Targeting Drug Resistance in EGFR with Covalent Inhibitors: A

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Targeting Drug Resistance in EGFR with Covalent Inhibitors - a Structure-Based Design Approach Julian Engel, Andre Richters, Matthäus Getlik, Stefano Tomassi, Marina Keul, Martin Termathe, Jonas Lategahn, Christian Becker, Svenja Mayer-Wrangowski, Christian Grütter, Niklas Uhlenbrock, Jasmin Krüll, Niklas Schaumann, Simone Eppmann, Patrick Kibies, Franziska Hoffgaard, Jochen Heil, sascha Menninger, Sandra Ortiz-Cuaran, Johannes Heuckmann, Verena Tinnefeld, René Peiman Zahedi, Martin L. Sos, Carsten Schultz-Fademrecht, Roman K. Thomas, Stefan M. Kast, and Daniel Rauh J. Med. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jmedchem.5b01082 • Publication Date (Web): 14 Aug 2015 Downloaded from http://pubs.acs.org on August 16, 2015

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Journal of Medicinal Chemistry

Thomas, Roman; University of Cologne, Department of Translational Genomics Kast, Stefan; Technische Universität Dortmund, Fakultät für Chemie und Chemische Biologie Rauh, Daniel; Technische Universität Dortmund, Chemie und Chemische Biologie; Technische Universität Dortmund, Fakultät für Chemie und Chemische Biologie

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Targeting Drug Resistance in EGFR with Covalent Inhibitors – a Structure-Based Design Approach Julian Engel1, André Richters1, Matthäus Getlik2, Stefano Tomassi1, Marina Keul1, Martin Termathe2, Jonas Lategahn1, Christian Becker1, Svenja Mayer-Wrangowski1, Christian Grütter1, Niklas Uhlenbrock1, Jasmin Krüll1, Niklas Schaumann1, Simone Eppmann1, Patrick Kibies1, Franziska Hoffgaard1, Jochen Heil1, Sascha Menninger3, Sandra Ortiz-Cuaran4, Johannes Heuckmann4, Verena Tinnefeld7, René P. Zahedi7, Martin L. Sos4,6, Carsten SchultzFademrecht3, Roman K. Thomas4,5, Stefan M. Kast1,*, Daniel Rauh1,2,* 1

Faculty of Chemistry and Chemical Biology, TU Dortmund University, Otto-Hahn-Straße 6, D44227 Dortmund, Germany 2

Chemical Genomics Centre of the Max-Planck Society, Otto-Hahn-Straße 15, D-44227 Dortmund, Germany 3

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Lead Discovery Center GmbH, Otto-Hahn-Straße 15, D-44227 Dortmund, Germany

Department of Translational Genomics, University of Cologne, Weyertal 115b, D-50931, Cologne, Germany

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Department of Pathology, University of Cologne, Joseph-Stelzmann Straße 9, D-50931, Cologne, Germany

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Molecular Pathology, University Hospital of Cologne, Kerpenerstraße 62, D-50937, Cologne, Germany 7

Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V., Dortmund, Germany


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Abstract Receptor tyrosine kinases represent one of the prime targets in cancer therapy as the dysregulation of these elementary transducers of extracellular signals, like the epidermal growth factor receptor (EGFR), contributes to the onset of cancer such as non-small cell lung cancer (NSCLC). Strong efforts were directed to the development of irreversible inhibitors and led to compound CO-1686, which takes advantage of increased residence time to EGFR by alkylating Cys797 and thereby preventing toxic effects. Here, we present a structure-based approach, rationalized by subsequent computational analysis of conformational ligand ensembles in solution, to design novel and irreversible EGFR inhibitors based on a screening hit that was identified in a phenotype screen of 80 NSCLC cell lines against about 1500 compounds. Using protein X-ray crystallography, we deciphered the binding mode in engineered cSrc (T338M/S345C), a validated model system for EGFR-T790M, which constituted the basis for further rational design approaches. Chemical synthesis led to further compound collections revealing increased biochemical potency and, in part, selectivity towards mutated (L858R and L858R/T790M) vs. non-mutated EGFR. Further cell-based and kinetic studies were performed to substantiate our initial findings. Utilizing proteolytic digestion and nano-LC-MS/MS analysis, we confirmed the alkylation of Cys797.


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INTRODUCTION The epidermal growth factor receptor (EGFR), a receptor tyrosine kinase (RTK), is a key mediator in cellular signaling related to cell growth, proliferation, survival, and migration.1-3 Its aberrant activity plays a pivotal role in the development and growth of tumor cells and is associated with the onset and progression of non-small cell lung cancer (NSCLC).4, 5 Mutations in the catalytic domain of EGFR, accounting for increased kinase activity and ligandindependency, have been discovered as oncogenic drivers in NSCLC. The most prevalent activating mutations are represented by the L858R, a single point substitution in exon 21, and the exon 19 deletion (delE746-A750). Patients harboring these specific activating mutations show a significant clinical response (50-80 %) to first-generation reversible EGFR Type-I inhibitors gefitinib6 and erlotinib.7-12 Therefore, EGFR activating mutations serve as predictive markers for the treatment of NSCLC with EGFR tyrosine kinase inhibitors (TKIs), thus demonstrating the potential of targeted cancer therapy. However, patients responding to these drugs develop secondary drug resistance mutations and suffer from a dramatic relapse within months. In 50 % of these cases, the acquired resistance results from a mutation of the gatekeeper residue (T790M). This leads to increased affinity for ATP when compared to other oncogenic primary mutant variants.13-16 Moreover, the sterically more demanding methionine provokes a clash with 4-aminoquinazoline-based drugs erlotinib and gefitinib and thereby induces a slightly different binding geometry that results in a complete loss of inhibitory activity.17-19 Second generation EGFR inhibitors, including neratinib20, dacomitinib21, and afatinib22 (Figure 1A) contain electrophilic Michael-acceptor systems to target a rare cysteine (Cys797) at the lip of the ATP binding cleft of EGFR. These new inhibitors were thought to overcome T790M drug resistance due to the covalent modification of Cys797 and the resulting increased target residence time.23-25


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Despite promising in vitro results, these inhibitors exhibit insufficient efficacy in patients at clinically achievable concentrations. Thus, on-target toxicity represents the dose-limiting factor. In addition to the oncogenic mutant variants, the wild type form of EGFR is likewise inhibited and severe side effects during therapy are observed (e.g., skin rash and diarrhea).26-28 For this reason, third-generation EGFR inhibitors including WZ4002,29 CO-1686 (Rociletinib),30,

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and AZD929132,

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(Figure 1A), have been developed and are based on an

amino pyrimidine scaffold. While WZ4002 has not progressed into human clinical trials, CO1686 (Rociletinib) and AZD9291 are currently at the leading edge of NSCLC treatment exhibiting beneficial effects in terms of residence time, toxicity profile, and further ADME parameters.34 Notably, these compounds do not interfere with larger gatekeeper residues such as of the methionine in the T790M variant and, therefore, retain their inhibitory efficacy towards these clinically relevant mutants. The work of Walter and colleagues showed that covalent modification of EGFR by small molecule inhibitors is feasible for overcoming gatekeeper mutations in cancer treatment30. However, only a few compounds possessing the necessary structural features are under investigation in clinical trials, and further scaffolds are needed for directed treatments. Recently, we performed a phenotype screen of 80 NSCLC cell lines against 1500 small molecule inhibitors and identified quinazoline 1a (Figure 1B) as having inhibitory impact on the drug-resistant H1975 cell line (L858R/T790M).35 However, we also observed significant nonspecific inhibitory effects, most likely caused by off-target activity. Nevertheless, the identified candidate is comprised of a classical 4-aminoquinazoline, but with a unique substitution pattern. This kinase inhibitor is decorated with a sterically demanding phenyl moiety at the 2-position that prevents the adoption of the typical quinazoline binding mode and which


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utilizes the 4-aminopyrazole moiety as an alternative hinge binding element (Figure 1B). Moreover, a Michael acceptor system is incorporated in the 7-position of 1a, which may provide the ability to target covalently Cys797 in EGFR. However, X-ray crystallography studies utilizing engineered cSrc (T338M/S345C) as a validated model system for EGFR (T790M) did not show evidence for the desired covalent modulation of Cys345 which is homologous to Cys797 in EGFR (Figure 1C).18, 36 We used engineered cSrc (T338M/S345C) as initial model system as it provides structural insights. However, crystal structures of EGFR-T790M in complex with irreversible ligands have already been published and likewise guided our design studies. Here, we present the follow-up chemical optimization of potent and irreversible EGFRinhibitors based on the screening hit from the phenotype screen of 80 NSCLC cell lines.35 Structure-based design studies guided us to scaffolds including quinazolines and pyrimidines both targeting the drug resistant T790M as well as the mutant variants of EGFR that harbor activating mutations. Organic synthesis led to a focused inhibitor collection and subsequent characterization using activity-based assay systems elicited potent inhibition profiles. Using Xray crystallography, we gained valuable insights into the mode of action of the new series of inhibitors and its structure-activity relationships (SARs) that led to the design of further derivatives with improved inhibitory activity and, accordingly, better mutant selectivity. Since restricted conformational freedom of ligands in free solution is an important beneficial factor governing binding affinity, we also characterized the population of relevant conformational basins by computational means in order to rationalize the experimental observations. This work demonstrates the strength of the interplay of medicinal chemistry methods, preparative organic chemistry, biochemistry, structure biology, and computational methods in rational drug design approaches.


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RESULTS The relevance of oncogenic EGFR for the treatment of NSCLC and the ongoing interest in the role of acquired drug resistant mutations in targeted cancer therapy emphasize the need for strategies to identify and improve new kinase inhibitors targeting gatekeeper mutant forms of oncogenes, such as EGFR-T790M. Recently, these efforts were focused on the development of irreversible inhibitors, which covalently modify Cys797 at the lip of the ATP-binding cleft.20-22, 30, 32

Modulators that incorporate thiol-reactive groups are beneficial as they increase the target

residence time at the protein of interest upon covalent binding. Therefore, the off-rate of these inhibitors is directly associated with the cellular turn-over rate of the respective protein.23, 37, 38

Rational Design of EGFR Inhibitors Based on Screening Hit Analysis. Intrigued by the substitution pattern of 1a, we recently solved the crystal structure of 1a in complex with mutated cSrc to gain deeper structural insights into the binding mode and to constitute a structural basis for further design and optimization cycles (Figure 1C). Here, we used the previously engineered and validated cSrc-kinase (T338M/S345C) as a model system for drug-resistant EGFR-T790M that has been proven to be appropriate to provide primarily structural information.18, 36 Notably, the co-crystal structure of 1a and cSrc revealed a novel but reversible binding mode in which the 4-aminopyrazole moiety addresses the hinge region by three direct hydrogen bonds to the peptide backbone residues of Glu339 and Met341. Furthermore, the hinge binding element apparently does not affect the gatekeeper residue (Met338). Moreover, the Michael-acceptor system in the 7-position of the quinazoline is turned outwards from the ATP binding cleft, whereas the 2-phenyl moiety accesses the binding pocket preventing the formation of a covalent


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bond to Cys345. Therefore, the observed inhibitory effect is apparently not caused by covalent modification of EGFR, which is consistent with an analog inhibitory potency of the reversible counterpart 1b as compared to 1a (Table 1). Both 1a and 1b did not show any significant kinase inhibition of EGFR-WT and illustrated comparable inhibitory effects on the activating mutant of EGFR (1.9 µM vs. 2.1 µM for 1a and 1b, respectively) and on the drug-resistant mutant variant (2.2 µM and 2.2 µM), strengthening the conclusion that the Michael-acceptor adopts a nonreactive binding geometry, in which it does not impact the inhibitory efficacy of 1a as compared to 1b. This remarkable observation, in turn, allows a structure-guided development of inhibitors with respect to the improved inhibitory effects evoked by covalent modification of Cys797. Based on this X-ray structure, we generated superimposed models to investigate further the options for the covalent bond formation and proposed various scaffolds and substitution patterns capable of covalent modification (Figure 2). The phenyl moiety in the 2-position of 1a represented a convenient attachment point for incorporating a Michael acceptor (e.g., acrylamide) (Figure 2A). We also proposed a pyrimidine as an alternative scaffold. This variant retains the aminopyrazole moiety as the hinge binding element and may increase flexibility due to the reduced core structure (pyrimidine vs. quinazoline). We suggested two different linkages of the Michael acceptor system to the pyrimidine core to investigate different conformations and to evaluate the preferred geometry and orientation of the electrophile. Therefore, the electrophile was attached directly (Figure 2B) and by a linked phenylether (Figure 2C, D) to the pyrimidine core. Moreover, we paid particular attention to the optimization of the hinge binding element with the aim to enhance the interdependency between the methionine gatekeeper and the ligand by expanding the hydrophobic character of the 4-substituent (e.g., 1-methylpyrazole in 5b,


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indazole in 6a). Recently, this interaction was shown to have a dramatic effect on inhibitory activity and mutant-selectivity in case of various EGFR inhibitors.39, 40

Synthesis of a Focused Small Molecule Library. We set out to synthesize a focused library of pyrimidine-based inhibitors with diverse substitution patterns. Our efforts were directed towards the optimal orientation of the Michaelacceptor system with respect to the alkylation of Cys797 in EGFR. Moreover, we focused on the derivatization of the hinge binding element to enhance the hydrophobic interaction with the gatekeeper residue while simultaneously retaining the crucial direct hinge interactions. Therefore, seven different synthetic routes were established to produce pyrimidine-based compounds 3a-b, 4, 5l-m and 5a-k, 5n-o, 5p-q, 6a-e, 7. In case of 3a-b (Scheme 1), we started with a nucleophilic aromatic substitution using 2-phenyl substituted pyrimidine 8 and 5aminopyrazole, resulting in intermediate 9. Subsequent decoration of the pyrazole with the Bocprotection group led to 10, which was then converted into 3a and its reversible counterpart 3b by amide formation using acryloyl or propionyl chloride and subsequent deprotection with TFA. To retain the flexibility of the pyrimidine based inhibitors but to vary the type of substituent at the 2- and 4-positions, we synthesized several similar derivatives by the synthetic route shown in Scheme 2. Driven by our modeling studies (Figure 2), we proposed different attachment points for incorporating a Michael-acceptor moiety to scrutinize and optimize the geometry and orientation towards Cys797. Therefore, we incorporated an electrophile utilizing a linker through a carbon-carbon bonding (4) and we likewise introduced a heteroatom linkage to gain increased flexibility that allows for altered and potentially beneficial orientation towards Cys797 (5l). Also, we proposed further molecules incorporating a proton at the pyrimidine 6-position to gain further


