Quantitative Interrogation of the Human Kinome Perturbed by Two

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Quantitative Interrogation of the Human Kinome Perturbed by Two BRAF Inhibitors Weili Miao, and Yinsheng Wang J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.9b00134 • Publication Date (Web): 17 Apr 2019 Downloaded from http://pubs.acs.org on April 18, 2019

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Journal of Proteome Research

Quantitative Interrogation of the Human Kinome Perturbed by Two BRAF Inhibitors Weili Miao1 and Yinsheng Wang1,* 1

Department of Chemistry, University of California, Riverside, CA, 92521-0403, USA

*Correspondence author: Yinsheng Wang. Telephone: (951)827-2700; E-mail: [email protected]

1 ACS Paragon Plus Environment

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Abstract Oncogenic BRAF mutations contribute to the development of a number of cancers, and smallmolecule BRAF inhibitors have been approved by the Food and Drug Administration (FDA) for anti-cancer therapy. In this study, we employed two targeted quantitative proteomics approaches for monitoring separately the alterations in protein expression and ATP binding affinities of kinases in cultured human melanoma cells elicited by two FDA-approved small-molecule BRAF inhibitors, dabrafenib and vemurafenib. Our results showed that treatment with the two inhibitors led to markedly different reprograming of the human kinome. Furthermore, we confirmed that vemurafenib could compromise the ATP binding capacity of MAP2K5 in vitro and inhibit its kinase activity in cells. Together, our targeted quantitative proteomic methods revealed profound changes in expression levels of kinase proteins in cultured melanoma cells upon treatment with clinically used BRAF inhibitors and led to the discovery of novel putative target kinases for these inhibitors.

Key Words: quantitative proteomics, parallel-reaction monitoring, multiple-reaction monitoring, targeted proteomics, SILAC, kinase, kinase inhibitors, kinome, BRAF, melanoma


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Introduction BRAF is a serine/threonine-protein kinase that is involved in the mitogen-activated protein kinase (MAPK) signaling pathway that culminates in the activations of transcription factors important for cell growth, proliferation, and survival.1 Oncogenic BRAF mutations are among the most frequently observed mutations in human cancer, especially melanoma.2 The most common genotype is V600E (valine to glutamic acid),3 with recent reports suggesting that this mutation accounts for up to 90% of BRAF-mutant melanoma.4 Thus, small-molecule BRAF inhibitors, including vemurafenib and dabrafenib, have been approved by the Food and Drug Administration (FDA) for the treatment of metastatic melanomas harboring the V600E mutant BRAF.5-6 Although the response rate toward the inhibitors are high, most patients relapse at 6-8 months after therapy.7 Appropriate applications of these BRAF inhibitors in cancer chemotherapy require the knowledge about whether other kinases are also targeted by these inhibitors. The BRAF inhibitors are designed to disrupt directly the ATP-binding capabilities of BRAF.8 However, the ATPbinding domains are highly conserved in kinases;8-9 hence, compound selectivity is an important issue in the development of new kinase inhibitors.10 Despite with substantial efforts in optimizing the structures of BRAF inhibitors for selective binding toward BRAF, the inhibitors may also interact with the ATP binding pockets of other kinases.11-13 In addition, cancer cells may respond to inhibitor treatment by altering the protein expression levels of kinases.14 The knowledge about kinome reprogramming evoked by BRAF inhibitors and about their off-targets is, therefore, important for understanding more thoroughly the mechanisms through which these inhibitors confer therapeutic efficacy, side effects and resistance.



In this study, we applied two targeted quantitative proteomic approaches for monitoring separately the changes in protein expression and ATP-binding affinities of ~80% of non-redundant kinases in M14 cells15-20, which carry the oncogenic V600E mutation,21 upon treatment with two FDA-approved BRAF inhibitors, dabrafenib and vemurafenib. Our results confirmed previously reported kinase targets for these inhibitors, uncovered many novel putative targets, and revealed profound changes in expression levels of kinase proteins in melanoma cells upon treatment with these BRAF inhibitors. Experimental Procedures Cell culture WM-266-4 (ATCC), IGR-37 (obtained from Prof. Peter H. Duesberg),22 M14 (National Cancer Institute) cells were cultured in Dulbecco's modified eagle medium (DMEM). All culture media were supplemented with 10% fetal bovine serum (Invitrogen, Carlsbad, CA) and penicillin (100 IU/mL). The cells were incubated at 37°C in a humidified atmosphere containing 5% CO2. Approximately 2×107 cells were harvested, washed with ice-cold PBS for three times, and lysed by incubating on ice for 30 min with CelLytic M (Sigma) cell lysis reagent containing 1% protease inhibitor cocktail. The cell lysates were centrifuged at 9,000g at 4°C for 30 min, and the resulting supernatants collected. For SILAC experiments,23 M14 cells were cultured in a medium containing unlabeled lysine and arginine, or [13C6,15N2]-lysine and [13C6]-arginine for at least 2 weeks to promote complete incorporation of the stable isotope-labeled amino acids. Preparation of the desthiobiotinylated nucleotide affinity probe, and desthiobiotin labeling of ATP-binding proteins


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The desthiobiotinylated nucleotide affinity probes were synthesized following previously published procedures.24-25 Approximately 2×107 cells were harvested, washed for three times with ice-cold PBS, and lysed in a 1-mL lysis buffer, which contained 0.7% CHAPS, 50 mM HEPES (pH 7.4), 0.5 mM EDTA, 100 mM NaCl, and 10 µL (1:100) protease inhibitor cocktail on ice for 30 min. The cell lysates were centrifuged at 16,000g at 4°C for 30 min and the supernatants collected. Endogenous nucleotides in the resultant protein extract were removed by gel filtration using a NAP-5 column (Amersham Biosciences). Cell lysates were subsequently eluted into a buffer containing 50 mM HEPES (pH 7.4), 75 mM NaCl, and 5% glycerol. The amounts of proteins in the lysates were quantified using Quick Start Bradford Protein Assay (Bio-Rad). Prior to the labeling reaction, MgCl2, MnCl2, and CaCl2 were added to the concentrated cell lysate until their final concentrations reached 50, 5 and 5 mM, respectively. Tryptic digestion of protein lysates Cell lysates were washed with 8 M urea for protein denaturation, and dithiothreitol and iodoacetamide for cysteine reduction and alkylation, respectively. The proteins were subsequently digested with modified MS-grade trypsin (Pierce) at an enzyme/substrate ratio of 1:100 in 50 mM NH4HCO3 (pH 8.5) at 37°C overnight. The resulting peptide mixture was dried in a Speed-vac, desalted with OMIX C18 pipette tips (Agilent Technologies), and analyzed by LC-MS and MS/MS on a Q Exactive Plus quadrupole-Orbitrap or a TSQ Vantage triple-quadrupole mass spectrometer (Thermo Fisher Scientiﬁc). Sample preparation, multiple-reaction monitoring (MRM) and parallel-reaction monitoring (PRM) analyses



