y. (2012) Fast, Cell-Compatible Click Chemistry with Copper-Chelating Azides for Biomolecular Labeling. Angew. Chem. Int. Ed. 51, 5852–5856. 21 ACS Paragon Plus Environment

Page 23 of 23

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(53) Yao, J. Z., Uttamapinant, C., Poloukhtine, A., Baskin, J. M., Codelli, J. A., Sletten, E. M., Bertozzi, C. R., Popik, V. V., and Ting, A. Y. (2012) Fluorophore Targeting to Cellular Proteins via EnzymeMediated Azide Ligation and Strain-Promoted Cycloaddition. J. Am. Chem. Soc. 134, 3720–3728. (54) Thurber, G. M., Yang, K. S., Reiner, T., Kohler, R. H., Sorger, P., Mitchison, T., and Weissleder, R. (2013) Single-cell and subcellular pharmacokinetic imaging allows insight into drug action in vivo. Nat. Commun. 4, 1504. (55) Thurber, G. M., Reiner, T., Yang, K. S., Kohler, R. H., and Weissleder, R. (2014) Effect of SmallMolecule Modification on Single-Cell Pharmacokinetics of PARP Inhibitors. Mol. Cancer Ther. 13, 986–995. (56) Meder, V. S., Boeglin, M., Murcia, G. de, and Schreiber, V. (2005) PARP-1 and PARP-2 interact with nucleophosmin/B23 and accumulate in transcriptionally active nucleoli. J. Cell Sci. 118, 211–222. (57) Darko, A., Wallace, S., Dmitrenko, O., Machovina, M. M., Mehl, R. A., Chin, J. W., and Fox, J. M. (2014) Conformationally Strained trans-Cyclooctene with Improved Stability and Excellent Reactivity in Tetrazine Ligation. Chem. Sci. R. Soc. Chem. 2010 5, 3770–3776. (58) Taylor, M. T., Blackman, M. L., Dmitrenko, O., and Fox, J. M. (2011) Design and Synthesis of Highly Reactive Dienophiles for the Tetrazine–trans-Cyclooctene Ligation. J. Am. Chem. Soc. 133, 9646–9649. (59) Pan, Z., Scheerens, H., Li, S.-J., Schultz, B. E., Sprengeler, P. A., Burrill, L. C., Mendonca, R. V., Sweeney, M. D., Scott, K. C. K., Grothaus, P. G., Jeffery, D. A., Spoerke, J. M., Honigberg, L. A., Young, P. R., Dalrymple, S. A., and Palmer, J. T. (2007) Discovery of Selective Irreversible Inhibitors for Bruton’s Tyrosine Kinase. ChemMedChem 2, 58–61. (60) Cooper, G. M. (2000) The Cell 2nd ed. Sinauer Associates. (61) Thomas, H. D., Calabrese, C. R., Batey, M. A., Canan, S., Hostomsky, Z., Kyle, S., Maegley, K. A., Newell, D. R., Skalitzky, D., Wang, L.-Z., Webber, S. E., and Curtin, N. J. (2007) Preclinical selection of a novel poly(ADP-ribose) polymerase inhibitor for clinical trial. Mol. Cancer Ther. 6, 945–956. (62) Abdelkarim, G. E., Gertz, K., Harms, C., Katchanov, J., Dirnagl, U., Szabó, C., and Endres, M. Protective effects of PJ34, a novel, potent inhibitor of poly(ADP-ribose) polymerase(PARP) in in vitro and in vivo models of stroke. Int. J. Mol. Med. 1, 255–260.


A Modular Probe Strategy for Drug Localization, Target Identification

Recommend Documents