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information about the significance of a solubility group on this position. 2,4-Dichloropyrimidine was preferentially decorated with 3-methyl-1H-pyrazol-5-amine at the 4-position to afford key intermediate 12. Subsequently, the pyrazole moiety was protected using dihydropyran. Then, (3nitrophenyl)boronic acid was used to introduce the 3-nitrophenyl moiety into the pyrimidine 2position under Suzuki-conditions resulting in intermediate 14a which was reduced to the corresponding amine 14b. The acrylamide Michael acceptor system was introduced by amide formation using acryloyl chloride. THP-deprotection with TFA led to compound 4. Starting from key intermediate 12, we likewise generated compounds with a bridging ether at the 2-position to increase the conformational flexibility of the Michael acceptor-decorated moiety. Nucleophilic aromatic substitution of 12 utilizing 3-nitrophenol gave intermediate 15a, and subsequent reduction with Pd/C and ammonium formate led to the amino equivalent 15b. Reaction of amine 15b with various acid chlorides yielded compounds 5l-m. In a third approach (Scheme 3), we applied a generic route to build up 2,4,6-substituted pyrimidine compounds 5a-k, 5n-q, and 6a-d. Initially, 4,6-dichloro-2-(methylthio)pyrimidine was oxidized to the corresponding sulfone 17 using mCPBA to generate an appropriate leaving group at the pyrimidine 2-position. Consecutive nucleophilic aromatic substitution with the ortho-, meta- or para-substituted nitrophenol-derivatives led to intermediates 18a-c. Following substitution of one aromatic chlorine with either amino-pyrazoles or amino-indazoles resulted in intermediates 19a-c and 20-22, which were then derivatized with 1-methylpiperazine at the pyrimidine 6-position, providing 23a-c and 24-26. The decoration of the pyrazoles or indazoles with the Boc-protection group led to 27b-c and 28-30. Subsequent reduction of the aromatic nitro-group was performed by using Pd/C and ammonium formate and resulted in the corresponding amino derivatives 31b-c and 32-34. Ultimately, these amines were decorated with


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Michael acceptors using acid chlorides or carboxylic acids, under standard amide coupling conditions (EDC/HOBt), respectively. The equivalent reversible counterparts were produced accordingly utilizing propionyl chloride. Final Boc-deprotection was conducted using TFA and led to compounds 5a-k, 5n-q, and 6a-d (Table 1). Synthetic schemes and preparations of quinazoline-based compounds 1a-b and 2a-f have been recently described elsewhere.35 Synthetic schemes of compounds 6e and 7 as well as detailed synthetic procedures are shown in the supporting Information (Scheme S1 and S2, respectively).

Activity-Based Characterization of Quinazoline and Pyrimidine-Based Scaffolds on EGFR inhibition. We characterized the focused compound collection against various types of EGFR including wild type and mutant forms L858R and L858R/T790M (Table 1) using an activity-based assay that quantifies phosphorylation of an artificial substrate by a particular kinase through homogeneous time-resolved FRET measurements (see Experimental Section). Since 1a was decorated with an acrylamide warhead, we tested the reversible counterpart and observed equal potency on EGFR-L858R and L858R/T790M (IC50 ~ 2.0 µM) while 1a displayed a reduced effect on the wild type form of EGFR (IC50 >10 µM). However, due to these results and in concordance with the observed reversible binding mode (Figure 1C), we generated further quinazoline-based compounds (2a-f) with the Michael acceptors attached in different positions (ortho, meta, para) to increase the probability of alkylating Cys797. Compounds 2b and 2e demonstrated significant inhibitory effects in the investigated EGFR variants. We observed IC50 values of 1.1 µM (wt), 0.5 µM (L858R) and 0.1 µM (L858R/T790M) for compound 2b, while the reversible counterpart 2e was 4 times less potent (3.7 µM, 1.9 µM, and 0.4 µM, respectively)


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indicating that in contrast to 2b, no covalent bond was formed with 2e. Altering the attachment point of the acrylamide/propionamide motif to the ortho and para sites, (2a, 2d and 2c, 2f) did not result in notable inhibitory effects, except for 2a with moderate inhibitory effects on L858R (2.8 µM) and L858R/T790M (1.1 µM). When we decreased the spatial arrangement by utilizing a pyrimidine core instead of a quinazoline 3a, we achieved similar IC50 values (0.9 µM, 0.8 µM, 0.3 µM), although the Michael acceptor was not attached to the 2-phenyl moiety as in the case of 2a-f but instead at the pyrimidine 6-position. Both attachment points were likewise eligible to elicit potent inhibition on EGFR. Furthermore, the reversible counterpart 3b did not significantly inhibit EGFR, supporting our hypothesis of covalent bond formation between Cys797 and 3a. Based on modeling studies (Figure 2), we attached the Michael acceptor to the 2-phenyl moiety (4) to increase inhibitory activity. We incorporated an additional methyl group at the pyrazole 5-position, which we proposed would form hydrophobic interactions with the methionine gatekeeper residue in EGFR-L858R/T790M, and increase the compound’s selectivity towards this variant. Several EGFR inhibitors have been equipped with either halogen or methyl substituents directed towards the methionine gatekeeper residue.29,

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However, we did not

observe any beneficial effect for compound 4 with respect to the inhibitory potency towards the investigated EGFR variants (IC50 >10 µM (wt), 2.5 µM (L858R) and 2.3 µM (L858R/T790M). Further approaches were undertaken to position the Michael acceptor in proximity to Cys797 by connecting the phenylacrylamide to a flexible ether linkage. We speculated that this would translate into an improved orientation towards the reactive cysteine and favor subsequent covalent bond formation. While the wild type form was not inhibited (IC50 >10 µM), we observed moderate inhibition of the L858R (1.8 µM) as well as the L858R/T790M mutant


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(0.9 µM) by 5l. The reversible counterpart 5m certainly did not elicit substantial inhibitory activity towards any of the EGFR variants. These results prompted us to introduce a solubilizing group (1-methylpiperazine) to the 6position of the pyrimidine to restrict the structural flexibility with respect to hinge binding and optimally orient the 2-phenyl moiety to preserve its conformational flexibility to reach Cys797 for covalent modification. Compounds 5a-c were generated to investigate the influence of ortho-, meta- and para-substituted acrylamides on the inhibition and also on the formation of a covalent bond by the thiol-reactive warhead. For 5a (ortho), only moderate inhibition was observed for wild type (IC50 = 0.9 µM), L858R (IC50 = 0.6 µM) and L858R/T790M (IC50 = 2.1 µM). Equal behavior was demonstrated for the corresponding para-substituted compound 5c (3.1 µM, wt; 1.8 µM, L858R; 2.4 µM, L858R/T790M). Notably, meta-substitution as in 5b led to remarkable inhibition of EGFR-L858R (IC50 = 0.03 µM) whereas the double mutant form was less addressed (IC50 = 0.5 µM). Interestingly, 5b did not show any significant inhibition of the wild type. With respect to the reversible counterpart 5e, which is equipped with a propionyl moiety that cannot undergo a Michael-addition to form a covalent bond to Cys797, we observed a dramatic loss in inhibitory activity against both activating and drug-resistant mutant variants of EGFR (60-fold and about 20-fold, respectively) as compared to its covalent counterpart 5b, thus indicating that 5b may interact with EGFR in a covalent manner. This observation further strengthened the conclusion that covalently targeting EGFR-T790M is a crucial feature to achieve sufficient efficacy. The corresponding 5n solely possesses a proton instead of the methyl substitution at the pyrazole 5-position and therefore resulted in moderate inhibitory activity on the mutant variants (2.0 µM and 1.9 µM for L858R and L858R/T790M, respectively) whereas no inhibitory activity was observed against the wild type, supporting the concept that favorable hydrophobic


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gatekeeper interactions may lead to improved protein-ligand interactions. To further strengthen this concept, we introduced an indazole into the most promising compound 5b to increase the spatial and hydrophobic character while retaining the crucial hinge binding motif as well as the meta-substituted phenylether as a linker system for the electrophile, resulting in 6a. We observed a strikingly increased effect on the drug-resistant mutant of EGFR (IC50 = 0.07 µM) for 6a. The mutant variant harboring the activating mutation is 7-fold less well inhibited (0.5 µM, L858R) whereas only moderate activity could be observed against the wild type (IC50 = 1.7 µM), indicating a favorable interaction of the methionine gatekeeper and the indazole moiety. With respect to the reversible counterpart (6b), we did not observe an inhibitory effect on any of the EGFR variants, thereby demonstrating the importance of a covalent bond. We intended to further increase the gatekeeper interacting element by introducing a bromine in the 5-position of the indazole and likewise to sterically constrain the inhibitor’s conformation (6d). We observed similar behavior for 6d against the wild type (IC50 = 2.9 µM) as well as against the mutant form EGFR-L858R (0.4 µM) while 6d displayed a slightly reduced effect against the drug-resistant mutant variant (0.3 µM, L858R/T790M). In order to investigate the electrophilic characteristics of the Michael-acceptor system, we equipped the acrylamide with an additional dimethylamino moiety (compound 6c) which is supposed to increase the reactivity of the thiol nucleophile for subsequent Michael-addition (Cys797) by intramolecular base catalysis.41 This modification, however, led to a significant loss of inhibitory activity against all investigated EGFR mutants (>10 µM, wt; 3.6 µM, L858R; 0.7 µM, L858R/T790M). These observations indicate that the acrylamide moiety represents a more favored electrophile for this scaffold in terms of size, reactivity, and orientation.


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Notably, initial ESI-MS analyses of EGFR-T790M treated with 3a, 5b or 6a resulted in mass increases equivalent to the corresponding single-labeled EGFR-T790M (303 Da (3a), 436 Da (5b), and 468 Da (6a), respectively), as compared to control EGFR-T790M treated with DMSO indicating a covalent inhibitor adduct with EGFR-T790M (Figure S1). Furthermore, utilizing proteolytic digestion of 5b and 6a and nano-LC-MS/MS analysis we precisely confirmed selective Cys797 modification for both compounds (Figure 3 and Supporting Information).

Activity-Based Characterization of Quinazoline and Pyrimidine-Based Scaffolds on the EGFR surrogate system cSrc. To account for the validity of our EGFR surrogate system, we likewise tested the focused set of compounds on cSrc and selected mutant variants. In particular, we determined the IC50 values with respect to cSrc wild type that lacks both, a large gatekeeper and a reactive Cys at the lip of the ATP-pocket. Furthermore, we investigated the inhibitory activities on engineered cSrc gatekeeper mutant variant T338M as well as on a mutant incorporating the gatekeeper mutation T338M and the reactive cysteine (S345C) to serve as model system for EGFR T790M (Table S1). For the parent compound 1a we observed moderate inhibitory activity towards cSrc wild type (IC50 = 0.211 µM), while inhibition of cSrc T338M, as well as T338M/S345C, was six- to nine-fold stronger, but did not improve with introducing S345C (IC50 = 0.065 µM on T338M vs 0.043 µM on T338M/S345C) indicating that the mutant form is addressed more efficiently, however, not covalently in case of T338M/S345C. The reversible counterpart 1b likewise reflects improved inhibitory activity on the mutated variants as compared to wild type cSrc substantiating our conclusion (IC50 = 0.336 µM vs. 0.060 µM vs. 0.048 µM). Improved inhibitory effects towards the gatekeeper mutant forms of cSrc were observed and reflect a


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general trend throughout the focused compound collection (Table S1). However, for 5b we observed distinct differences among the mutated variants. In detail, an IC50 value of 0.170 µM was determined for cSrc T338M whereas cSrc T338M/S345C was inhibited five-fold more efficient (IC50 = 0.028 µM). On the contrary, we did not observe increasing potency for the analogous reversible compound 5e (IC50 = 0.254 µM and 0.349 µM, respectively). Analogous characteristics were found for 6a and 6b accounting for more efficient inhibition of cSrc T338M/S345C in case of the Michael-acceptor decorated 6a (IC50 = 0.017 µM) as compared to the reversible analogue 6b (IC50 = 0.260 µM). These results validated further the use of engineered cSrc as a surrogate system for EGFR and its mutants.

Kinetic Characterization of Covalent Bond Formation of 5b and 6a to EGFR Mutant Variants. Covalent binding of inhibitors to their respective target proteins requires distinct spatial orientations that allow for efficient and irreversible modification of a unique cysteine. In particular, Cys797 in EGFR serves as the anchor point for irreversible inhibitors equipped with warheads. In order to investigate the rate and efficiency of covalent bond formation of our most effective inhibitors 5b and 6a, we set out to determine the corresponding Ki and kinact parameters with respect to the mutant variants L858R and T790M/L858R of EGFR utilizing an activitybased assay system (See Experimental Section). We monitored the respective IC50 values of 5b and 6a after treatment of the respective proteins in a time-dependent manner and correlated the according values to the respective incubation times which then translated into the determination of Ki and kinact as described in the literature (Table 2).42 Based on the kinetic characterization, we demonstrated 5b as well as 6a to exhibit particularly high affinity towards EGFR L858R/T790M


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(Ki = 0.64 nM and 0.32 nM, respectively) whereas they solely account for specific moderate reactivity (kinact = 0.116 min-1 and 0.137 min-1, respectively) as compared to known reference compounds.43 On the contrary, we likewise illustrated that both the affinity and specific reactivity of 5b and 6a towards EGFR L858R is significantly impaired (Ki = 70.2 nM and 833 nM, respectively; kinact = 0.017 min-1 and 0.055 min-1, respectively) as compared to EGFR L858R/T790M.