For assessing the alterations in ATP binding affinities of kinases in cultured cells induced by kinase inhibitors, we treated M14 cells with 100 nM dabrafenib or vemurafenib for 24 h. The cells were subsequently harvested by centrifugation and lysed, following the aforementioned procedures. The removal of endogenous nucleotides from protein lysate, labeling with desthiobiotin-conjugated ATP-affinity probe, tryptic digestion, and affinity purification of desthiobiotin-labeled peptides were conducted following the previously described procedures.16 The resultant peptide mixture was subjected to LC-MS/MS analysis on a TSQ Vantage triplequadrupole mass spectrometer, where the instrument was operated in the scheduled MRM mode and coupled with an Easy-nLC II system. The peptides were separated using a 130-min linear gradient of 2-35% acetonitrile in 0.1% formic acid and the flow rate was 230 nL/min. The spray voltage was 1.9 kV. Q1 and Q3 resolutions were 0.7 Da and the cycle time was 5 s. To assess how vemurafenib modulates the ATP binding affinities of kinases in cell lysate, we removed endogenous nucleotides from the whole-cell protein lysate of M14 cells, and treated the resultant lysate (1 mg/mL) with 100 nM vemurafenib (or DMSO control) at room temperature for 2 h prior to labeling with desthiobiotin-conjugated ATP-affinity probe. The samples were then processed and subjected to LC-MRM analysis in the same way as described above. To examine the differential expression of protein kinases in inhibitor-treated cells, we conducted both forward and reverse SILAC labeling experiments. In this context, the lysates of light-labeled, inhibitor-treated cells and heavy-labeled, mock-treated (with DMSO) cells were combined at 1:1 ratio (by mass) in the forward SILAC experiments, whereas the reverse SILAC experiments were performed in the opposite way. The whole-cell protein lysates were subsequently digested following the above-described procedures and the resulting peptides analyzed on a Q Exactive Plus quadrupole-Orbitrap mass spectrometer in the scheduled PRM 6 ACS Paragon Plus Environment

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mode. The mass spectrometer was coupled with an EASY-nLC 1200 system, and the samples were automatically loaded onto a 4-cm trapping column (150 µm i.d.) packed with ReproSil-Pur 120 C18-AQ resin (5 µm in particle size and 120 Å in pore size, Dr. Maisch GmbH HPLC) at 3 µL/min. The trapping column was coupled to a 20-cm fused silica analytical column (PicoTip Emitter, New Objective, 75 µm i.d.) packed with ReproSil-Pur 120 C18-AQ resin (3 µm in particle size and 120 Å in pore size, Dr. Maisch GmbH HPLC). The peptides were then separated using a 140-min linear gradient of 9-38% acetonitrile in 0.1% formic acid and at a flow rate of 300 nL/min. The spray voltage was 1.8 kV. The linear predictor of empirical RT from iRT

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for targeted kinase peptides was determined

by the linear regression of RT vs iRT of tryptic peptides of BSA obtained for the chromatography setup prior to the analysis of kinase peptides.16, 27-28 This RT-iRT linear relationship was redetermined in every eight LC-PRM runs by injecting another BSA tryptic digestion mixture. The targeted precursor ions were monitored in eight separate injections for each sample in scheduled PRM mode with an 8-min retention time window. The precursor ions of tryptic peptides from kinase proteins were isolated and collisionally activated in the HCD cell at a collision energy of 27. All raw data acquired from LC-MRM and LC-PRM analyses were processed using Skyline (version 3.5) 29 for the generation of extracted-ion chromatograms and for peak integration. The targeted peptides were first manually checked to ensure the overlaid chromatographic profiles of multiple fragment ions derived from light and heavy forms of the same peptide. The data were then analyzed to ensure that the distribution of the relative intensities of multiple transitions for the same precursor ion is correlated with the theoretical distribution in the kinome MS/MS spectral



library. The sum of peak areas from all transitions of light or heavy forms of peptides was used for quantification. Western blot WM-266-4, IGR-37, M14 cells were cultured in a 6-well plate and the cells were lysed at 4050% confluency following the above-described procedures. For Western blot analysis of p-ERK5, the cells were treated with 100 ng/mL FGF21 (Sigma-Aldrich) for 20 min and then harvested for cell lysis. The concentrations of proteins in the resulting lysates were determined by using Bradford Assay (Bio-Rad), and 10 μg protein lysate was denatured by boiling in Laemmli loading buffer and resolved by SDS-PAGE.

The proteins were subsequently transferred onto a

nitrocellulose membrane at 4°C overnight. The resulting membrane was blocked with PBS-T (PBS with 0.1% Tween 20) containing 5% milk (Bio-Rad) at 4°C for 6 h. The membrane was then incubated with primary antibody at 4°C overnight and subsequently with secondary antibody at room temperature for 1 h. After thorough washing with PBS-T, the HRP signal was detected with Pierce ECL Western Blotting Substrate (Thermo). Antibodies recognizing human AK1 (Santa Cruz Biotechnology, sc-165981, 1:1000 dilution), ARAF (Santa Cruz Biotechnology, sc-166771, 1:4000 dilution), BRAF (Santa Cruz Biotechnology, sc-5284, 1:4000 dilution), CHK1 (Cell Signaling Technology, 2360S, 1:2000 dilution), EGFR (Santa Cruz Biotechnology, sc-03, with a 1:10000 dilution), ERK5 (Santa Cruz Biotechnology, sc-393405, with a 1:1000 dilution), p-ERK5 (T218/Y220, Santa Cruz Biotechnology, sc-135761, with a 1:1000 dilution), IGF2R (Santa Cruz Biotechnology, sc-14408, 1:1000 dilution), JAK3 (Thermo Fishier Scientific, AHO1572, 1:1000 dilution), MAP3K5 (a.k.a. ASK1, Santa Cruz Biotechnology, sc-5294, 1:2000 dilution), MAP2K5 (a.k.a. MEK5, Santa Cruz Biotechnology, sc-365198, 1:2000 dilution), MAP3K3 (a.k.a. MEKK3, Santa Cruz Biotechnology, 8 ACS Paragon Plus Environment

