Dataset Information

Imatinib-Induced Changes in Protein Expression and ATP-Binding Affinities of Kinases in Chronic Myelocytic Leukemia Cells.

ABSTRACT: Kinases are crucial components in numerous cell signaling pathways. Aberrant expression and activation of protein kinases are known to be accompanied by many types of cancer, and more than 30 small-molecule kinase inhibitors have been approved by the Food and Drug Administration (FDA) for cancer chemotherapy. Biological and clinical applications of small-molecule kinase inhibitors require comprehensive characterizations about how these inhibitors modulate the protein expression and activities of kinases at the entire proteome scale. In this study, we developed a parallel-reaction monitoring (PRM)-based targeted proteomic method to monitor the alterations in protein expression of kinases in K-562 chronic myelocytic leukemia (CML) cells elicited by treatment with imatinib, an ABL kinase inhibitor approved by the FDA for CML treatment. By employing isotope-coded ATP affinity probes together with liquid chromatography-multiple-reaction monitoring (LC-MRM) analysis, we also examined the modulation of the ATP-binding affinities of kinases induced by imatinib treatment. The results revealed profound increases in protein expression levels of a large number of kinases in K-562 cells upon treatment with imatinib, which is accompanied by substantial decreases in ATP-binding capacities of many kinases. Apart from ABL kinases, we identified a number of other kinases whose ATP-binding affinities are markedly diminished upon imatinib treatment, including CHK1, a checkpoint kinase involved in DNA damage response signaling. Together, our targeted quantitative proteomic methods enabled, for the first time, dual assessments of small-molecule kinase inhibitor-induced changes in protein expression and ATP-binding affinities of kinases in live cells.

SUBMITTER: Miao W

PROVIDER: S-EPMC6484830 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Imatinib-Induced Changes in Protein Expression and ATP-Binding Affinities of Kinases in Chronic Myelocytic Leukemia Cells.

Miao Weili W Guo Lei L Wang Yinsheng Y

Analytical chemistry 20190220 5

Kinases are crucial components in numerous cell signaling pathways. Aberrant expression and activation of protein kinases are known to be accompanied by many types of cancer, and more than 30 small-molecule kinase inhibitors have been approved by the Food and Drug Administration (FDA) for cancer chemotherapy. Biological and clinical applications of small-molecule kinase inhibitors require comprehensive characterizations about how these inhibitors modulate the protein expression and activities of ...[more]

PMID: 30773012

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Project description:Inhibition of deregulated protein kinases by small molecule drugs has evolved into a major therapeutic strategy for the treatment of human malignancies. Imatinib mesylate has emerged as the leading compound to treat chronic myeloid leukemia (CML), through its inhibition of Bcr- Abl tyrosine kinases, and other cancers. However, resistance to imatinib develops frequently, particularly in late-stage disease and has necessitated the development of new BCR-ABL inhibitors. The synthesis of a new series of phenylaminopyrimidines, structurally related to imatinib showed large interest since the introduction of the nilotibin. To identify the cellular pathways affected by new synthesized compounds, we applied mass spectrometry together with stable isotope labeling by amino acids in cell culture (SILAC) for the comparative study of protein expression in K562 cells that were untreated or treated with imatinib and imatinib derivates. Further, the global proteome of the K562 cells treated with imatinib were quantitatively compared with the cells treated with the new compounds. This study enriched our knowledge about direct cellular targets of kinase selective drugs. Further the results offered important new knowledge for gaining insights into the structural effects of action of the new compounds. Samples were analyzed on a longer column (30cm) and a longer gradient (180min). Raw data files were processed with Mascot distiller 2.3. The mgf files were searched with Mascot daemon 2.3. The quantification was also done by Mascot Distiller. All data was stored in ms_lims. The manual validation of false peptide ratios was done with Rover (part of ms_lims). Fixed modifications: none. Variable modifications: acetylation of peptide N-terminus, pyroglutamate formation of N-terminal glutamine, methionine oxidation. Enzyme: trypsine with one missed cleavage allowed. Precursor mass tolerance: 10 ppm. Peptide fragment mass tolerance: 0.5 Da Quantitation method: SILAC arginine and lysine +6 Da. Overview of the 17 different analyses: B SK23 vs DMSO C Y22 vs DMSO D SK20 vs DMSO E Y18 vs DMSO I SK20 vs DMSO K Y18 vs DMSO O Y22 vs DMSO R Imatinib vs Water Z Imatinib vs Water J SK20 vs Imatinib M SK23 vs Imatinib N Y22 vs Imatinib P SK23 vs Imatinib Q Y18 vs Imatinib S Y22 vs Imatinib T SK20 vs Imatinib Y Y18 vs Imatinib

Project description:A computational docking strategy using multiple conformations of the target protein is discussed and evaluated. A series of low molecular weight, competitive, nonpeptide protein tyrosine phosphatase inhibitors are considered for which the x-ray crystallographic structures in complex with protein tyrosine phosphatase 1B (PTP1B) are known. To obtain a quantitative measure of the impact of conformational changes induced by the inhibitors, these were docked to the active site region of various structures of PTP1B using the docking program FlexX. Firstly, the inhibitors were docked to a PTP1B crystal structure cocrystallized with a hexapeptide. The estimated binding energies for various docking modes as well as the RMS differences between the docked compounds and the crystallographic structure were calculated. In this scenario the estimated binding energies were not predictive inasmuch as docking modes with low estimated binding energies corresponded to relatively large RMS differences when aligned with the corresponding crystal structure. Secondly, the inhibitors were docked to their parent protein structures in which they were cocrystallized. In this case, there was a good correlation between low predicted binding energy and a correct docking mode. Thirdly, to improve the predictability of the docking procedure in the general case, where only a single target protein structure is known, we evaluate an approach which takes possible protein side-chain conformational changes into account. Here, side chains exposed to the active site were considered in their allowed rotamer conformations and protein models containing all possible combinations of side-chain rotamers were generated. To evaluate which of these modeled active sites is the most likely binding site conformation for a certain inhibitor, the inhibitors were docked against all active site models. The receptor rotamer model corresponding to the lowest estimated binding energy is taken as the top candidate. Using this protocol, correct inhibitor binding modes could successfully be discriminated from proposed incorrect binding modes. Moreover, the ranking of the estimated ligand binding energies was in good agreement with experimentally observed binding affinities.

Dataset Information

Imatinib-Induced Changes in Protein Expression and ATP-Binding Affinities of Kinases in Chronic Myelocytic Leukemia Cells.

Publications

Imatinib-Induced Changes in Protein Expression and ATP-Binding Affinities of Kinases in Chronic Myelocytic Leukemia Cells.

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