Complex Crystal Structures of 5b and 5c In order to investigate the binding modes of our newly designed inhibitors and to substantiate the observed SARs, we generated complex crystal structures of representative compounds of our focused library. We co-crystallized 5b and 5c (Figure 4) in complex with engineered cSrc (T338M/S345C) as the model system validated for EGFR-T790M18, 36. We focused on 5b and 5c as they exclusively differed in the substitution pattern of the attachment point of the Michaelacceptor to the phenylether linker system, but exhibited a dramatic discrepancy in inhibitory activity towards the investigated EGFR mutant variants. In accordance to the X-ray structure of 1a, the complex crystal structures of both 5b and 5c revealed a hinge contact addressed by three hydrogen bonds to the peptide backbone residues of Glu339 and Met341. The pyrazole amine forms a hydrogen bond to the carbonyl group of Glu339 while Met341 is addressed by N2 of the pyrazole that serves as the hydrogen bond donor. The 3-amino moiety of the pyrazole forms the third hydrogen bond to the carbonyl group of Met341. The co-crystal structure of cSrc-DM-5b confirms the covalent bond between Cys345 and the inhibitor. The phenylether carrying an acrylamide in the meta-position adopted a perpendicular orientation towards the pyrimidine core, thereby facilitating a close proximity and


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an optimal geometry of the electrophile towards Cys345 that was crucial for alkylation. The 6substituted methylpiperazine extended to the solvent exposed region of the ATP binding cleft functioning as solubilizing group. As anticipated by modeling studies, the newly introduced methyl group in the 5-position of the pyrazolo group accurately points towards the methionine gatekeeper, most likely inducing a hydrophobic protein-ligand interactions. The co-crystal structure cSrc-DM-5c, in contrast, revealed a reversible binding mode for 5c, in which the phenylether (acrylamide in the para-position) adopted a stretched or slightly bent conformation accessing a subpocket adjacent to the gatekeeper residue, thereby preventing a covalent bond formation to Cys345. To date, only covalent inhibitors have been sufficiently effective in overcoming T790M drug resistance. Therefore, these X-ray structures demonstrate the exceptional importance of optimized Michael-acceptor systems for each inhibitor scaffold with respect to orientation, basicity, and reactivity. These remarkable structural observations reveal a novel scaffold possessing the ability to form a covalent bond and they likewise elucidate the opposing inhibitory characteristics of 5b and 5c. Furthermore, this structure-guided approach provides valuable insights into the SAR and may stimulate further approaches to develop covalent inhibitors targeting the drug resistance in EGFR.

Evaluation of Selected Derivatives on Drug-Resistant NSCLC Cell Line We investigated inhibitory effects of a selected subset of representative quinazoline- and pyrimidine-based compounds in preliminary studies utilizing the drug-resistant NSCLC cell line H1975 and we additionally included the HCC827 (exon 19 deletion) and metastatic lung cancer cells harboring wild type EGFR (A431 and H661 Table 3). Each cell type was treated with


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quinazoline 1a, and 2,4,6- substituted pyrimidines 5b, 5e, 5j, 6a, 6b, 6c, 6d, 6e and 7 (0-30 µM) respectively for 96 h. Although several covalent inhibitors of our focused library displayed strong inhibitory effects in biochemical evaluations using isolated kinases, we observed poor translation to cellular potency. While parent compound 1a equally addressed NSCLC lines harboring wild type and gatekeeper mutated EGFR (GI50 = 0.7 µM, 1.9 µM, and 1.6 µM for H661, HCC827, and H1975, respectively) none of the structurally altered pyrimidines displayed improved effects in terms of inhibitory efficacy and mutant-selectivity. For instance, a distinct biochemical selectivity profile was observed for 6a and its reversible counterpart 6b targeting the mutant form of EGFR while sparing the wild type (Table 1). On the contrary, this trend was not reflected in cellular evaluations since 6a solely exhibited moderate effects on the activating and drug resistant cell lines HCC827 and H1975 (GI50 = 2.5 µM and 9.8 µM, respectively) and likewise displayed comparable inhibitory activity on the wild type cell line A431 (GI50 = 8.6 µM). However, the reversible counterpart 6b did not display any significant effect on the NSCLC cell lines, thereby indicating a certain beneficial cellular effect caused by the inhibitor’s properties to form covalent adducts. We observed a slightly different tendency for 5b and 5e since cellular evaluations led to equal GI50 values of 5.7 µM and 8.4 µM respectively on EGFR wild type cell lines, but on the contrary 5e did not account for any significant inhibitory effect in HCC827 and H1975 at concentrations up to 30 µM while the Michael acceptor equipped derivative 5b illustrated moderate inhibition on both activating and drug-resistant mutant cell lines (GI50 = 8.2 µM and 20 µM). Of note, nitro-decorated compound 5h represents one of the most active inhibitors in our cellular setting eliciting GI50 values of 3.5 µM, 8.9 µM, and 6.5 µM towards H661, HCC827, and H1975 respectively.


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Interestingly, we observed similar cellular effects for the majority of our compounds on the cell line harboring the activating mutation (HCC827) as compared to the drug-resistant H1975 cell line without a dramatic loss in activity. However, the entity of investigated compounds did not account for significant reduction of cell viability in cellular settings indicating the need for a stronger inhibitory effect on the kinase activity and likewise strengthening the need for further investigation with respect to pharmacokinetic properties such as solubility and cell permeability. In order to assess these pharmacokinetic parameters and to pursue the poor translation of biochemical activity into cellular-based potency, we set out to investigate the solubility and the cell permeability for the most promising compounds 5b and 6a using in vitro assays (see Experimental Section). The kinetic solubility for 5b and 6a was measured at pH 7.4 and revealed a high aqueous solubility of 432 µM and 277 µM for 5b and 6a, respectively (Table S3). Furthermore, we gained valuable insights into the cellular absorption using an artificial membrane permeation assay (PAMPA). 5b exhibited a rather low cellular penetration at pH 7.4 (PAMPA, flux 7%), whereas 6a, equipped with an indazole instead of a pyrazolo moiety, showed a 7-fold higher permeability (PAMPA, flux 47%) representing a sufficient cellular penetration in an artificial membrane system according to the assay’s classification.44 However, we further investigated the cell permeability of 5b and 6a using a Caco-2 cell assay, in which the ratio of influx/efflux across Caco-2 cells is determined, and, therefore, is more appropriate to reflect the setting in a cellular environment. Strikingly, we observed a high efflux rate for both compounds (efflux over cell penetration: 32:1 and 35:1 for 5b and 6a) indicating a poor overall absorption that leads to a low receptor occupancy in the cells, thus providing a reasonable explanation for the compound’s moderate cellular efficacy as compared to their inhibitory activity with respect to isolated kinases.


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Computational Studies of Ligands’ Conformation in Solution The drug CO-1686 as one of the current front-runners in EGFR related cancer therapy is supposed to be conformationally constrained and therefore most likely to adopt a preconfigured conformation which is very similar to the observed binding mode in the WZ4002-EGFR complex (PDB code 3ika). Preconfigured compounds take advantage of the fact that the free energy penalty incurred upon binding a ligand in an optimum conformation to the protein of interest is markedly lower than for those compounds that present considerably different conformational states in aqueous solution and therefore must undergo unfavorable conformational changes upon ligand binding. For this reason, our current efforts, especially by introducing an indazole moiety, were directed to the design of compounds that take advantage of a certain preconfiguration to minimize disfavored conformational changes upon intrinsic compound rearrangements. In order to test these propositions, we performed theoretical calculations of the conformational ensembles for selected compounds in order to identify most favored conformations that could be adopted in aqueous solution and their similarity to the crystallographic binding mode. Conceptually, (near) exhaustive search of the conformational space of typical EGFR ligands in solution is problematic due to the large number of accessible states which requires sampling schemes followed by geometrical clustering approaches in order to identify representative structures.45-47 Moreover, empirical force field-based methods, for instance based on the “General Amber Force Field” (GAFF48,

49

) are not accurate enough to discriminate possibly

subtle population shifts arising from free energy differences below 1 kcal mol-1. This represents the typical so-called “chemical accuracy” which poses a systematic limit to force field


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calculations and simulations for instance of small ligands in solution50 or of protein-ligand interactions51. To overcome this uncertainty, we developed a strategy to estimate the configurational free energy of conformational “basins” of free ligands in solution based on quantum-chemical calculations taking into account an aqueous solution environment. To address the complexity of the conformational space, we started by generating a, for all practical purposes, uniformly distributed ensemble of structures by sampling from a high-temperature simulation trajectory of the ligand with fixed charges immersed in a Poisson-Boltzmann-type continuum model of the solvent. After applying a sufficiently large energetic cutoff of 3 kcal mol-1 (corresponding to a Boltzmann weight of skipped conformations of less than 0.007 at ambient temperature) in order to remove high-energy structures, the resulting snapshots were geometrically clustered. The minimum energy geometries of each cluster (still from a fixed charged force field) were subjected to further quantum-chemical treatments. These consisted for each cluster optimum in a preoptimization step under vacuum conditions followed by final optimization taking into account a solvent by the polarizable continuum model (PCM52), yielding the configuration’s free energy in solution GPCM. Finally, the free energies of the resulting structures in solution were rescored by the embedded-cluster reference interaction site model (EC-RISM53, giving values GEC-RISM) integral equation theory, using settings adopted earlier for tautomer54 and chemical shift55 predictions in water. The number of cluster members was taken as degeneracy factor gi,j for cluster i in the conformational “basin” j, where the latter has been defined by grouping clusters that have visually sufficient distance between each other (quantified in the caption to Figures 5 and 6) as measured by their root mean square deviation (RMSD) with respect to the crystallographic binding mode. Such a basin corresponds to a certain distribution of dihedral angles (data and atom indices are discussed below) which define a specific


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conformation. Different basins are therefore characteristic dihedral angle groups, allowing for limited fluctuations represented by the other members within a basin. Neglecting contributions from vibrational entropy associated with each cluster well, the cluster population is given by the Boltzmann weight at ambient target temperature T,

p

PCM|EC − RISM i, j

=

|EC − RISM g i , j exp(−GiPCM / RT ) ,j

∑∑ i

j

|EC − RISM g i , j exp(−GiPCM / RT ) ,j

(1)

where R is the gas constant, while the population of each conformational basin is defined by |EC− RISM |EC− RISM p PCM = ∑i piPCM j ,j

(2)

This methodology has been applied initially to WZ4002 in order to test the performance with respect to the proposition that a substitution of chlorine by hydrogen could lead to more conformational freedom and, correspondingly, less inhibitory activity.40 Results are summarized in Tables 4 and 5 as well as Figure 5. Most importantly, only four dihedral angels are relevant for defining the accessible conformational space, as shown in Figure 5. Here, WZ4002 is the only compound which exhibits a close match between reference crystal structure and basin 1 (smallest RMSD) in terms of three out of four dihedrals, while the population of this basin is nonzero. In this sense, WZ4002 is indeed preconfigured since only a single torsional rearrangement of members of basin 1 is required in order to bind. In contrast, the structurally completely differing basin 4 (largest RMSD) has to rotate all four dihedrals to facilitate binding. Although we cannot estimate the binding pathway (in the sense of making assumptions about the possibility of internal rotations at certain points on the binding reaction coordinate), it is clear that the visually elongated form is not likely to bind directly. However, its population is basically zero in free solution, so all essentially contributing conformations of the compound are to a certain degree preconfigured, as measured by the preconfiguration ratio (PR) defined in Table 5 being 100:0.


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In contrast, dihedral and population data for WZ4002-H show that the latter derivative exhibits a form closest to the binding mode where at least two dihedrals have to rotate. This is already an indication of less likely binding. Moreover, the PR in this case shows a shift toward elongated conformations (basin 3) whereas the other two conformations are U-shaped as defined by dihedral angles spanned by atoms (2,3,4,5) and (5,6,7,8) being close to 0 (see Table 4). Note that the diffuse RMSD boundary between basins 2 and 3 is nevertheless clearly characterized by a change of angle (5,6,7,8) by almost 180°. In summary, the reduced WZ4002-H activity is indeed correlated with a loss of conformational preconfiguration propensity. In order to understand the conformational space of the present set of compounds, we examined analogously 5b, 5n, and 6a. Numbers for dihedral angles, populations, and graphical representations of main conformers are also shown in Tables 4 and 5 as well as in Figure 6. Again, we find that it is possible to reduce the conformational space to four essential dihedral angles. Remarkably, at least 5n possesses an accessible state where three out of four dihedrals match the crystal binding mode of reference compound 5b fully, but this state is practically unpopulated for all 5b, 5n, and 6a – in contrast to the best matching WZ4002 conformer. All three compounds have to undergo a rotation of at least one dihedral angle by 180° whereas WZ4002’s best matching conformation only has to rotate a single dihedral (6,7,8,9) by 57° as mentioned in Table 4. Also, all three compounds show some tendency to form mirror-like image relations, defined by the inverted angles (1,2,3,4) and (2,3,4,5) between basins 2 and 3, which are similarly populated. Some degree of preconfiguration exists for this class of compounds measured by summing populations of basins 1 (which contributes only marginally) and 2 that come closest to the binding. It is important to note that 6a, the most active compound against the L858R/T790M double mutant of EGFR, shows indeed the some increased propensity toward the


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preconfigured conformation as compared to 5b and 5n, corroborating the proposition that conformational restriction is a valid design goal that can be predicted by computational means.