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sc-136260, 1:1000 dilution), MEK1 (Santa Cruz Biotechnology, sc-6250, 1:2000 dilution), pMEK1 (Santa Cruz Biotechnology, sc-136542, 1:1000 dilution), mTOR (Cell Signaling Technology, 2972S, 1:1000 dilution), and STK26 (Abcam, ab52491, 1:20000 dilution) were employed as primary antibodies. Horseradish peroxidase-conjugated anti-rabbit IgG, IRDye® 680LT Goat anti-Mouse IgG and donkey anti-goat IgG-HRP (Santa Cruz Biotechnology, sc-2020, 1:10000 dilution) were used as secondary antibodies. Membranes were also probed with -actin antibody (Cell Signaling #4967, 1:10000 dilution) to confirm equal protein loading. Results and Discussion Profound Alterations in Kinase Protein Expression in M14 Human Melanoma Cells upon Treatment with BRAF Inhibitors We employed our recently reported scheduled LC-PRM analysis19 together with metabolic labeling using SILAC (Figure 1a)23 to assess the reprogramming of the human kinome in M14 cells induced by two BRAF inhibitors. The M14 cells were chosen because they carry the frequently observed BRAF V600E mutation.21 The results from the PRM-based targeted proteomic method yielded quantitative results for 302 and 289 unique kinases in M14 cells treated with dabrafenib and vemurafenib, respectively (Table S1). The same retention time and a dot product (dotp) value > 0.7 were shown for all PRM transitions (4-6 transitions) used in kinase peptide quantification (Figure S1).30 In addition, forward and reverse SILAC labeling experiments yielded consistent trends for the quantified kinases (Figure 1b & 1c, Table S1) and the average relative standard deviation for kinase protein quantification was 13.3% (Table S1). We further validated, by using Western blot analyses, the expression levels of 11 quantified kinases (mTOR, IGF2R, JAK3, CHK1, AK1, STK26, ARAF,



BRAF, MAP2K1, MAP3K3 and MAP3K5) in M14 cells with or without dabrafenib or vemurafenib treatment. The results demonstrated that the PRM method afforded robust quantifications of the protein expression levels of kinases (Figure 2). While both dabrafenib and vemurafenib were intended to target the V600E and V600K mutants of BRAF, treatment of M14 melanoma cells with these two inhibitors led to markedly different reprograming of the human kinome (Figures 3 & 4a). Specifically, treatment with 100 nM dabrafenib led to the up- and down-regulations of 27 and 42 kinases, respectively (Figure 3a), whereas the corresponding treatment with vemurafenib resulted in the up- and down-regulations of 58 and 5 kinases, respectively (Figure 3b). To explore further the attenuated expression of a large number of kinase proteins induced by dabrafenib, we performed a time-dependent experiment, where we treated M14 cells with 100 nM dabrafenib for shorter durations (i.e. 4 and 12 h) and examined, using the aforementioned LCPRM method, the protein expression levels of kinases at these two time points. Our result showed that many kinases exhibited augmented protein expression at 4 h following dabrafenib treatment and some kinases started to display diminished expression after 12 h (Figure S2, Table S1), suggesting that the decreased expression of most kinases occurred after 12 h of dabrafenib exposure (Figure S2, Table S1). Alterations in ATP Binding Affinities of Kinases Elicited by BRAF Inhibitors We further examined the changes in ATP binding affinities of kinases in cultured human cells following treatment with these BRAF inhibitors. Labeling with isotope-coded ATP affinity probes, in conjunction with LC-MS/MS analysis in the MRM mode, was found to afford a high-throughput and highly sensitive assessment about the ATP binding affinities of kinases in cultured human


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cells (Figure S3).15-16 In this respect, the ratio for a kinase (in inhibitor-treated over DMSO-treated cells) obtained from labeling with ATP affinity probe and LC-MRM is influenced by both the protein expression level and the ATP binding affinity of the kinase.31 We next applied the MRM-based method to assess the perturbations in ATP binding affinities of kinases (Figure S3) upon treatment with the two FDA-approved small-molecule BRAF inhibitors. We found that the ATP binding affinities of 38 and 9 kinases in M14 cells were attenuated following exposure to dabrafenib and vemurafenib, respectively (ratio < 0.67, Table S1, Figures S4). In particular, our results confirmed BRAF as a target kinase for both dabrafenib and vemurafenib (Figures 4b & 4c, Table S1). In addition, ARAF, which was previously identified as a direct target of dabrafenib,11, 32 was detected with the ATP binding affinity being attenuated by more than 40% (Figures 4b & S4, Table S1). In keeping with previous findings,33-34 we observed that vemurafenib exposure resulted in reduced ATP binding affinities of ARAF, BRAF and ZAK (Figure S4, Table S1). Our capability in identifying previously reported target kinases for these BRAF inhibitors underscored that our quantitative proteomic strategy is effective in uncovering potential kinase targets for small-molecule kinase inhibitors. Aside from discovering those kinases exhibiting reduced ATP binding affinities upon inhibitor treatment, we were able to detect 18 kinases displaying augmented binding affinities toward ATP upon treatments with dabrafenib or vemurafenib (i.e. with ratio > 1.5. Figure S4, Table S1). Among these kinases, CRAF is known to be activated by dabrafenib via a paradoxical pathway through the drug-mediated inhibition of one protomer of BRAF in the BRAF-CRAF heterodimer.34 Vemurafenib Suppresses the ATP-binding Affinity of MAP2K5



In addition to ARAF, BRAF and ZAK (Figure 3&4e-g), our results showed that vemurafenib treatment led to the diminished ATP binding affinities of several other kinases, including MAP2K5 (Figures 5a-c). In this vein, the inhibition of MAP2K5 by vemurafenib is even more pronounced than that of BRAF (Figure 5a), and similar inhibition of MAP2K5 was previously observed for PLX-4720, another BRAF inhibitor and a structural analog of vemurafenib.35 In agreement with the proteomic data, results from Western blot analysis showed that treatment of WM-266-4, IGR37 and M14 cells with vemurafenib led to a marked diminution in the kinase activity of MAP2K5 (as reflected by reduced p-ERK5), albeit with no appreciable change in protein expression level of MAP2K5 (Figure 5b-c, and S5). However, the proliferation of the M14 cells was not inhibited upon treatment with up to 1 µM BIX-02188, a small-molecule inhibitor for MAP2K5 (Figure S8). Thus, inhibition of MAP2K5 does not constitute a major mechanism for the cytotoxic effects of vemurafenib in BRAF-V600E mutant melanoma cells. For comparison, we also examined the changes in ATP binding affinities of kinases in the whole-cell lysate of M14 cells upon treatment with vemurafenib (Figure S6). We were able to quantify 268 kinases, among which 7 exhibited reduced ATP binding affinities after 100 nM vemurafenib treatment (Figure S7, Table S2). Among these kinases, ARAF, ZAK and MAP2K5 exhibited markedly lower ATP binding affinities in the lysate treated with vemurafenib (Figures 5d, 5e & S7). In addition, the in vitro assay with the use of cell lysate provides information about other kinases exhibiting lower ATP binding affinities upon treatment with 100 nM vemurafenib, including SRC (Figure 5f), IP6K1, FER, and PRPS1, whereas these four kinases did not display reduced ATP binding affinities in the above cell-based experiments. On the other hand, AK6, ABR, BRAF, CHUK, FGFR3, and PEAK1 displayed reduced ATP binding affinities in cellular experiments; however, all of them except CHUK1 were not detected in the in-vitro assay. The