DISCUSSION AND CONCLUSIONS Drug resistance mutations within the catalytic pocket, which occur as the consequence of secondary mutations after first-line treatment, represent a major challenge in modern cancer therapy, as the target proteins have to be considered as entirely different enzymes and, therefore, require newly developed inhibitors.31, 33, 56, 57 However, in case of the T790M mutation in EGFR, recently designed third-generation inhibitors bearing a warhead for covalent modification of a unique and reactive cysteine at the lip of the ATP-binding cleft in EGFR provide evidence for a successful mode of action without evolving severe side effects.31, 33, 58 Covalent drugs equipped with Michael acceptors were not appreciated in medicinal chemistry for a long time. Such drugs were mainly seen as acting nonspecifically because of their reactive groups and thereby driving toxicity such as idiosyncratic drug-related toxicity by eliciting adverse immune response.59-61 Recently, it has been found that the specific fine-tuning of these covalent drugs leads to distinct therapeutic and selective effects, which are not associated with toxicity in vivo. It has been turned out that an acrylamide warhead, which is perfectly attached to a drug in terms of geometry and orientation towards the reactive cysteine, appears to represent an excellent compromise regarding reactivity and toxicity as it is feasible to specifically alkylate the target protein in vivo while omitting unwanted irreversible interactions with arbitrary proteins.31, 33, 62, 63 Current design approaches take advantage of cysteine mapping along the kinome and therefore, the concept of covalently modifying target protein to increase the target residence time and elicit temporal target selectivity has been revived in the last decade. Current efforts in medicinal


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chemistry, for instance, are directed towards the design and development of selective and irreversibly bound compounds to overcome secondary drug resistance mutations, as in the case of EGFR-T790M.20-22, 64 Irreversible inhibitors such as CO-1686 and AZD9291 are currently at the leading edge of clinically relevant therapeutics for the treatment of advanced NSCLC and may stimulate further rational design approaches adapted from covalent modification of target proteins.30, 32 Here, we have presented a structure-guided development of irreversible inhibitors to selectively target the L858R/T790M mutant form of EGFR. Initial screening of 1500 compounds against 80 NSCLC cell lines led us to the identification of 1a, revealing an attractive chemotype and showing effective inhibitory impact on H1975, an EGFR-L858R/T790M mutant lung cancer cell line. However, the pharmacological effect was not limited to H1975 but to the majority of investigated cell lines which indicates rather broad specificity. We set out to utilize the general quinazoline scaffold of 1a as the structural basis for further rational design approaches that would result in compounds with increased specificity while retaining cellular potency. Therefore, we utilized X-ray crystallography and discovered the complex crystal structure of 1a in complex with genetically engineered cSrc as the initial model system for the therapeutically relevant kinase EGFR. By methods of synthetic chemistry, we produced focused compound libraries and particularly paid attention to the variation of the quinazoline core structure resulting in further quinazolines (2a-f) as well as various substituted pyrimidines (3a-b, 4, 5a-q, 6a-e, 7). The latter were extensively elaborated with respect to different substitution patterns (e.g., Michael acceptor position, 2,4- vs. 2,4,6,-substitution) and revealed distinct inhibitory effects in biochemical characterizations using wild type as well as L858R and accordingly L858R/T790M mutated EGFR. While quinazoline-based inhibitor 2b illustrated increasing inhibitory impact in biochemical characterizations (IC50 = 1.1 µM (wt) > 0.5 µM


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L858R > 0.1 µM L858R/T790M) and thereby displaying mutant selectivity, the related pendants 2a and 2c, differing only by the position of the attachment of the Michael-acceptor, basically did not evoke any effect. Shortened pyrimidine scaffolds 3a and 5l, however, illustrated the same mutant selectivity. Notably, for the 2,4,6-substituted scaffold 5b, the mutant selective inhibition profile was somehow inverted since the L858R mutant form of EGFR was predominantly addressed (IC50 = 0.4 µM (wt) > 0.03 µM (L858R) < 0.5 µM (L858R/T790M)) whereas 6a exhibited an excellent as well as a mutant-selective effect on EGFR mutant variants (IC50 = 2.2 µM (wt) > 0.5 µM L858R > 0.07 µM L858R/T790M). Constitutive protein X-ray experiments using a validated model system of cSrc (T338M/S345C) representing EGFRT790M and promising inhibitors from our focused library revealed binding modes that are in accordance with covalent modification of the target protein as in the case of 5b. Moreover, MSbased analyses further supported our result of covalent modification of EGFR by demonstrating increased molecular weight of the protein-ligand complex matching the respective monolabeled species as in the case of EGFR-3a, EGFR-5b, and EGFR-6a. In addition, we confirmed the alkylation of Cys797 for both inhibitors by conducting proteolytic digestion of 5b and 6a and subsequent nano-LC-MS/MS analysis. As a proof of concept study, we likewise tested our focused compound collection with respect to their inhibitory activities on cSrc as our initial EGFR surrogate system and found the majority our covalent inhibitors to more efficiently inhibit cSrc T338M/S345C as compared to cSrc T338M and cSrc wildtype. In a further experimental setup, we set out to investigate the kinetic properties of 5b and 6a with respect to time-dependent affinity and specific reactivity towards EGFR mutant variants (L858R and L858R/T790M) by determination of the respective Ki and kinact parameters. Based on this analysis we found that the inhibitors address the gatekeeper mutant form of EGFR


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(L858R/T790M) with high affinity reflected by Ki values in the subnanomolar range whereas the rate of inactivation remained fairly moderate (kinact). On the contrary, the activating mutant (L858R) was addressed with significantly less affinity revealing Ki values of 70 nM (5b) and 833 nM (6b) and beyond that the rate of inactivation was marginal (kinact ≤ 0.055 min-1). Covalent inhibitors achieve their potency through a two-step-mechanism. In the first step, a covalent inhibitor reversibly interacts with the target kinase to build a crucial non-covalent drugtarget complex. In a second step, a covalent bond is exclusively formed in vivo in case the inhibitor incorporates an optimized electrophile located in close proximity towards the reactive cysteine that allows a rapid alkylation. Therefore, a potent covalent inhibitor should comprise two essential feature: (i) a strong reversible binding interaction and (ii) an optimized electrophile that facilitates rapid covalent bond formation. We observed discriminative inhibitory activities of 5b and its reversible counterpart 5e that clearly demonstrates the importance of covalently targeting the drug-resistant mutant of EGFR, as 5e exhibited a 60-fold and >20-fold loss in inhibition against EGFR-L858R and EGFRL858R/T790M. As a Michael-acceptor represents the only structural difference between these two inhibitors, the shift in activity might directly correlate with beneficial effects due to the covalency of the compound and its associated prolonged drug-target residence time. In conjunction with the MS-based analyzes and the X-ray crystal structures our most promising pyrimidine based inhibitors 5b and 6a seem to form a covalent adduct with EGFR in vitro. These results explicitly revealed the potential of covalent inhibitors and highlighted the benefits of covalent design strategies for further drug development. We also conducted theoretical calculations investigating the potentially preconfigured conformation of our 2,4,6,-substituted pyrimidine scaffolds (5b, 5n and 6a) and the


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WZ4002/CO-1686 shape. Comparative analysis of both structure types revealed that the U-shape of WZ4002, the significantly populated geometry (out of four basins) that resembles the binding mode most closely, to a large extent, already exists in solution prior to interacting with the target protein. This favorable preconfiguration triggers the superior inhibitory effect of this compound because the free energy penalty that must be paid in order to bind to the target protein is much lower than that incurred by non-preconfigured species. In the case of our compounds, we similarly found three discrete conformational basins of which only two are significantly populated with mirror-like conformations that are adopted in solution. For the nonzero populated basin closest to the binding mode, at least two dihedrals have to rotate which may result in an increased penalty and, therefore, reduced the inhibitory effect. Preconfiguration exists for this class, but not to the same extent and similar relevance as for WZ4002. The compound that is most active against the double mutant exhibits the largest average preconfiguration ratio, although the effect is too small to be the only reason for the observed activity trend. The results presented in this paper indicate that conformation control during ligand design is important and furthermore demonstrate the feasibility of computational tools to address this challenge. A further investigation of pharmacokinetic parameters such as solubility, cell permeability and drug-absorption for 5b and 6a revealed an excellent aqueous solubility for both compounds and a sufficient cellular permeability for 6a in an artificial membrane system. However, we observed a dramatic efflux rate for 5b and 6a illustrating a moderate drug-absorption that leads to low cellular receptor occupancy, and thereby providing a reasonable explanation for their moderate cellular efficacy in the NSCLC cell lines.


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In summary, we have identified a novel class of irreversible and mutant-selective EGFR inhibitors, which may stimulate further approaches to develop covalently modulating inhibitors with increased target residence time.

Experimental Section Reagents and Materials. All supplies for the EGFR HTRF assay kit were purchased from CisBio (Bagnols-sur-Cèze, France). Small volume (20 µL fill volume) white round bottom 384-well plates were obtained from Greiner Bio-One GmbH (Solingen, Germany).

Activity-Based Assay for IC50 Determination and Kinetic Characterization. IC50 determinations for EGFR and its mutants (Carna Biosciences, lot13CBS-0005K for EGFR-wt; Invitrogen, lot279551C for EGFR-L858R and Invitrogen, lot350247C for EGFRL858R/T790M) were performed with the HTRF KinEASE-TK assay from Cisbio according to the manufacturer’s instructions. Briefly, the amount of EGFR in each reaction well was set to 0.6 ng EGFR wild type (0.67 nM), 0.1 ng EGFR L858R (0.11 nM) or 0.07 ng EGFR T790M/L858R (0.08 nM), respectively. An artificial substrate peptide (TK-substrate from Cisbio) was phosphorylated by EGFR. After completion of the reaction (reaction times: 25 min for wt, 15 min for L858R, 20 min for T790M/L858R), the reaction was stopped by addition of buffer containing EDTA as well as, an anti-phosphotyrosine antibody labeled with europium cryptate and streptavidin labeled with the fluorophore XL665. FRET between europium cryptate and XL665 was measured after an additional hour of incubation to quantify the phosphorylation


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of the substrate peptide. ATP concentrations were set at their respective Km-values (9.5 µM for EGFR-wt, 9 µM for EGFR-L858R and 4 µM for EGFR-L858R/T790M) while a substrate concentration of 1 µM, 225 nM and 200 nM, respectively, was used. Kinase and inhibitor were preincubated for 30 min (EGFR-wt) and 1 h (EGFR-L858R and EGFR-L858R/T790M) before the reaction was started by addition of ATP and substrate peptide. A Tecan infinite M1000 plate reader was used to measure the fluorescence of the samples at 620 nm (Eu-labeled antibody) and 665 nm (XL665 labeled streptavidin) 60 µs after excitation at 317 nm. The quotient of both intensities for reactions made with eight different inhibitor concentrations was fit to a Hill fourparameter equation using XLfit (IDBS, Surrey, UK) to determine IC50 values. Each reaction was performed in duplicate, and at least three independent determinations of each IC50 were made. For kinetic characterization (kinact/Ki) of 5a and 6b, the respective inhibitors were incubated with EGFR wildtype, L858R or T790M/L858R, respectively over different periods of time (2-90 min) whereas durations of enzymatic and stop reactions were kept constant as stated above. A six-fold dilution series (eight data points per IC50 curve) starting at 20 µM final compound concentrations was applied. Compound dilutions were generated using the acoustic dispensing system “ECHO 520 Liquid Handler” from Labcyte (Sunnyvale, California, USA) and the according dose-response software “Echo Dose-Response v1.5.4”. Calculated IC50 values were plotted versus incubation time and data was fit as described in the literature to determine kinact and Ki (See Supplementary Information).42

Crystallization and Structure Determination of cSrc-DM-1a, cSrc-DM-5b and cSrc-DM5c.


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Inhibitor 1a was co-crystallized with cSrc-DM (cSrc-DM was expressed and purified as described elsewhere18) using conditions similar to those previously reported by Michalczyk et al.18 Briefly, final concentrations of 900 µM inhibitor (100 mM stock in DMSO) and 180 µM cSrc-DM (stored in 50 mM Tris pH 8.0, 100 mM NaCl, 1 mM DTT, and 5 % glycerol (v/v)) were pre-incubated for 1 h on ice to form the enzyme-inhibitor complex prior to crystallization. Crystals were grown using the hanging drop method at 20°C after mixing 1 µL protein-inhibitor solution with 1 µL reservoir solution (0.085-0.125 mM MES, pH 6.0-7.0, 9-11.5 % PEG20000). For generating the co-crystal structures of cSrc-DM-5b and cSrc-DM-5c, 565 µM inhibitor (prepared in DMSO) was preincubated along with 282 µM cSrc-DM for 2 h at room temperature to form the covalent enzyme-inhibitor complex prior to crystallization. The crystals were grown using the hanging drop method at 25 °C after mixing 1-1.5 µL of protein-inhibitor solution with 1 µL of reservoir solution (0-0.03 M NaCl, 9-20 % ethylene glycol for cSrc-DM-5b and 0.01 M NaCl, 11 % ethylene glycol for cSrc-DM-5c). All crystals were frozen with further addition of 25-30 % (v/v) glycerol. The data set for the complex crystal structure of cSrc-DM-5c was collected in-house to a resolution of 2.7 Å using wavelengths close to 1.5 Å. Diffraction data of cSrc-DM-1a and -5b were collected at the PX10SA beamline of the Swiss Light Source (PSI, Villingen, Switzerland) to resolutions of 3.0 Å and 2.3 Å respectively using wavelengths close to 1 Å. All data sets were processed with XDS65 and scaled using XSCALE65.

Structure Determination and Refinement of cSrc-DM-1a, cSrc-DM-5b and cSrc-DM-5c. The complex crystal structures of cSrc-DM-1a, cSrc-DM-5b and cSrc-DM-5c were solved by molecular replacement with PHASER66 using structure 2HWP36 or 2OIQ67 as template. The two cSrc molecules in the asymmetric unit were manually modified using the program COOT.68 The


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model was first refined with CNS69 using simulated annealing to remove model bias. The final refinement was performed with REFMAC570. Inhibitor topology files were generated using the Dundee PRODRG2 server.71 Refined structures were validated with PROCHECK.71 Data collection, structure refinement statistics, PDB-ID codes, further details for data collection are provided in Table S2. PyMOL72 was used for generating the figures.

Viability Assay. H1975, A431, H661 and HCC827 cells were obtained from the American Type Culture Collection (ATCC). Cells were seeded on day 1 at cell numbers that assure linearity and optimal signal intensity. After culturing for 24 hours in serum- and antibiotics-containing media in humidified chambers at 37 °C/5 % CO2 the cells were incubated for 96 hours with EGFR inhibitors in serial dilutions (14 nM to 30 µM) and DMSO as control. Viability studies were carried out on day 5 using CellTiter Glo Assay (Promega, USA) that is a homogeneous method of determining the number of viable cells in culture. It is based on quantification of ATP, indicating the presence of metabolically active cells. For these studies, CellTiter Glo Reagent was prepared according to the instructions of the kit. Thereon, reagent and assay plates were equilibrated at room temperature for 20 min. Equal volumes of the reagent were added to the volume of culture medium present in each well. The plates were mixed for 2 minutes on an orbital shaker. The microplates were then incubated at room temperature for 10 minutes for stabilization of the luminescent signal. Following incubation the luminescence was recorded on a Victor microplate reader (Perkin Elmer) using 200 ms integration time. The data was then analyzed with Excel using the XLfit-Plugin (dose response Fit 205) for GI50-determination. As quality control the Z’-factor was calculated from 16 positive and negative control values. Only


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assay results showing a Z´-factor ≥ 0.5 were used for further analysis. All experimental points were measured in duplicates for each plate and were replicated in at least two plates.