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failure to detect these five kinases could be attributed to the lack of stability of these kinases, where the in-vitro experiment involved a 2-h incubation of the lysate with vemurafenib prior to ATP affinity probe labeling. The differences in vemurafenib-elicited variations in ATP binding affinities, as revealed from the in cellulo and in vitro assays, could arise from the presence of transient and unstable protein-protein interactions that may modulate the kinase’s capability in binding to ATP. Conclusions In this study, we employed two targeted proteomic approaches to explore the alterations in protein expression and ATP binding affinity of kinases in cultured human cells upon treatment with two FDA-approved BRAF inhibitors. We were able to quantify the perturbations in protein expression levels and ATP binding affinities of approximately 300 kinases in BRAF V600Ecarrying M14 human melanoma cells upon exposure to each BRAF inhibitor by employing LCPRM analysis of the tryptic digestion mixture of whole cell lysate and ATP-affinity probe pulldown coupled with LC-MRM analysis, respectively. We observed that, whereas treatment with vemurafenib stimulated the expression of a large number of kinases, exposure to dabrafenib led to diminished protein expression of a large number of kinases. In addition, the ATP binding affinity of MAP2K5 is inhibited by vemurafenib in both in cellulo and in vitro experiments, suggesting MAP2K5 is a novel binding target for vemurafenib. Consistent with the results obtained from quantitative proteomic analyses, Western blot analysis revealed that exposure of M14 cells to vemurafenib led to diminished phosphorylation of ERK5. The results from the present study, together with our recent work on imatinib,19 demonstrate that the two quantitative proteomic methods constitute powerful approaches for revealing, at the proteome-wide scale, the alterations in protein expression and ATP binding affinities of kinases. 13 ACS Paragon Plus Environment


In this regard, it is also worth discussing the limitations of the study. In particular, our quantitative proteomic experiments for ATP binding affinity assessment were conducted by using a single concentration of the ATP acyl nucleotide probe (i.e. 100 M) and BRAF inhibitor (i.e. 100 nM). Our underlying assumption is that, under such conditions, the ATP acyl nucleotide probe compete directly with BRAF inhibitors for binding to ATP binding pocket of kinases. On the grounds that the concentrations of kinases in cells can vary by several orders of magnitude, this assumption may not be valid for some kinases whose expression levels far exceed 100 nM. Thus, it will be important to examine, in the future, how the ATP affinity probe labeling efficiencies can be altered with the use of different concentrations of kinase inhibitors.

SUPPORTING INFORMATION: The following supporting information is available free of charge at ACS website http://pubs.acs.org: Table S1. Relative protein expression levels and ATP-binding affinities of kinases in M14 cells with or without dabrafenib or vemurafenib treatment (in Excel). Table S2. Differential ATP binding affinities of kinase proteins in lysate of M14 cells with and without a 24-hr treatment with 100 nM vemurafenib (in Excel). Figure S1. Extracted-ion chromatograms for monitoring the expression levels of representative kinases (AK1, STK26, MAP2K1, mTor). Figure S2. Heat map for time-dependent changes in kinase protein expression in M14 cells following treatment with 100 nM dabrafenib.


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Figure S3. The experimental strategy for MRM-based targeted proteomic approaches. Figure S4. Differential ATP-binding affinities of kinase proteins in M14 cells upon a 24-hr treatment with 100 nM dabrafenib (a) or vemurafenib (b). Figure S5. Western blot for monitoring the expression and phosphorylation levels of ERK5 in WM-266-4 and IGR-37 cells. Figure S6. The experimental strategy of using MRM-based targeted proteomic approach for probing the in vitro ATP-binding affinity of kinases upon treatment with vemurafenib. Figure S7. Differential ATP binding affinities of kinase proteins in lysates of M14 cells with and without vemurafenib treatment. Figure S8. Relative cell growth after MAP2K5 inhibitor treatment.

Acknowledgement.

This work was supported by the National Institutes of Health (R01

CA210072). Data Availability. All the raw files for LC-PRM and LC-MRM analyses of kinases were deposited into

PeptideAtlas

with

the

identifier

(http://www.peptideatlas.org/PASS/PASS01178).