Solubility and cell permeability measurements. For determining kinetic solubility, the compound was diluted from a 10 mM stock in DMSO to a final concentration of 500 µM in 50 mM Hepes buffer, pH 7.4. Following an incubation of 90 minutes at room temperature on a shaker, the aqueous dilution was filtrated through a 0.2 µm PVDF filter and the optical density between 250 and 500 nm was measured in intervals of 10 nm. The kinetic solubility was calculated from the area under the curve (AUC) between 250 and 500 nm and normalized to absorption of a dilution of the compound in acetonitrile.73 Absorption was assessed using PAMPA (Parallel artificial membrane permeability assay) and Caco-2 cell culture. For PAMPA, the compound was diluted from a 10 mM stock in DMSO to a final concentration of 500 µM in 50 mM Hepes buffer pH 7.4 and transferred onto a transwell membrane covered with a membrane-forming solution of 10% 1.2 Dioleyl-sn-glycer-3phosphocholine (Sigma Aldrich) and 0.5% (w/v) cholesterol (Sigma Aldrich) in dodecane. Following an incubation of 16 hours at room temperature in a wet chamber, the optical density of the solution in the receiver well was measured between 250 and 500 nm in intervals of 10 nm. The percent flux was calculated from the AUC between 250 and 500 nm and normalized to the absorption of the compound following a 16 hour incubation in a parallel transwell containing a membrane covered with 50% methanol in 50 mM Hepes buffer pH 7.4.44 For Caco-2 cell culture, a 10 mM DMSO stock of the compound was diluted to a final concentration of 5 µM in HBSS buffer pH 7.4 and incubated for 2 hours at 37°C and 5% CO2 on a monolayer of Caco-2 cells (ATCC) that had been grown on a transwell membrane (Millipore, Schwalbach, Germany) for


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21 days. The compound concentration was measured in the receiver as well as the donor well. Apparent permeability (Papp) from either the apical to basolateral direction or vice versa was calculated by the equation: Papp = 1/AC0 (dQ/dt), where A is the membrane surface area, C0 is the donor drug concentration at t = 0, and dQ/dt is the amount of drug transported within the given time period of 2 hours.

Mass Spectrometry Experiments. We used the drug-resistant mutant variant of EGFR (EGFR-T790M) for MS experiments. We incubated a mixture of 52 µM of protein with 100 µM of inhibitor in buffer (25 mM TRIS, 250 mM NaCl, 10 % glycerol, 1 mM TCEP, pH 8) on ice for 1 h. We analyzed the aliquots by ESI-MS using an Agilent 1100 Series HPLC System connected to a ThermoFinnigan LTQ Linear Ion Trap mass spectrometer. Therefore, 6 µL of sample was injected and separated using a Vydac 214TP C4 5µm column (150 mm x 2.1 mm) starting at 20 % of solvent B for 5 minutes followed by a gradient up to 90% of solvent B over 14 min with a flow rate of 210 µL/min with 0.1 % TFA in water as solvent A and 0.1 % TFA in acetonitrile. A mass range of 700 to 2000 m/z was scanned and raw data was deconvoluted and analyzed with MagTran software74. For nano-LC-MS/MS measurements the samples were incubated with 10 mM iodoacetamide for 30 min at RT in the dark, in order to carbamidomethylate all free cysteine residues. Next, 1 µg of each sample was digested using the broad specificity protease subtilisin (Sigma Aldrich) to obtain a high sequence coverage. Therefore, subtilisin was added in a 1:10 ratio (protease:protein) and the samples were digested for 20 min at 5 °C. The digestion was quenched by addition of 1% TFA and 2 pmol per sample were analyzed by nano-LC-MS/MS using an


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Orbitrap Fusion mass spectrometer (Thermo Scientific), online-coupled to an Ultimate 3000 nano RSLC system (Thermo Scientific). Peptides were preconcentrated on a 75 µm x 2 cm C18 trapping column for 10 min using 0.1% TFA (v/v) at a flow rate of 20 µL/min, followed by separation on a 75 µm x 50 cm C18 main column (both Pepmap, Thermo Scientific) with a 60 min LC gradient ranging from 3-42% B (84% acetonitrile in 0.1% formic acid) at a flow rate of 250 nL/min. MS survey scans were acquired in the Orbitrap from 300 to 1500 m/z at a resolution of 120,000 using the polysiloxane ion at 445.12003 m/z as lock mass. The most intense ions were isolated with a 1.6 Da window for Top Speed (3 s) fragmentation using a charge state-based decision tree including collisioninduced dissociation (CID; +1), higher-energy collisional dissociation (HCD; +2, +3) and electron transfer dissociation (ETD >+3). MS/MS spectra were acquired in the Orbitrap at a resolution of 15,000, taking into account a dynamic exclusion of 6 s. Normalized collision energies of 35 and 30 were used for CID and HCD, respectively. For ETD reagent target and ETD reaction time were set to 200,000 and 100 ms, respectively. AGC target values were set to 400,000 for MS and 50,000 for MS/MS (100,000 for ETD). Raw data were searched against an in-house generated database containing the sequence of EGFR-T790M in a yeast background (SGD database, 6,879 target sequences) using Mascot 2.4 with the following parameters: (i) ‘none’ as protease, (ii) MS and MS/MS tolerances of 5 ppm and 0.02 Da, (iii) carbamidomethylation at Cys (+57.0214 Da), 5b at Cys (+434.2178 Da), and 6a at Cys (470.2178 Da) as variable modifications.

Construct Design of EGFR-T790M.


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DNA encoding residues comprising the kinase domain of human EGFR (uniprot entry P00533, residues 695-1022) were synthesized (GeneArt, life technologies) including an N-terminal polyhistidine tag and recognition site for thrombin protease (MGHHHHHHVDLVPRG), the point mutation T790M was introduced by side-directed mutagenesis (QuikChange, Stratagene/Agilent Technologies). The construct was cloned into pIEX/Bac3 expression vector (Merck Millipore), using NcoI and Bsu36I restriction sites, for deployment in BacMagic expression system (Merck Millipore). Transfection, virus generation and amplification was carried out in Spodoptera frugiperda cell line Sf9 following the BacMagic protocol.

Protein Expression and Purification. The protein was expressed in Sf9 cells using the BacMagic system. Following protein expression the cells were harvested (3000 x g, 10 min), resuspended in buffer A (50 mM TRIS, 500 mM NaCl, 10 % glycerol, 1 mM DTT, pH 8) and homogenized by french press. The lysate was cleared by centrifugation at 40.000 x g for 1 h and loaded on a column packed with Ni-NTA Superflow resin (Qiagen). The elution was done with a gradient of buffer B (buffer A + 500 mM imidazole) from 0-250 mM imidazole. Thrombin cleavage was carried out by dialysis against buffer C (25 mM TRIS, 50 mM NaCl, 10 % glycerol, 1 mM EDTA, 1 mM DTT, pH 8) overnight at 8 °C. Following the cleavage reaction the protein solution was loaded on a HiTrap-Q-HP column (GE Healthcare). The protein was eluted with buffer D (buffer C + 1 M NaCl) with a gradient of 0-250 mM NaCl. For the final purification step the fractions containing EGFR were combined, concentrated and applied to a HiLoad 16/600 superdex 75 pg column (GE Healthcare) in buffer E (25 mM TRIS, 250 mM NaCl, 1 mM DTT, 10 % Glycerol, pH 8). The purified protein was concentrated to 5 mg/mL and stored at -80 °C for further use.


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Theoretical Section Generation of Conformations. For all compounds studied (WZ4002, WZ4002-H, 5b, 5n, 6a) we applied an identical workflow that emerged after careful optimization of procedural parameters initially for WZ4002. Briefly, the protonation state at pH 7.4 in water was estimated by MoKa 2.5.275, 76 (S. Güssregen, Sanofi, private communication), resulting in a singly protonated (i.e. net-charged) species with an estimated specific tautomer preference (protonated secondary nitrogen of the piperazyl ring) of 82.3 %. The analogous tautomer was chosen for all other species. For fixed-charged force field simulations, GAFF48, 49 was applied with AM1-BCC charges computed by Antechamber49. Molecular dynamics simulations were performed by Amber 1277 at a temperature of 500 K for 108 time steps of 1 fs duration (100 ns) of a single compound exposed to a linearized PoissonBoltzmann model of water (ALPB78) using an Andersen thermostat79. We checked that an increase of the simulation time beyond that did not generate further conformations. After discarding the first 10000 steps, every 10000th snapshot were stored for subsequent geometry optimization to the next-nearest local minimum down to a maximum gradient norm of 10-4 kcal mol-1 Å-1. Structures with force field energies of 3 kcal mol-1 above the global minimum were removed from the final set before similar conformations were clustered using the utility g_cluster from Gromacs 4.6.380 that applies the Jarvis-Patrick algorithm81 for superimposed molecules with an RMSD criterion of 0.7 Å. This procedure yields the following numbers of conformations after applying the energy cutoff and numbers of clusters for WZ4002, WZ4002-H, 5b, 5n, 6a: 7750/154, 8109/143, 7685/131, 7788/111, 2147/451.


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Quantum Chemical Calculations. The global minima found for each cluster were optimized first in vacuo using density functional theory with the B3LYP82, 83 exchange-correlation model as implemented in Gaussian 0984 with the 6-31G(d) basis set85, followed by PCM optimization using default settings for water and the same basis set. The resulting sum of electronic and solvation energy defines GPCM. The same set of structures was subjected to single-point EC-RISM calculations at 298.15 K with the water model used earlier54, 55. The quantum chemical level of theory here was B3LYP/6311+G(d), the closure used was second order partial series expansion (PSE-2)86 utilizing a grid size of 0.3 Å and a maximum box length of 30 Å. Convergence was achieved when the free energy in solution (defining GEC-RISM as the sum of electronic energy and excess chemical potential) fell below 0.01 kcal mol-1. RMSDs to the binding mode were calculated with respect to the WZ4002 complex structure40 for all WZ4002 derivatives, and with respect to 5b for 5b, 5n, and 6a. All basin structures were visualized by VMD 1.9.187, their geometries are provided as supporting information.

Abbreviations ADME administration, distribution, metabolization and excretion; ALPB analytical linearized Poisson–Boltzmann; AM1-BCC semi-empirical (AM1) with bond charge correction (BCC); B3LYP Becke, three-parameter, Lee-Yang-Parr; cSrc-DM cSrc-(T338M/S345C); EC-RISM embedded cluster reference interaction site model; EGFR epidermal growth factor receptor; GAFF general Amber force field; mCPBA 3-chloroperoxybenzoic acid; ms mass-spectrometry; NSCLC non-small cell lung cancer; PCM polarizable continuum model; PR preconfiguration


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ratio; PSE partial series expansion; RMSD root mean square deviation; RTK receptor tyrosine kinase; SAR structure-activity relationship; TKI tyrosine kinase inhibitor.

Author Information Corresponding Author Information *Prof. Dr. Daniel Rauh: phone: +49 (0)231 – 755 7080, fax: +49 (0)231 – 755 7082, email: [email protected], *Prof. Dr. Stefan M. Kast: phone +49 0(231) – 755 3906, fax: +49 (0)231 – 755 3748, email: [email protected]

Notes The authors declare the following competing financial interest(s): RKT is a founder and shareholder of Blackfield AG/New Oncology; reports receiving commercial research grants from AstraZeneca, EOS, and Merck KgaA; and honoraria from AstraZeneca, Bayer, Blackfield AG/New Oncology, Boehringer Ingelheim, Clovis Oncology, Daiichi-Sankyo, Eli Lilly, Johnson & Johnson, Merck KgaA, MSD, Puma, Roche, and Sanofi. DR received consultant and lecture fees from Astra-Zeneca, Merck-Serono, Takeda, Pfizer, Novartis, Boehringer Ingelheim and Sanofi-Aventis.

Acknowledgment This work was co-funded by the German federal state North Rhine Westphalia (NRW) and the European Union (European Regional Development Fund: Investing In Your Future) as part of the PerMed NRW initiative (NEGECA), the German Federal Ministry for Science and Education (BMBF) as part of the NGFNplus program (grants 01GS08104, 01GS08101) and the hpCADD


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project (grant 01IH11002B) and as part of the e:Med program (grants 01ZX1303C, 01ZX1303A, 01ZX1406), by the Deutsche Forschungsgemeinschaft (DFG; through TH1386/3-1, RA 1055/31, and KA1381/5-1). RPZ and VT thank the Ministry for Innovation, Science and Research of the Federal State of Northrhine-Westphalia for financial support. Computer time on the LiDOng cluster at the ITMC Dortmund is also gratefully acknowledged.

References 1. Chen, P.; Xie, H.; Sekar, M. C.; Gupta, K.; Wells, A. Epidermal growth factor receptormediated cell motility: phospholipase C activity is required, but mitogen-activated protein kinase activity is not sufficient for induced cell movement. J Cell Biol 1994, 127, 847-857. 2. Datta, S. R.; Dudek, H.; Tao, X.; Masters, S.; Fu, H.; Gotoh, Y.; Greenberg, M. E. Akt phosphorylation of BAD couples survival signals to the cell-intrinsic death machinery. Cell 1997, 91, 231-241. 3. Pages, G.; Lenormand, P.; L'Allemain, G.; Chambard, J. C.; Meloche, S.; Pouyssegur, J. Mitogen-activated protein kinases p42mapk and p44mapk are required for fibroblast proliferation. Proc Natl Acad Sci U S A 1993, 90, 8319-8323. 4. Rosell, R.; Moran, T.; Queralt, C.; Porta, R.; Cardenal, F.; Camps, C.; Majem, M.; Lopez-Vivanco, G.; Isla, D.; Provencio, M.; Insa, A.; Massuti, B.; Gonzalez-Larriba, J. L.; PazAres, L.; Bover, I.; Garcia-Campelo, R.; Moreno, M. A.; Catot, S.; Rolfo, C.; Reguart, N.; Palmero, R.; Sanchez, J. M.; Bastus, R.; Mayo, C.; Bertran-Alamillo, J.; Molina, M. A.; Sanchez, J. J.; Taron, M.; Spanish Lung Cancer, G. Screening for epidermal growth factor receptor mutations in lung cancer. N Engl J Med 2009, 361, 958-967. 5. Suzuki, S.; Dobashi, Y.; Sakurai, H.; Nishikawa, K.; Hanawa, M.; Ooi, A. Protein overexpression and gene amplification of epidermal growth factor receptor in nonsmall cell lung carcinomas. An immunohistochemical and fluorescence in situ hybridization study. Cancer 2005, 103, 1265-1273. 6. Barker, A. J.; Gibson, K. H.; Grundy, W.; Godfrey, A. A.; Barlow, J. J.; Healy, M. P.; Woodburn, J. R.; Ashton, S. E.; Curry, B. J.; Scarlett, L.; Henthorn, L.; Richards, L. Studies leading to the identification of ZD1839 (IRESSA): an orally active, selective epidermal growth factor receptor tyrosine kinase inhibitor targeted to the treatment of cancer. Bioorg Med Chem Lett 2001, 11, 1911-1914.