number

of

PASS01178


References 1. McCain, J., The MAPK (ERK) Pathway: Investigational Combinations for the Treatment Of BRAF-Mutated Metastatic Melanoma. P. T. 2013, 38, 96-108. 2. Md Atiqur, R.; Ali, S.; Robert Anthony, S.; Alfred King-yin, L., BRAF inhibitor therapy for melanoma, thyroid and colorectal cancers: development of resistance and future prospects. Curr. Cancer Drug Targets 2014, 14, 128-143. 3. Davies, H.; Bignell, G. R.; Cox, C.; Stephens, P.; Edkins, S.; Clegg, S.; Teague, J.; Woffendin, H.; Garnett, M. J.; Bottomley, W.; Davis, N.; Dicks, E.; Ewing, R.; Floyd, Y.; Gray, K.; Hall, S.; Hawes, R.; Hughes, J.; Kosmidou, V.; Menzies, A.; Mould, C.; Parker, A.; Stevens, C.; Watt, S.; Hooper, S.; Wilson, R.; Jayatilake, H.; Gusterson, B. A.; Cooper, C.; Shipley, J.; Hargrave, D.; Pritchard-Jones, K.; Maitland, N.; Chenevix-Trench, G.; Riggins, G. J.; Bigner, D. D.; Palmieri, G.; Cossu, A.; Flanagan, A.; Nicholson, A.; Ho, J. W. C.; Leung, S. Y.; Yuen, S. T.; Weber, B. L.; Seigler, H. F.; Darrow, T. L.; Paterson, H.; Marais, R.; Marshall, C. J.; Wooster, R.; Stratton, M. R.; Futreal, P. A., Mutations of the BRAF gene in human cancer. Nature 2002, 417, 949-954. 4. Bradish, J. R.; Cheng, L., Molecular pathology of malignant melanoma: changing the clinical practice paradigm toward a personalized approach. Hum. Pathol. 2014, 45, 1315-1326. 5. Bollag, G.; Tsai, J.; Zhang, J.; Zhang, C.; Ibrahim, P.; Nolop, K.; Hirth, P., Vemurafenib: the first drug approved for BRAF-mutant cancer. Nat. Rev. Drug Discov. 2012, 11, 873-886. 6. Menzies, A. M.; Long, G. V., Dabrafenib and trametinib, alone and in combination for BRAFmutant metastatic melanoma. Clin. Cancer Res. 2014, 20, 2035-2043. 7. Chapman, P. B.; Hauschild, A.; Robert, C.; Haanen, J. B.; Ascierto, P.; Larkin, J.; Dummer, R.; Garbe, C.; Testori, A.; Maio, M.; Hogg, D.; Lorigan, P.; Lebbe, C.; Jouary, T.; Schadendorf, D.; Ribas, A.; O'Day, S. J.; Sosman, J. A.; Kirkwood, J. M.; Eggermont, A. M. M.; Dreno, B.; Nolop, K.; Li, J.; Nelson, B.; Hou, J.; Lee, R. J.; Flaherty, K. T.; McArthur, G. A., Improved survival with vemurafenib in melanoma with BRAF V600E mutation. N. Engl. J. Med. 2011, 364, 2507-2516. 8. Wu, P.; Nielsen, T. E.; Clausen, M. H., FDA-approved small-molecule kinase inhibitors. Trends Pharmacol. Sci. 2015, 36, 422-439. 9. Dancey, J.; Sausville, E. A., Issues and progress with protein kinase inhibitors for cancer treatment. Nat. Rev. Drug Discov. 2003, 2, 296-313. 10. Bosc, N.; Meyer, C.; Bonnet, P., The use of novel selectivity metrics in kinase research. BMC Bioinformatics 2017, 18, 17. 11. Fabian, M. A.; Biggs, W. H., 3rd; Treiber, D. K.; Atteridge, C. E.; Azimioara, M. D.; Benedetti, M. G.; Carter, T. A.; Ciceri, P.; Edeen, P. T.; Floyd, M.; Ford, J. M.; Galvin, M.; Gerlach, J. L.; Grotzfeld, R. M.; Herrgard, S.; Insko, D. E.; Insko, M. A.; Lai, A. G.; Lelias, J. M.; Mehta, S. A.; Milanov, Z. V.; Velasco, A. M.; Wodicka, L. M.; Patel, H. K.; Zarrinkar, P. P.; Lockhart, D. J., A small molecule-kinase interaction map for clinical kinase inhibitors. Nat. Biotechnol. 2005, 23, 329-36. 12. Davis, M. I.; Hunt, J. P.; Herrgard, S.; Ciceri, P.; Wodicka, L. M.; Pallares, G.; Hocker, M.; Treiber, D. K.; Zarrinkar, P. P., Comprehensive analysis of kinase inhibitor selectivity. Nat. Biotechnol. 2011, 29, 1046-1051. 13. Klaeger, S.; Heinzlmeir, S.; Wilhelm, M.; Polzer, H.; Vick, B.; Koenig, P.-A.; Reinecke, M.; Ruprecht, B.; Petzoldt, S.; Meng, C.; Zecha, J.; Reiter, K.; Qiao, H.; Helm, D.; Koch, H.; Schoof, M.; Canevari, G.; Casale, E.; Depaolini, S. R.; Feuchtinger, A.; Wu, Z.; Schmidt, T.; Rueckert, L.; Becker, W.; Huenges, J.; Garz, A.-K.; Gohlke, B.-O.; Zolg, D. P.; Kayser, G.; Vooder, T.; Preissner, R.; Hahne, H.; Tõnisson, N.; Kramer, K.; Götze, K.; Bassermann, F.; Schlegl, J.; Ehrlich, H.-C.; Aiche, S.; Walch, A.; Greif, P. A.; Schneider, S.; Felder, E. R.; Ruland, J.; Médard, G.; Jeremias, I.; Spiekermann, K.; Kuster, B., The target landscape of clinical kinase drugs. Science 2017, 358, eaan4368. 14. Duncan, J. S.; Whittle, M. C.; Nakamura, K.; Abell, A. N.; Midland, A. A.; Zawistowski, J. S.; Johnson, N. L.; Granger, D. A.; Jordan, N. V.; Darr, D. B.; Usary, J.; Kuan, P. F.; Smalley, D. M.; Major, B.; He, X.; Hoadley, K. A.; Zhou, B.; Sharpless, N. E.; Perou, C. M.; Kim, W. Y.; Gomez, S. M.; Chen, X.; 16 ACS Paragon Plus Environment

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Jin, J.; Frye, S. V.; Earp, H. S.; Graves, L. M.; Johnson, G. L., Dynamic reprogramming of the kinome in response to targeted MEK inhibition in triple-negative breast cancer. Cell 2012, 149, 307-21. 15. Xiao, Y.; Guo, L.; Wang, Y., A targeted quantitative proteomics strategy for global kinome profiling of cancer cells and tissues. Mol. Cell. Proteomics 2014, 13, 1065-1075. 16. Miao, W.; Xiao, Y.; Guo, L.; Jiang, X.; Huang, M.; Wang, Y., A high-throughput targeted proteomic approach for comprehensive profiling of methylglyoxal-induced perturbations of the human kinome. Anal. Chem. 2016, 88, 9773-9779. 17. Patricelli, M. P.; Nomanbhoy, T. K.; Wu, J.; Brown, H.; Zhou, D.; Zhang, J.; Jagannathan, S.; Aban, A.; Okerberg, E.; Herring, C.; Nordin, B.; Weissig, H.; Yang, Q.; Lee, J.-D.; Gray, N. S.; Kozarich, J. W., In situ kinase profiling reveals functionally relevant properties of native kinases. Chem. Bio. 2011, 18, 699710. 18. Patricelli, M. P.; Szardenings, A. K.; Liyanage, M.; Nomanbhoy, T. K.; Wu, M.; Weissig, H.; Aban, A.; Chun, D.; Tanner, S.; Kozarich, J. W., Functional interrogation of the kinome using nucleotide acyl phosphates. Biochem. 2007, 46, 350-358. 19. Miao, W.; Guo, L.; Wang, Y., Imatinib-Induced Changes in Protein Expression and ATP-Binding Affinities of Kinases in Chronic Myelocytic Leukemia Cells. Anal. Chem. 2019, 91, 3209-3214. 20. Miao, W.; Wang, Y., Targeted quantitative kinome analysis identifies PRPS2 as a promoter for colorectal cancer metastasis. J. Proteome Res. 2019, DOI: 10.1021/acs.jproteome.9b00119. 21. Hou, P.; Liu, D.; Dong, J.; Xing, M., The BRAF(V600E) causes widespread alterations in gene methylation in the genome of melanoma cells. Cell cycle 2012, 11, 286-295. 22. Bloomfield, M.; Duesberg, P., Inherent variability of cancer-specific aneuploidy generates metastases. Mol. Cytogenet. 2016, 9, 90. 23. Ong, S.-E.; Blagoev, B.; Kratchmarova, I.; Kristensen, D. B.; Steen, H.; Pandey, A.; Mann, M., Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol. Cell. Proteomics 2002, 1, 376-386. 24. Xiao, Y.; Guo, L.; Jiang, X.; Wang, Y., Proteome-wide discovery and characterizations of nucleotide-binding proteins with affinity-labeled chemical probes. Anal. Chem. 2013, 85, 3198-206. 25. Xiao, Y.; Guo, L.; Wang, Y., Isotope-Coded ATP Probe for Quantitative Affinity Profiling of ATPBinding Proteins. Anal. Chem. 2013, 85, 7478-7486. 26. Escher, C.; Reiter, L.; MacLean, B.; Ossola, R.; Herzog, F.; Chilton, J.; MacCoss, M. J.; Rinner, O., Using iRT, a normalized retention time for more targeted measurement of peptides. Proteomics 2012, 12, 1111-1121. 27. Miao, W.; Li, L.; Wang, Y., A targeted proteomic approach for heat shock proteins reveals DNAJB4 as a suppressor for melanoma metastasis. Anal. Chem. 2018, 90, 6835-6842. 28. Miao, W.; Li, L.; Wang, Y., Identification of helicase proteins as clients for HSP90. Anal. Chem. 2018, 90, 11751-11755. 29. MacLean, B.; Tomazela, D. M.; Shulman, N.; Chambers, M.; Finney, G. L.; Frewen, B.; Kern, R.; Tabb, D. L.; Liebler, D. C.; MacCoss, M. J., Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 2010, 26, 966-968. 30. de Graaf, E. L.; Altelaar, A. F.; van Breukelen, B.; Mohammed, S.; Heck, A. J., Improving SRM assay development: a global comparison between triple quadrupole, ion trap, and higher energy CID peptide fragmentation spectra. J. Proteome Res. 2011, 10, 4334-4341. 31. Cravatt, B. F.; Wright, A. T.; Kozarich, J. W., Activity-based protein profiling: from enzyme chemistry to proteomic chemistry. Annu. Rev. Biochem. 2008, 77, 383-414. 32. Peng, S.-B.; Henry, James R.; Kaufman, Michael D.; Lu, W.-P.; Smith, Bryan D.; Vogeti, S.; Rutkoski, Thomas J.; Wise, S.; Chun, L.; Zhang, Y.; Van Horn, Robert D.; Yin, T.; Zhang, X.; Yadav, V.; Chen, S.-H.; Gong, X.; Ma, X.; Webster, Y.; Buchanan, S.; Mochalkin, I.; Huber, L.; Kays, L.; Donoho, G. P.; Walgren, J.; McCann, D.; Patel, P.; Conti, I.; Plowman, Gregory D.; Starling, James J.; Flynn, Daniel L., Inhibition of RAF Isoforms and Active Dimers by LY3009120 Leads to Anti-tumor Activities in RAS or BRAF Mutant Cancers. Cancer Cell 2015, 28, 384-398.