40


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

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7. Greulich, H.; Chen, T. H.; Feng, W.; Jänne, P. A.; Alvarez, J. V.; Zappaterra, M.; Bulmer, S. E.; Frank, D. A.; Hahn, W. C.; Sellers, W. R.; Meyerson, M. Oncogenic transformation by inhibitor-sensitive and -resistant EGFR mutants. PLoS Med 2005, 2, e313. 8. Lynch, T. J.; Bell, D. W.; Sordella, R.; Gurubhagavatula, S.; Okimoto, R. A.; Brannigan, B. W.; Harris, P. L.; Haserlat, S. M.; Supko, J. G.; Haluska, F. G.; Louis, D. N.; Christiani, D. C.; Settleman, J.; Haber, D. A. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N Engl J Med 2004, 350, 2129-2139. 9. Moyer, J. D.; Barbacci, E. G.; Iwata, K. K.; Arnold, L.; Boman, B.; Cunningham, A.; DiOrio, C.; Doty, J.; Morin, M. J.; Moyer, M. P.; Neveu, M.; Pollack, V. A.; Pustilnik, L. R.; Reynolds, M. M.; Sloan, D.; Theleman, A.; Miller, P. Induction of apoptosis and cell cycle arrest by CP-358,774, an inhibitor of epidermal growth factor receptor tyrosine kinase. Cancer Res 1997, 57, 4838-4848. 10. Paez, J. G.; Jänne, P. A.; Lee, J. C.; Tracy, S.; Greulich, H.; Gabriel, S.; Herman, P.; Kaye, F. J.; Lindeman, N.; Boggon, T. J.; Naoki, K.; Sasaki, H.; Fujii, Y.; Eck, M. J.; Sellers, W. R.; Johnson, B. E.; Meyerson, M. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science 2004, 304, 1497-1500. 11. Pao, W.; Miller, V.; Zakowski, M.; Doherty, J.; Politi, K.; Sarkaria, I.; Singh, B.; Heelan, R.; Rusch, V.; Fulton, L.; Mardis, E.; Kupfer, D.; Wilson, R.; Kris, M.; Varmus, H. EGF receptor gene mutations are common in lung cancers from "never smokers" and are associated with sensitivity of tumors to gefitinib and erlotinib. Proc Natl Acad Sci U S A 2004, 101, 1330613311. 12. Sordella, R.; Bell, D. W.; Haber, D. A.; Settleman, J. Gefitinib-sensitizing EGFR mutations in lung cancer activate anti-apoptotic pathways. Science 2004, 305, 1163-1167. 13. Kobayashi, S.; Boggon, T. J.; Dayaram, T.; Jänne, P. A.; Kocher, O.; Meyerson, M.; Johnson, B. E.; Eck, M. J.; Tenen, D. G.; Halmos, B. EGFR mutation and resistance of nonsmall-cell lung cancer to gefitinib. N Engl J Med 2005, 352, 786-792. 14. Pao, W.; Miller, V. A.; Politi, K. A.; Riely, G. J.; Somwar, R.; Zakowski, M. F.; Kris, M. G.; Varmus, H. Acquired resistance of lung adenocarcinomas to gefitinib or erlotinib is associated with a second mutation in the EGFR kinase domain. PLoS Med 2005, 2, e73. 15. Sequist, L. V.; Waltman, B. A.; Dias-Santagata, D.; Digumarthy, S.; Turke, A. B.; Fidias, P.; Bergethon, K.; Shaw, A. T.; Gettinger, S.; Cosper, A. K.; Akhavanfard, S.; Heist, R. S.; Temel, J.; Christensen, J. G.; Wain, J. C.; Lynch, T. J.; Vernovsky, K.; Mark, E. J.; Lanuti, M.; Iafrate, A. J.; Mino-Kenudson, M.; Engelman, J. A. Genotypic and histological evolution of lung cancers acquiring resistance to EGFR inhibitors. Sci Transl Med 2011, 3, 75ra26. 16. Yun, C. H.; Mengwasser, K. E.; Toms, A. V.; Woo, M. S.; Greulich, H.; Wong, K. K.; Meyerson, M.; Eck, M. J. The T790M mutation in EGFR kinase causes drug resistance by increasing the affinity for ATP. Proc Natl Acad Sci U S A 2008, 105, 2070-2075.


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17. Klüter, S.; Simard, J. R.; Rode, H. B.; Grütter, C.; Pawar, V.; Raaijmakers, H. C.; Barf, T. A.; Rabiller, M.; van Otterlo, W. A.; Rauh, D. Characterization of irreversible kinase inhibitors by directly detecting covalent bond formation: a tool for dissecting kinase drug resistance. ChemBioChem 2010, 11, 2557-2566. 18. Michalczyk, A.; Kluter, S.; Rode, H. B.; Simard, J. R.; Grutter, C.; Rabiller, M.; Rauh, D. Structural insights into how irreversible inhibitors can overcome drug resistance in EGFR. Bioorg Med Chem 2008, 16, 3482-3488. 19. Sos, M. L.; Rode, H. B.; Heynck, S.; Peifer, M.; Fischer, F.; Klüter, S.; Pawar, V. G.; Reuter, C.; Heuckmann, J. M.; Weiss, J.; Ruddigkeit, L.; Rabiller, M.; Koker, M.; Simard, J. R.; Getlik, M.; Yuza, Y.; Chen, T. H.; Greulich, H.; Thomas, R. K.; Rauh, D. Chemogenomic profiling provides insights into the limited activity of irreversible EGFR Inhibitors in tumor cells expressing the T790M EGFR resistance mutation. Cancer Res 2010, 70, 868-874. 20. Kwak, E. L.; Sordella, R.; Bell, D. W.; Godin-Heymann, N.; Okimoto, R. A.; Brannigan, B. W.; Harris, P. L.; Driscoll, D. R.; Fidias, P.; Lynch, T. J.; Rabindran, S. K.; McGinnis, J. P.; Wissner, A.; Sharma, S. V.; Isselbacher, K. J.; Settleman, J.; Haber, D. A. Irreversible inhibitors of the EGF receptor may circumvent acquired resistance to gefitinib. Proc Natl Acad Sci U S A 2005, 102, 7665-7670. 21. Engelman, J. A.; Zejnullahu, K.; Gale, C. M.; Lifshits, E.; Gonzales, A. J.; Shimamura, T.; Zhao, F.; Vincent, P. W.; Naumov, G. N.; Bradner, J. E.; Althaus, I. W.; Gandhi, L.; Shapiro, G. I.; Nelson, J. M.; Heymach, J. V.; Meyerson, M.; Wong, K. K.; Jänne, P. A. PF00299804, an irreversible pan-ERBB inhibitor, is effective in lung cancer models with EGFR and ERBB2 mutations that are resistant to gefitinib. Cancer Res 2007, 67, 11924-11932. 22. Li, D.; Ambrogio, L.; Shimamura, T.; Kubo, S.; Takahashi, M.; Chirieac, L. R.; Padera, R. F.; Shapiro, G. I.; Baum, A.; Himmelsbach, F.; Rettig, W. J.; Meyerson, M.; Solca, F.; Greulich, H.; Wong, K. K. BIBW2992, an irreversible EGFR/HER2 inhibitor highly effective in preclinical lung cancer models. Oncogene 2008, 27, 4702-4711. 23. Copeland, R. A.; Pompliano, D. L.; Meek, T. D. Drug-target residence time and its implications for lead optimization. Nat Rev Drug Discov 2006, 5, 730-739. 24. Heuckmann, J. M.; Rauh, D.; Thomas, R. K. Epidermal growth factor receptor (EGFR) signaling and covalent EGFR inhibition in lung cancer. J Clin Oncol 2012, 30, 3417-3420. 25. Singh, J.; Petter, R. C.; Baillie, T. A.; Whitty, A. The resurgence of covalent drugs. Nat Rev Drug Discov 2011, 10, 307-317. 26. Katakami, N.; Atagi, S.; Goto, K.; Hida, T.; Horai, T.; Inoue, A.; Ichinose, Y.; Koboyashi, K.; Takeda, K.; Kiura, K.; Nishio, K.; Seki, Y.; Ebisawa, R.; Shahidi, M.; Yamamoto, N. LUX-Lung 4: a phase II trial of afatinib in patients with advanced non-small-cell lung cancer who progressed during prior treatment with erlotinib, gefitinib, or both. J Clin Oncol 2013, 31, 3335-3341.


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27. Miller, V. A.; Hirsh, V.; Cadranel, J.; Chen, Y. M.; Park, K.; Kim, S. W.; Zhou, C.; Su, W. C.; Wang, M.; Sun, Y.; Heo, D. S.; Crino, L.; Tan, E. H.; Chao, T. Y.; Shahidi, M.; Cong, X. J.; Lorence, R. M.; Yang, J. C. Afatinib versus placebo for patients with advanced, metastatic non-small-cell lung cancer after failure of erlotinib, gefitinib, or both, and one or two lines of chemotherapy (LUX-Lung 1): a phase 2b/3 randomised trial. Lancet Oncol 2012, 13, 528-538. 28. Sequist, L. V.; Besse, B.; Lynch, T. J.; Miller, V. A.; Wong, K. K.; Gitlitz, B.; Eaton, K.; Zacharchuk, C.; Freyman, A.; Powell, C.; Ananthakrishnan, R.; Quinn, S.; Soria, J. C. Neratinib, an irreversible pan-ErbB receptor tyrosine kinase inhibitor: results of a phase II trial in patients with advanced non-small-cell lung cancer. J Clin Oncol 2010, 28, 3076-3083. 29. Zhou, W.; Ercan, D.; Chen, L.; Yun, C. H.; Li, D.; Capelletti, M.; Cortot, A. B.; Chirieac, L.; Iacob, R. E.; Padera, R.; Engen, J. R.; Wong, K. K.; Eck, M. J.; Gray, N. S.; Jänne, P. A. Novel mutant-selective EGFR kinase inhibitors against EGFR T790M. Nature 2009, 462, 10701074. 30. Walter, A. O.; Sjin, R. T.; Haringsma, H. J.; Ohashi, K.; Sun, J.; Lee, K.; Dubrovskiy, A.; Labenski, M.; Zhu, Z.; Wang, Z.; Sheets, M.; St Martin, T.; Karp, R.; van Kalken, D.; Chaturvedi, P.; Niu, D.; Nacht, M.; Petter, R. C.; Westlin, W.; Lin, K.; Jaw-Tsai, S.; Raponi, M.; Van Dyke, T.; Etter, J.; Weaver, Z.; Pao, W.; Singh, J.; Simmons, A. D.; Harding, T. C.; Allen, A. Discovery of a mutant-selective covalent inhibitor of EGFR that overcomes T790M-mediated resistance in NSCLC. Cancer Discov 2013, 3, 1404-1415. 31. Sequist, L. V.; Soria, J. C.; Goldman, J. W.; Wakelee, H. A.; Gadgeel, S. M.; Varga, A.; Papadimitrakopoulou, V.; Solomon, B. J.; Oxnard, G. R.; Dziadziuszko, R.; Aisner, D. L.; Doebele, R. C.; Galasso, C.; Garon, E. B.; Heist, R. S.; Logan, J.; Neal, J. W.; Mendenhall, M. A.; Nichols, S.; Piotrowska, Z.; Wozniak, A. J.; Raponi, M.; Karlovich, C. A.; Jaw-Tsai, S.; Isaacson, J.; Despain, D.; Matheny, S. L.; Rolfe, L.; Allen, A. R.; Camidge, D. R. Rociletinib in EGFR-mutated non-small-cell lung cancer. N Engl J Med 2015, 372, 1700-1709. 32. Cross, D. A.; Ashton, S. E.; Ghiorghiu, S.; Eberlein, C.; Nebhan, C. A.; Spitzler, P. J.; Orme, J. P.; Finlay, M. R.; Ward, R. A.; Mellor, M. J.; Hughes, G.; Rahi, A.; Jacobs, V. N.; Red Brewer, M.; Ichihara, E.; Sun, J.; Jin, H.; Ballard, P.; Al-Kadhimi, K.; Rowlinson, R.; Klinowska, T.; Richmond, G. H.; Cantarini, M.; Kim, D. W.; Ranson, M. R.; Pao, W. AZD9291, an irreversible EGFR TKI, overcomes T790M-mediated resistance to EGFR inhibitors in lung cancer. Cancer Discov 2014, 4, 1046-1061. 33. Jänne, P. A.; Yang, J. C.; Kim, D. W.; Planchard, D.; Ohe, Y.; Ramalingam, S. S.; Ahn, M. J.; Kim, S. W.; Su, W. C.; Horn, L.; Haggstrom, D.; Felip, E.; Kim, J. H.; Frewer, P.; Cantarini, M.; Brown, K. H.; Dickinson, P. A.; Ghiorghiu, S.; Ranson, M. AZD9291 in EGFR inhibitor-resistant non-small-cell lung cancer. N Engl J Med 2015, 372, 1689-1699. 34. Finlay, M. R.; Anderton, M.; Ashton, S.; Ballard, P.; Bethel, P. A.; Box, M. R.; Bradbury, R. H.; Brown, S. J.; Butterworth, S.; Campbell, A.; Chorley, C.; Colclough, N.; Cross, D. A.; Currie, G. S.; Grist, M.; Hassall, L.; Hill, G. B.; James, D.; James, M.; Kemmitt, P.; Klinowska, T.; Lamont, G.; Lamont, S. G.; Martin, N.; McFarland, H. L.; Mellor, M. J.; Orme, J. P.; Perkins, D.; Perkins, P.; Richmond, G.; Smith, P.; Ward, R. A.; Waring, M. J.; Whittaker, D.;