33. Vin, H.; Ojeda, S. S.; Ching, G.; Leung, M. L.; Chitsazzadeh, V.; Dwyer, D. W.; Adelmann, C. H.; Restrepo, M.; Richards, K. N.; Stewart, L. R.; Du, L.; Ferguson, S. B.; Chakravarti, D.; Ehrenreiter, K.; Baccarini, M.; Ruggieri, R.; Curry, J. L.; Kim, K. B.; Ciurea, A. M.; Duvic, M.; Prieto, V. G.; Ullrich, S. E.; Dalby, K. N.; Flores, E. R.; Tsai, K. Y., BRAF inhibitors suppress apoptosis through off-target inhibition of JNK signaling. eLife 2013, 2, e00969. 34. Hatzivassiliou, G.; Song, K.; Yen, I.; Brandhuber, B. J.; Anderson, D. J.; Alvarado, R.; Ludlam, M. J. C.; Stokoe, D.; Gloor, S. L.; Vigers, G.; Morales, T.; Aliagas, I.; Liu, B.; Sideris, S.; Hoeflich, K. P.; Jaiswal, B. S.; Seshagiri, S.; Koeppen, H.; Belvin, M.; Friedman, L. S.; Malek, S., RAF inhibitors prime wild-type RAF to activate the MAPK pathway and enhance growth. Nature 2010, 464, 431. 35. Davis, M. I.; Hunt, J. P.; Herrgard, S.; Ciceri, P.; Wodicka, L. M.; Pallares, G.; Hocker, M.; Treiber, D. K.; Zarrinkar, P. P., Comprehensive analysis of kinase inhibitor selectivity. Nat. Biotechnol. 2011, 29, 1046.


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Figure Legends

Figure 1. PRM-based targeted proteomic approaches for interrogating the human kinome. (a) Experimental strategy for PRM-based targeted proteomic approaches. (b) A scatter plot displaying the correlation between the ratios obtained from forward and reverse SILAC labeling experiments in M14 cells with or without dabrafenib treatment. (c) A Venn diagram showing the overlap between quantified kinases from the forward and reverse SILAC labeling experiments in M14 cells with or without dabrafenib treatment.

Figure 2. Western blot analyses for validating the protein expression levels of kinases in M14 cells with or without dabrafenib/vemurafenib treatment. (a) Images from Western blot analyses of the expression levels of representative kinases in M14 cells with or without dabrafenib or vemurafenib treatment. The quantification results for the ratios of kinase proteins in dabrafenib- and vemurafenib-treated cells over control untreated cells are shown in (b) and (c), respectively. The data represent the mean ± S. D. of the quantification results (n = 3).

Figure 3. The alterations in expression levels of kinase proteins in M14 cells after treatment with two small-molecule BRAF inhibitors, dabrafenib (a) and vemurafenib (b). The cells were treated with 100 nM inhibitor for 24 h. Displayed are the ratios of expression of kinase proteins in BRAF inhibitor-treated over mock-treated M14 cells, where the X-axis was plotted in log10 scale. The data represent the average ratios obtained from two forward and two reverse SILAC labeling experiments for dabrafenib treatment and two forward and one reverse SILAC labeling



experiments for vemurafenib treatment. The red and blue bars designate those kinases that were up- and down-regulated, respectively, by at least 1.5-fold upon the inhibitor treatment (Table S1).

Figure 4. PRM- and MRM-based targeted proteomic approaches for interrogating the perturbations in protein expression and ATP binding affinity of kinases induced by kinase inhibitor treatment. (a) A scatter plot showing the absence of apparent correlation of alterations in kinase protein expression triggered by dabrafenib and vemurafenib treatments. (b-c) Scatter plots showing the lack of correlation between the ratios of kinases in dabrafenib (b) and vemurafenib (c)-treated over control DMSO-treated cells obtained from the PRM and MRM methods. (d) Venn diagrams depicting the overlaps of the number of kinases that were quantified by the PRM- and MRM-based kinome profiling methods for cellular samples obtained from treatments with dabrafenib and vemurafenib. (e) Western blot for examining the expression and phosphorylation level of MEK1 protein. (f) MRM traces for BRAF by vemurafenib treatment. (g) Quantitative comparison of ATP-binding affinity and activity of BRAF obtained from PRM and Western blot analyses, respectively. The data represent the mean ± S. D. of the quantification results (n = 3).