43

Page 45 of 69

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


Wells, S.; Wrigley, G. L. Discovery of a potent and selective EGFR inhibitor (AZD9291) of both sensitizing and T790M resistance mutations that spares the wild type form of the receptor. J Med Chem 2014, 57, 8249-67. 35. Dietlein, F.; Heuckmann, J.; Choidas, A.; Basu, D.; Habenberger, P.; Fang, Z.; OrtizCuaran, S.; Leenders, F.; Eickhoff, J.; Koch, U.; Getlik, M.; Termathe, M.; Sallouh, M.; Greff, Z.; Varga, Z.; Balke-Want, H.; Sos, M. L.; Peifer, M.; Reinhardt, H. C.; Örfi, L.; Kéri, G.; Ansen, S.; Heukamp, L. C.; Büttner, R.; Rauh, D.; Klebl, B.; Thomas, R. K. Reconstructing structure-activity relationships of kinase inhibitors by automated chemopanning. In Revision. 36. Blair, J. A.; Rauh, D.; Kung, C.; Yun, C. H.; Fan, Q. W.; Rode, H.; Zhang, C.; Eck, M. J.; Weiss, W. A.; Shokat, K. M. Structure-guided development of affinity probes for tyrosine kinases using chemical genetics. Nat Chem Biol 2007, 3, 229-238. 37. Tummino, P. J.; Copeland, R. A. Residence time of receptor-ligand complexes and its effect on biological function. Biochemistry 2008, 47, 5481-5492. 38. Barf, T.; Kaptein, A. Irreversible protein kinase inhibitors: balancing the benefits and risks. J Med Chem 2012, 55, 6243-6262. 39. Ward, R. A.; Anderton, M. J.; Ashton, S.; Bethel, P. A.; Box, M.; Butterworth, S.; Colclough, N.; Chorley, C. G.; Chuaqui, C.; Cross, D. A.; Dakin, L. A.; Debreczeni, J. E.; Eberlein, C.; Finlay, M. R.; Hill, G. B.; Grist, M.; Klinowska, T. C.; Lane, C.; Martin, S.; Orme, J. P.; Smith, P.; Wang, F.; Waring, M. J. Structure- and reactivity-based development of covalent inhibitors of the activating and gatekeeper mutant forms of the epidermal growth factor receptor (EGFR). J Med Chem 2013, 56, 7025-7048. 40. Zhou, W.; Ercan, D.; Jänne, P. A.; Gray, N. S. Discovery of selective irreversible inhibitors for EGFR-T790M. Bioorg Med Chem Lett 2011, 21, 638-643. 41. Wissner, A.; Mansour, T. S. The development of HKI-272 and related compounds for the treatment of cancer. Arch Pharm (Weinheim) 2008, 341, 465-477. 42. Krippendorff, B. F.; Neuhaus, R.; Lienau, P.; Reichel, A.; Huisinga, W. Mechanismbased inhibition: deriving K(I) and k(inact) directly from time-dependent IC(50) values. J Biomol Screen 2009, 14, 913-923. 43. Schwartz, P. A.; Kuzmic, P.; Solowiej, J.; Bergqvist, S.; Bolanos, B.; Almaden, C.; Nagata, A.; Ryan, K.; Feng, J.; Dalvie, D.; Kath, J. C.; Xu, M.; Wani, R.; Murray, B. W. Covalent EGFR inhibitor analysis reveals importance of reversible interactions to potency and mechanisms of drug resistance. Proc Natl Acad Sci U S A 2014, 111, 173-178. 44. Kansy, M.; Senner, F.; Gubernator, K. Physicochemical high throughput screening: parallel artificial membrane permeation assay in the description of passive absorption processes. J Med Chem 1998, 41, 1007-1010.


44


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 46 of 69

45. Shim, J.; Mackerell, A. D., Jr. Computational ligand-based rational design: Role of conformational sampling and force fields in model development. Medchemcomm 2011, 2, 356370. 46. Richards, M. R.; Brant, M. G.; Boulanger, M. J.; Cairo, C. W.; Wulff, J. E. Conformational analysis of peramivir reveals critical differences between free and enzymebound states. Medchemcomm 2014, 5, 1483-1488. 47. Forti, F.; Cavasotto, C. N.; Orozco, M.; Barril, X.; Luque, F. J. A Multilevel Strategy for the Exploration of the Conformational Flexibility of Small Molecules. Journal of Chemical Theory and Computation 2012, 8, 1808-1819. 48. Wang, J.; Wolf, R. M.; Caldwell, J. W.; Kollman, P. A.; Case, D. A. Development and testing of a general amber force field. J Comput Chem 2004, 25, 1157-1174. 49. Wang, J.; Wang, W.; Kollman, P. A.; Case, D. A. Automatic atom type and bond type perception in molecular mechanical calculations. J Mol Graph Model 2006, 25, 247-260. 50. Mobley, D. L.; Dumont, E.; Chodera, J. D.; Dill, K. A. Comparison of charge models for fixed-charge force fields: small-molecule hydration free energies in explicit solvent. J Phys Chem B 2007, 111, 2242-2254. 51. Yilmazer, N. D.; Korth, M. Comparison of molecular mechanics, semi-empirical quantum mechanical, and density functional theory methods for scoring protein-ligand interactions. J Phys Chem B 2013, 117, 8075-8084. 52. Tomasi, J.; Mennucci, B.; Cammi, R. Quantum mechanical continuum solvation models. Chem Rev 2005, 105, 2999-3093. 53. Kloss, T.; Heil, J.; Kast, S. M. Quantum chemistry in solution by combining 3D integral equation theory with a cluster embedding approach. J Phys Chem B 2008, 112, 4337-4343. 54. Kast, S. M.; Heil, J.; Gussregen, S.; Schmidt, K. F. Prediction of tautomer ratios by embedded-cluster integral equation theory. J Comput Aided Mol Des 2010, 24, 343-353. 55. Frach, R.; Kast, S. M. Solvation effects on chemical shifts by embedded cluster integral equation theory. J Phys Chem A 2014, 118, 11620-11628. 56. Cortes, J. E.; Talpaz, M.; Kantarjian, H. Ponatinib in Philadelphia chromosome-positive leukemias. N Engl J Med 2014, 370, 577. 57. Pemovska, T.; Johnson, E.; Kontro, M.; Repasky, G. A.; Chen, J.; Wells, P.; Cronin, C. N.; McTigue, M.; Kallioniemi, O.; Porkka, K.; Murray, B. W.; Wennerberg, K. Axitinib effectively inhibits BCR-ABL1(T315I) with a distinct binding conformation. Nature 2015, 519, 102-105.


45

Page 47 of 69

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


58. Leproult, E.; Barluenga, S.; Moras, D.; Wurtz, J. M.; Winssinger, N. Cysteine mapping in conformationally distinct kinase nucleotide binding sites: application to the design of selective covalent inhibitors. J Med Chem 2011, 54, 1347-1355. 59. Erve, J. C. Chemical toxicology: reactive intermediates and their role in pharmacology and toxicology. Expert Opin Drug Metab Toxicol 2006, 2, 923-946. 60. Guengerich, F. P.; MacDonald, J. S. Applying mechanisms of chemical toxicity to predict drug safety. Chem Res Toxicol 2007, 20, 344-369. 61. Park, B. K.; Boobis, A.; Clarke, S.; Goldring, C. E.; Jones, D.; Kenna, J. G.; Lambert, C.; Laverty, H. G.; Naisbitt, D. J.; Nelson, S.; Nicoll-Griffith, D. A.; Obach, R. S.; Routledge, P.; Smith, D. A.; Tweedie, D. J.; Vermeulen, N.; Williams, D. P.; Wilson, I. D.; Baillie, T. A. Managing the challenge of chemically reactive metabolites in drug development. Nat Rev Drug Discov 2011, 10, 292-306. 62.

Dungo, R. T.; Keating, G. M. Afatinib: first global approval. Drugs 2013, 73, 1503-1515.

63.

Cameron, F.; Sanford, M. Ibrutinib: first global approval. Drugs 2014, 74, 263-271.

64. Zambaldo, C.; Sadhu, K. K.; Karthikeyan, G.; Barluenga, S.; Daguer, J. P.; Winssinger, N. Selective affinity-based probe for oncogenic kinases suitable for live cell imaging. Chemical Science 2013, 4, 2088-2092. 65. Kabsch, W. Automatic Processing of Rotation Diffraction Data from Crystals of Initially Unknown Symmetry and Cell Constants. Journal of Applied Crystallography 1993, 26, 795-800. 66. Read, R. J. Pushing the boundaries of molecular replacement with maximum likelihood. Acta Crystallogr D Biol Crystallogr 2001, 57, 1373-1382. 67. Seeliger, M. A.; Nagar, B.; Frank, F.; Cao, X.; Henderson, M. N.; Kuriyan, J. c-Src binds to the cancer drug imatinib with an inactive Abl/c-Kit conformation and a distributed thermodynamic penalty. Structure 2007, 15, 299-311. 68. Emsley, P.; Cowtan, K. Coot: model-building tools for molecular graphics. Acta Crystallogr D Biol Crystallogr 2004, 60, 2126-2132. 69. Brünger, A. T.; Adams, P. D.; Clore, G. M.; DeLano, W. L.; Gros, P.; Grosse-Kunstleve, R. W.; Jiang, J. S.; Kuszewski, J.; Nilges, M.; Pannu, N. S.; Read, R. J.; Rice, L. M.; Simonson, T.; Warren, G. L. Crystallography & NMR system: A new software suite for macromolecular structure determination. Acta Crystallogr D Biol Crystallogr 1998, 54, 905-921. 70. Murshudov, G. N.; Vagin, A. A.; Dodson, E. J. Refinement of macromolecular structures by the maximum-likelihood method. Acta Crystallogr D Biol Crystallogr 1997, 53, 240-255. 71. Laskowski, R. A.; Macarthur, M. W.; Moss, D. S.; Thornton, J. M. Procheck - a Program to Check the Stereochemical Quality of Protein Structures. J Appl Crystallogr 1993, 26, 283291.


46


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

72.

Page 48 of 69

DeLano, W. L. The PyMOL Molecular Graphics System. http://www.pymol.org/, 2002

73. Avdeev, A. High-throughput measurements of solubility profiles. In Pharmacokinetic Optimization in Drug Research, 2001; pp 305-325. 74. Zhang, Z. Q.; Marshall, A. G. A universal algorithm for fast and automated charge state deconvolution of electrospray mass-to-charge ratio spectra. J Am Soc Mass Spectr 1998, 9, 225233. 75. Milletti, F.; Storchi, L.; Sforna, G.; Cruciani, G. New and original pKa prediction method using grid molecular interaction fields. J Chem Inf Model 2007, 47, 2172-2181. 76. Milletti, F.; Storchi, L.; Sforna, G.; Cross, S.; Cruciani, G. Tautomer enumeration and stability prediction for virtual screening on large chemical databases. J Chem Inf Model 2009, 49, 68-75. 77. Case, D. A.; Darden, T. A.; Cheatham, T. E.; Simmerling, C. L.; Wang, J.; Duke, R. E.; Luo, R.; Walker, R. C.; Zhang, W.; Merz, K. M.; Roberts, B.; Hayik, S.; Roitberg, A.; Seabra, G.; Swails, J.; Goetz, A. W.; Kolossváry, I.; Wong, K. F.; Paesani, F.; Vanicek, J.; Wolf, R. M.; Liu, J.; Wu, X.; Brozell, S. R.; Steinbrecher, T.; Gohlke, H.; Cai, Q.; Ye, X.; Wang, J.; Hsieh, M. J.; Cui, G.; Roe, D. R.; Mathews, D. H.; Seetin, M. G.; Solomon-Ferrer, R.; Sagui, C.; Babin, V.; Luchko, T.; Gusarov, S.; Kovalenko, A.; Kollman, P. A. In Amber12, University of California, San Francisco, 2012; 2012. 78. Sigalov, G.; Fenley, A.; Onufriev, A. Analytical electrostatics for biomolecules: beyond the generalized Born approximation. J Chem Phys 2006, 124, 124902. 79. Andersen, H. C. Molecular-Dynamics Simulations at Constant Pressure and-or Temperature. J Chem Phys 1980, 72, 2384-2393. 80. Van der Spoel, D.; Lindahl, E.; Hess, B.; Groenhof, G.; Mark, A. E.; Berendsen, H. J. C. GROMACS: Fast, flexible, and free. J Comput Chem 2005, 26, 1701-1718. 81. Jarvis, R. A.; Patrick, E. A. Clustering Using a Similarity Measure Based on Shared near Neighbors. Ieee Trans Comp 1973, C-22, 1025-1034. 82. Becke, A. D. Density-functional exchange-energy approximation with correct asymptotic behavior. Phys Rev A 1988, 38, 3098-3100. 83. Lee, C.; Yang, W.; Parr, R. G. Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density. Phys Rev B Condens Matter 1988, 37, 785-789. 84. Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Mennucci, B.; Petersson, G. A.; Nakatsuji, H.; Caricato, M.; Li, X.; Hratchian, H. P.; Izmaylov, A. F.; Bloino, J.; Zheng, G.; Sonnenberg, J. L.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; Hasegawa, J.; Ishida, M.; Nakajima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Vreven, T.; Montgomery Jr., J. A.; Peralta, J. E.; Ogliaro, F.; Bearpark, M. J.; Heyd, J.; Brothers, E. N.; Kudin, K. N.; Staroverov, V. N.; Kobayashi, R.; Normand, J.; Raghavachari,


47

Page 49 of 69

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


K.; Rendell, A. P.; Burant, J. C.; Iyengar, S. S.; Tomasi, J.; Cossi, M.; Rega, N.; Millam, N. J.; Klene, M.; Knox, J. E.; Cross, J. B.; Bakken, V.; Adamo, C.; Jaramillo, J.; Gomperts, R.; Stratmann, R. E.; Yazyev, O.; Austin, A. J.; Cammi, R.; Pomelli, C.; Ochterski, J. W.; Martin, R. L.; Morokuma, K.; Zakrzewski, V. G.; Voth, G. A.; Salvador, P.; Dannenberg, J. J.; Dapprich, S.; Daniels, A. D.; Farkas, Ö.; Foresman, J. B.; Ortiz, J. V.; Cioslowski, J.; Fox, D. J. Gaussian 09, Gaussian, Inc.: Wallingford, CT, USA, 2009. 85. Ditchfie.R; Hehre, W. J.; Pople, J. A. Self-Consistent Molecular-Orbital Methods .9. Extended Gaussian-Type Basis for Molecular-Orbital Studies of Organic Molecules. J Chem Phys 1971, 54, 724-728. 86. Kast, S. M.; Kloss, T. Closed-form expressions of the chemical potential for integral equation closures with certain bridge functions. J Chem Phys 2008, 129, 236101. 87. Humphrey, W.; Dalke, A.; Schulten, K. VMD: visual molecular dynamics. J Mol Graph 1996, 14, 33-38, 27-28.