Figure 5. Vemurafenib binds MAP2K5. (a) MRM traces for tryptic peptides of MAP2K5 in M14 cells with or without vemurafenib treatment. (b) Western blot for monitoring the expression levels of MAP2K5 and ERK5, and the phosphorylation level of ERK5. (c) Quantitative comparison of ratios of protein expression and activity of MAP2K5 obtained from Western blot analyses, and ATP-binding affinity obtained from MRM analyses. The data represent the mean ± S. D. of the quantification results (n = 3). (d) The Venn diagram showing the overlap between the cell-based and in vitro kinome profiling by vemurafenib treatment. (e) A scatter plot displaying the


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correlation between the ratios (vemurafenib treat/control) obtained from in cellulo (in M14 cells) and in vitro (M14 cell lysate) experiments, respectively. (f) MRM traces of MAP2K5 and SRC obtained from in vitro kinome profiling assay.



Figure 1. a

Vemurafenib

Q1

Q2

Q3

Cell Lysis Tryptic Digestion and Mix at 1:1 ratio LC-PRM Analysis

BRAFi-Treated Cells Light Amino Acids

Precursor Selection

Fragmentation

Relative Abundance

Dabrafenib

Fragment Selection

b

100

100

80

80

60

60

40

40

20

20

0

0

Retention Time

DMSO-Treated Cells Heavy Amino Acids c 5

Reverse

Forward log2(Reverse)

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

Page 22 of 27

3 1 40 -1 R2 = 0.50

-3 -3

-1

1

3

5

log2(Forward)


241

21

Page 23 of 27

Figure 2.

a Dabrafenib Vemurafenib (nM) (nM) 0 100

Relative Ratio (Dabrafenib/DMSO)

b

Dabrafenib Vemurafenib (nM) (nM)

0 100

0 100

mTor

EGFR

AK1

ARAF

JAK3

BRAF

IGF2R

MAP2K1

STK26 CHK1

MAP3K3 MAP3K5

β-Actin

β-Actin

0 100

2 PRM Western blot

1.5 1 0.5 0

c

Relative Ratio (Vemurafenib/DMSO)

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


3.5

PRM Western blot

3 2.5 2 1.5 1 0.5 0



0.33

3.3

0.33

RDabrafenib/Control

3.3

0.33

RDabrafenib/Control

0.33

3.3

3.3

0.33

RDabrafenib/Control

RDabrafenib/Control

DSTYK DTYMK EIF2AK2 ENG ERCC2 ERCC3 FASTKD1 FASTKD2 FASTKD3 FKBP1A FPGT GAK GALK1 GALK2 GNE GOLGA5 GTF2H1 GTF2H3 GTF2H4 GUK1 HK1 HK2 HK3 HKDC1 HSPB8 HUS1 IKBKAP IKBKB IPPK IRS1 ITPK1 ITPKA ITPKB KCNH4 MAGI3 MPP1 NAGK NEK4 NEK6 NEK7 NIN NME6 NME7 NRBP1 NRP1 NRP2 NUP62 PBK PEAK1 PFKFB2 PFKFB4

Other

FES FGFR4 FLT4 FYN IGF1R IGF2R ITK JAK1 JAK3 KIT LYN MERTK PDGFRB PTK2 PTK7 ROR1 SYK TK1 TK2 TNK1 TNK2 YES1 ZAP70 ACVR1 ARAF BRAF ILK IRAK1 IRAK4 KSR1 LIMK1 LIMK2 RAF1 RIPK1 TGFBR1 ZAK ACTL8 ADK AKAP13 AKAP9 ATRIP BMP2K CARD11 CAV2 CCNH CLP1 CMPK1 CPNE3 CRIM1 CTTNBP2 DLG1

Other

TKL

TK

GSK3A GSK3B MAPK1 MAPK14 MAPK15 MAPK3 MAPK7 MAPK8 MAPK9 PRPK PRPS1 PRPS2 PRPSAP1 PRPSAP2 SRPK1 SRPK2 CIT MAP2K1 MAP2K2 MAP2K3 MAP2K6 MAP3K11 MAP3K3 MAP3K4 MAP3K5 MAP3K6 MAP4K1 MAP4K4 MAP4K5 OXSR1 PAK2 PAK4 SLK STK10 STK24 STK25 STK26 STK3 STK39 STK4 TAOK1 TAOK3 TNIK CAD CSK DDR1 EPHB2 EPHB4 EPHB6 ERBB3

Other

STE

CMGC

RIOK1 RIOK2 RIOK3 SMG1 TRPM7 CAMK2D CAMK2G CAMK4 CAMKK2 CAMKV CHEK1 CHEK2 DCLK1 MAPKAPK2 MAPKAPK3 MAPKAPK5 MARK2 MELK OBSCN PHKA1 PHKA2 STK17A STK33 TRIO VRK2 VRK1 CSNK2B CSNK2A2 CSNK2A1 CSNK1E CSNK1D CSNK1A1 CDC42BPA CDC42BPB CDC42BPG CDC7 CDK1 CDK16 CDK2 CDK3 CDK4 CDK5 CDK7 CDK8 CDK9 CLK1 CLK3 CRKL DCK DYRK1A DYRK1B

TK

Atypical CK1

CAMK

ADRBK2 AKT1 AKT2 AKT3 GRK6 LATS1 MASTL PKN1 PKN2 PRKAA1 PRKACA PRKACB PRKACG PRKAG1 PRKAG2 PRKCB PRKCD PRKCE PRKCH PRKD1 PRKD3 PRKDC PRKX ROCK1 ROCK2 RPS6KA1 RPS6KA3 RPS6KA4 RPS6KA5 RPS6KB1 RPS6KC1 SGK3 STK38L ADCK4 AK1 AK2 AK3 AK4 AK5 AK6 AK9 ATM BRD2 FASTK MTOR PDK1 PDK2 PDK3 PDK4 PDPK1

CMGC

Atypical

AGC

Figure 3. AAK1 PFKL PFKM PFKP PI4K2B PIK3C2A PIK3CA PIK3CB PIK3CD PIK3R2 PIK3R4 PIKFYVE PIP4K2A PIP4K2C PIP5K1A PIP5K3 PKMYT1 PNKP POLR2A POLR2B POLR2C POLR2D POLR2E POLR2G POLR2H POLR2L PPIP5K2 PPP4C RP2 SCYL1 SCYL2 SCYL3 SPHK1 SRC TBCK TBK1 TBRG4 TFG TGFB2 TJP2 TRIM27 TRIM28 TWF1 UCK1 UCK2 UCKL1 ULK1 ULK3 WNK1 0.33