Figure legends and Tables

Figure 1. Covalent and reversible EGFR inhibitors. A) First-, second- and third-generation EGFRinhibitors. B) Screening hit 1a from a phenotype screen of 80 NSCLC cell lines. C) X-ray crystal structure of 1a in complex with cSrc-DM (PDB-code: 5D12). Michael-acceptors are highlighted (green).

Figure 2. Modeling studies of various hinge-binding motifs. A) quinazoline- (2b) and B-D) pyrimidinebased inhibitors (3a, 5b and 6a) based on the X-ray crystal structure of 1a in complex with cSrcDM (PDB-code: 5D12). Proposed hydrogen bonds a show as red dotted lines.


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Figure 3. Extracted ion chromatograms (XICs) of the three different isoforms of the peptide GCLLDYVR, identified in (A) the control sample, and after treatment with (B) 5b and (C) 6a, respectively. As expected, the carbamidomethylated (i.e. non-modified) peptide is almost absent in samples the inhibitor-treated samples, whereas the corresponding modified versions can only be detected in the respective samples. All XICs are shown with a tolerance of 4 ppm.

Figure 4. Pyrimidine-based compounds in complex with cSrc-DM. Diagrams of the experimental electron densities of cSrc-DM-5b at 2.3 Å (PDB-code: 5D11) (A) and cSrc-DM-5c at 2.7 Å (PDB-code: 5D10) (B) resolution are shown (2Fo − Fc map contoured at 1σ). Hydrogen-bond interaction of the inhibitors with the hinge region (wheat) are illustrated by red dotted lines. The structural elements comprising the DFG-motif as well as helix C are displayed in violet and cyan, respectively.


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Figure 5. Minimum free energy conformations and conformational basins of inhibitors. Left: Structures in their predominant protonation state. Right: Population diagrams resulting from the computational analysis of conformational basins (identified by different colors) of selected compounds for different methods to treat the solvation contribution to the total free energy (PCM: triangles, ECRISM: squares), from top to bottom: WZ4002 (note that a single PCM data point at RMSD = 0.222 nm with population 0.43 is not shown in order to limit the scale), WZ4002-H (Cl substituted by H). Middle: Superimposition of corresponding minimum free energy conformations per basin (also shown as insets); red models (with blue balls representing nitrogen) show the respective reference conformation (WZ4002, PDB-code: 3IKA) of the ligand in the binding site. Boundaries between basins are (in nm, from left to right) for WZ4002, group 1: RMSD < 0.16, 2: 0.16 ≤ RMSD < 0.3, 3: 0.3 ≤ RMSD < 0.38, 4: 0.38 ≤ RMSD; for WZ4002H, group 1: RMSD < 0.2, 2: 0.2 ≤ RMSD < 0.36, 0.36 ≤ RMSD.

Figure 6. Population analysis results for (from top to bottom) 5b, 5n, 6a in analogy to Figure 5. Reference conformation (red model) in all cases is the crystallographic binding mode of 5b (PDB-code: 5D11). Boundaries between basins are (in nm, from left to right) for 5b, group 1: RMSD < 0.16, 2: 0.16 ≤ RMSD < 0.25, 3: 0.25 ≤ RMSD; 5n, group 1: RMSD < 0.14, 2: 0.14 ≤ RMSD < 0.25, 3: 0.25 ≤ RMSD; 6a, group 1: RMSD < 0.15, 2: 0.15 ≤ RMSD < 0.25, 3: 0.25 ≤ RMSD.


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Scheme 1. Synthesis of a subset of pyrimidine derivatives (3a-b).a a

Reagents and conditions: i) 3-Aminopyrazole, NaI, HCl (cat.), n-BuOH, 120 °C, 72%; ii)

Boc2O, Et3N, DCM, rt, 21% iii) Acryloyl or propionyl chloride, DIPEA, THF, 0 °C; iv) TFA in DCM, rt, 58-64% (2 steps).

Scheme 2. Synthesis of a subset of pyrimidine derivatives (4a, 5l-m).a a

Reagents and conditions: i) 5-Methyl-1H-pyrazol-3-amine, DIPEA, DMF, 90 °C, 54%; ii)

DHP, pTsOH, THF, 90 °C, 64%; iii) (3-Nitrophenyl)boronic acid, Pd(PPh3)4, Na2CO3, DMF/H2O (9:1), 90 °C, 70%; iv) Ammonium formate, Pd/C, EtOH, 90 °C; v) Acryloyl chloride, DIPEA, THF, 0 °C, 26% (5l); vi) TFA in DCM, rt, 73% (2 steps); vii) 3-Nitrophenol, K2CO3, DMF, 140 °C, 20%; viii) Propionyl chloride, DIPEA, THF, 0 °C, 27%).

Scheme 3. Synthesis of a subset of pyrimidine derivatives (5a-k, 5n-q, 6a-d).a a

Reagents and conditions: i) mCPBA, DCM/THF, 0 °C – rt, 86%; ii) Nitrophenol, NaH, THF,

0 °C – rt, 29-84% iii) Amine, DIPEA, NaI, DMF, 85-110 °C, 60-82%; iv) Methylpiperazine, 110 °C, 62-82%; v) Boc2O, Et3N, MeOH, rt or Boc2O, Cs2CO3, THF, rt, 56-95%; vi) Ammonium formate, Pd/C, EtOH or EtOAc, 90 °C, 48-87%; vii) Acryloyl or propionyl chloride, DIPEA, THF, 0 °C; viii) (E)-4-(Dimethylamino)but-2-enoic acid or (E)-4,4,4-Trifluorobut-2-


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enoic acid, EDC, HOBt, DIPEA, DCM, rt or (E)-4-(Dimethylamino)but-2-enoic acid, oxalyl chloride, DMF(cat.), THF, rt); ix) TFA in DCM, rt, 33-95% (2 steps)).


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Table 1. Overview of a focused small molecule library of pyrimidine- and quinazoline-based inhibitors and corresponding IC50 determinations on different EGFR mutant variants.

1

2

R

1a

-

1b

R

EGFR IC50 (µM)

3

R

Compound

wt

L858R

L858R/T790M

-

>10

1.9 ± 0.3

2.2 ± 0.1

-

-

>10

2.1 ± 0.1

2.2 ± 0.1

2a

ortho

-

-

>10

2.7 ± 0.9

1.1 ± 0.1

2b

meta

-

-

1.1 ± 0.2

0.5 ± 0.03

0.1 ± 0.02

2c

para

-

-

>10

>10

>10

2d

ortho

-

-

>10

>10

>10

2e

meta

-

-

3.7 ± 0.2

1.9 ± 2.8

0.4 ± 0.1

2f

para

-

-

>10

>10

>10


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3a

-

-

0.9 ± 0.1

0.8 ± 0.2

0.3 ± 0.07

3b

-

-

>10

3.4 ± 2.5

>10

4

-

-

>10

2.8 ± 0.7

2.5 ± 0.4

5a

ortho

CH3

0.9 ± 0.3

0.6 ± 0.3

2.1 ± 0.8

5b

meta

CH3

>10

0.03 ± 0.08

0.5 ± 0.3

5c

para

CH3

3.1 ± 0.8

1.8 ± 1.10

2.4 ± 0.9

CH3

>10

>10

>10

5d

ortho

5e

meta

CH3

>10

1.9 ± 1.2

>10

5f

para

CH3

>10

1.9 ± 0.5

0.7 ± 0.1

5g

ortho

NO2

CH3

>10

1.9 ± 0.3

1.6 ± 0.3

5h

meta

NO2

CH3

3.9 ± 0.8

2.3 ± 0.8

0.6 ± 0.2

5i

para

NO2

CH3

>10

1.8 ± 0.3

0.9 ± 0.1

5j

meta

NH2

CH3

>10

>10

4.9 ± 1.3

5k

para

NH2

CH3

>10

2.1 ± 0.6

1.4 ± 0.4

5l

H

CH3

>10

1.8 ± 0.2

0.9 ± 0.2

5m

H

CH3

>10

>10

>10

H

>10

2.0 ± 0.04

1.9 ± 0.6

5n

meta


54


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Page 56 of 69

5o

meta

H

>10

>10

>10

5p

para

CH3

1.7 ± 0.6

1.8 ± 0.8

>10

5q

para

CH3

2.0 ± 1.3

2.1 ± 1.0

1.5 ± 0.3

6a

H

1.7 ± 0.5

0.5 ± 0.2

0.07 ± 0.04

6b

H

>10

>10

8.6 ± 2.3

6c

H

6.7 ± 0.7

3.6 ± 0.5

0.7 ± 0.3

6d

Br

2.9 ± 1.5

0.4 ± 0.2

0.3 ± 0.2

6e

H

3.6 ± 0.8

0.6 ± 0.1

0.2 ± 0.1

-

>10

5.0 ± 3.9

4.9 ± 2.5

Gefitinib

30

30 ± 0.4

>30

n.i.

8.6 ± 1.6

18 ± 3.4

25 ± 4.0

n.i.

16 ± 1.7

11 ± 0.8

0.03 ± 0.007

0.03 ± 0.01

>0.01

>0.01

22 ± 2.2 a

a

11 ± 2.3 >30

c

H1975 L858R/T790M

a

8.6 ± 2.3

>30

HCC827 delE746-A750

a a

12 ± 1.1

1.7 ± 0.1

a

0.6 ± 0.08

a

Values without a standard deviation were obtained from a single measurement in triplicates. n.i.: no inhibitory effect at 30 µM compound concentration. a A431, b H661, c PC9del1


57

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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


Table 4. Torsion angle characteristics (in degrees) of reference structures and predicted main conformations per basin. Constituting atom numberings are specified in Figs. 4 and 5. Crystallographic reference binding mode geometries for comparison between experiment and computational prediction are WZ4002 for both WZ4002 Cl and H derivatives, and 5b for 5b, 5n, and 6a. The number of matching dihedrals (Nmatch) is defined as the sum of similar dihedral angle values per main conformer in comparison with the respective reference structure to within 20° (taking into account periodicity). For instance, the resulting count 3 for basin 1 of WZ4002 is the number of corresponding dihedral angle row entries (1,2,3,4), (2,3,4,5), and (5,6,7,8); the last angle deviates by ca. 57°.

WZ4002 Basin

Dihedral atoms

(1,2,3,4)

(2,3,4,5)

(5,6,7,8)

(6,7,8,9)

Crystal

-109.1

10.9

-1.4

153.2

1

-104.8

6.1

-1.5

-150.0

3

2

89.0

2.0

9.6

117.3

2

3

82.7

3.7

179.8

-177.6

1

4

24.0

-113.5

-176.8

177.6

0

1

-86.9

7.3

-0.5

-178.5

2

2

80.2

7.7

1.3

178.0

2

3

89.0

7.5

179.9

-178.5

1

Dihedral atoms

(1,2,3,4)

(2,3,4,5)

(6,7,8,9)

(7,8,9,10)

Crystal

89.3

13.6

-1.7

176.2

1

84.1

4.0

-179.9

-0.2

2

2

51.0

22.9

178.6

0.3

1

3

-51.2

-22.7

-179.4

0.0

0

1

95.2

-1.0

0.7

-0.7

3

2

50.4

22.5

-0.2

0.4

2

3

-51.2

-21.4

0.7

0.2

1

Nmatch

WZ4002-H Basin

5b Basin

5n Basin


58


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Page 60 of 69

6a Basin

1

96.1

-2.0

-179.8

0.3

2

2

51.2

22.4

178.8

1.9

1

3

-52.2

-20.6

-179.1

1.5

0

Table 5. Population analysis of conformational basins of selected compounds for different methods to treat the solvation contribution to the total free energy. “PR” (averaged over PCM and EC-RISM data in the last column) denotes the “preconfiguration ratio” defined as the inverse of the ratio of population of the farthest basin (measured by the RMSD) and the sum of all others. Specifically, PR = (p1+p2+p3)/p4 for WZ4002 and PR = (p1+p2)/p3 for the remaining compounds. Compound

Method

WZ4002

WZ4002-H

5b

5n

6a

p1

p2

p3

p4

PR

PCM

0.210

0.668

0.122

0.000

100:0

EC-RISM

0.043

0.103

0.854

0.000

100:0

PCM

0.407

0.445

0.148

-

85:15

EC-RISM

0.015

0.177

0.808

-

19:81

PCM

0.000

0.519

0.481

-

52:48

EC-RISM

0.000

0.447

0.553

-

45:55

PCM

0.000

0.515

0.484

-

52:48

EC-RISM

0.000

0.534

0.466

-

53:47

PCM

0.000

0.621

0.379

-

62:38

EC-RISM

0.002

0.451

0.549

-

45:55

100:0

52:48

48.5:51.5

52.5:47.5

53.5:46.5


59

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177x126mm (300 x 300 DPI)



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

177x99mm (300 x 300 DPI)


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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


177x71mm (300 x 300 DPI)



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

177x81mm (300 x 300 DPI)


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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


177x109mm (300 x 300 DPI)



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

177x166mm (300 x 300 DPI)


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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


177x64mm (300 x 300 DPI)



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

177x79mm (300 x 300 DPI)


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177x149mm (300 x 300 DPI)



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

108x55mm (300 x 300 DPI)


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