3.3

RDabrafenib/Control

3.3

RDabrafenib/Control

0.33

3.3

RVemurafenib/Control

0.33

3.3


0.33

TKL 3.3


0.33

3.3



AURKB BUB1B CAV2 CCNH CMPK1 CPNE3 CTTNBP2 DGUOK DSTYK DTYMK EIF2AK2 EIF2AK4 ENG EXOSC10 FASTKD2 FASTKD3 FKBP1A FPGT GAK GALK1 GALK2 GNE GOLGA5 GTF2H1 GTF2H4 GUK1 HK1 HK2 HK3 HSPB8 HUS1 IKBKAP IPPK IRS1 ITPK1 ITPKA ITPKB ITPKC LGMN MAGI3 MNAT1 MPP1 MPP2 MYT1 NAGK NEK4 NEK6 NEK7 NIN NME6 NME7 NRP1 0.33

Other

ABL1 AXL BTK CAD CSK DDR1 EGFR EPHB2 EPHB4 EPHB6 ERBB2 FES FLT4 IGF1R IGF2R JAK3 LCK LYN MERTK PDGFRB PTK2 PTK7 SYK TK1 TK2 YES1 ZAP70 ACVR1 ARAF BRAF ILK IRAK1 IRAK4 KSR1 LIMK1 LIMK2 RAF1 RIPK1 RIPK3 RIPK4 TGFBR1 TGFBR2 ACTL8 ADK AGK AKAP9 ATRIP AURKA

Other

TK

CDK7 CDK9 CLK1 CLK3 CRKL DCK DYRK1B GSK3A MAPK1 MAPK14 MAPK15 MAPK3 MAPK7 PRPK PRPS1 PRPS2 PRPSAP1 PRPSAP2 SRPK1 SRPK2 CIT MAP2K1 MAP2K2 MAP2K3 MAP2K6 MAP2K7 MAP3K1 MAP3K11 MAP3K2 MAP3K3 MAP3K4 MAP3K5 MAP4K4 MAP4K5 MINK1 OXSR1 PAK2 PAK4 SLK STK10 STK24 STK26 STK39 STK4 TAOK2 TAOK3

Other

CMGC

FASTK MTOR PDPK1 RIOK1 RIOK3 SMG1 CAMK1D CAMK2D CAMK2G CAMKK2 CAMKV CHEK1 CHEK2 DCLK1 DCLK2 MAPKAPK2 MAPKAPK3 MAPKAPK5 MARK1 MARK2 MELK PASK PHKA1 PHKA2 PHKG2 SIK2 SIK3 STK17A TRIO CSNK1A1 CSNK1D CSNK1E CSNK2A1 CSNK2A2 CSNK2B VRK1 VRK2 CDC42BPA CDC42BPG CDC7 CDK1 CDK14 CDK16 CDK2 CDK3 CDK4 CDK5

STE

Atypical CK1

CAMK

ADRBK1 ADRBK2 AKT1 AKT2 AKT3 AMPK1 KAPCB LATS1 MAST3 MASTL PKN1 PKN2 PRKAA1 PRKACA PRKACB PRKACG PRKAG1 PRKAG2 PRKCD PRKCE PRKCH PRKCI PRKCZ PRKD1 PRKDC PRKX ROCK1 ROCK2 RPS6KA1 RPS6KA3 RPS6KC1 STK38 STK38L AK1 AK2 AK3 AK4 AK5 AK6 AK9 ATM BCR BRD2 EEF2K

CMGC

AGC

b

Atypical

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 24 of 27

3.3


AAK1 NRP2 NUP62 PBK PEAK1 PFKFB2 PFKFB3 PFKFB4 PFKL PFKM PFKP PI4K2B PI4KB PIK3CB PIK3R2 PIK3R4 PIKFYVE PIP4K2A PIP4K2C PIP5K1A PKMYT1 PLK1 PNKP POLR2A POLR2B POLR2C POLR2D POLR2E POLR2G POLR2H POLR2L PPIP5K1 PPIP5K2 PPP4C RP2 SCYL1 SCYL2 SPHK1 TBK1 TBRG4 TFG TGFB2 TJP2 TRIM28 TWF1 UCK2 UCKL1 ULK1 ULK3 WNK1 WNK4 0.33

3.3


Page 25 of 27

b

0.8

0.4 0 -0.4 -0.8 -1.6 -1.2 -0.8 -0.4

0

0.4

BRAF 0

ARAF

-0.4

0.4 0.8

-1.2 -0.8 -0.4 0

log10(Dabrafenib/DMSO)

c

Log10(MRM Ratio)

0.4 0.8 1.2 1.6

Log10(PRM Ratio)

d

0.5

Vemurafenib

Dabrafenib MRM

PRM

MRM

PRM

0 ARAF

147

150

141 151

181

107

BRAF

-0.5

-0.8

-0.4

0

0.4

0.8

Log10(PRM Ratio)

f M14

Vemurafenib (nM) 0 MEK1 p-MEK1 S222

β-Actin

100

g Relative Abundance

e

Vemurafenib DMSO

Vemurafenib DMSO

1

1

0.5

0.5

0

0 97

99

97

99

Retention Time (min)


Relative ATP-binding Affinity and Activity of BRAF

a

log10(Vemurafenib/DMSO)

Figure 4.

Log10(MRM Ratio)

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


1.2 0.8 0.4

0

PRM Western blot


Figure 5.

a Relative Abundance

b

Vemurafenib DMSO

Vemurafenib DMSO

M14 Vemurafenib (nM) 0

1

1

100

MAP2K5 0.5

0.5

0

0

ERK5 P-ERK5

79

81

79

β-Actin

81


c

In vitro

97

235

33

0.4

Expression Activity (pATP-binding Protein Activity ATP-Biding ERK5) Affinity Expression (p-ERK5) Affinity

f

DMSO

1

Relative Abundance

Relative Ratio

In cellulo

0.8

0

e

d

DMSO Vemurafenib

1.2

Log2(Vemurafenib/DMSO), In vitro

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 26 of 27

0 ARAF

-1

ZAK

-2 -3

MAP2K5

-4 -3 -2 -1

0

1

2

Log2(Vemurafenib/DMSO), In cellulo

Vemurafenib

MAP2K5

SRC

1

1

0.5

0.5

0

0

76

78

109 110 111



Page 27 of 27

LC-MRM TKL

TKTK

TKL

STE

STE

Targeted Proteomics

CMGC CMGC

CK1

CK1

AGC

PRM Library PRM library CAMK CAMK MRM library MRM Library Both PRM and MRM libraries PRM & MRM Library

AGC

Vemurafenib DMSO

Vemurafenib DMSO

1

1

0.5

0.5

0

0 79

81

79

81


2


Log2(Vemurafenib/DMSO), In vitro

For TOC Only

Relative Abundance

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


In vitro vs. In cellulo 1 0 ARAF -1

ZAK

-2

-3

MAP2K5

-4

-3

-2

-1

0

1

2

Log2(Vemurafenib/DMSO), In cellulo

Quantitative Interrogation of the Human Kinome Perturbed by Two

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