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3D-QSAR modeling and molecular docking study on Mer kinase inhibitors of pyridine-substituted pyrimidines

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Abstract

Mer kinase is a novel therapeutic target for many cancers, and overexpression of Mer receptor tyrosine kinase has been observed in several kinds of tumors. To deeply understand the structure–activity correlation of a series of pyridine/pyrimidine analogs as potent Mer inhibitors, a combined molecular docking and three-dimensional quantitative structure–activity relationship modeling was carried out. A comparative molecular similarity indices analysis model was developed based on the maximum common substructure alignment. The optimum model exhibited statistically significant results: the cross-validated correlation coefficient \(q^{2}\) was 0.599, and non-cross-validated \(r^{2}\) value was 0.984. Furthermore, the results of internal validation such as bootstrapping, Y-randomization as well as external validation (the external predictive correlation coefficient \(r_\mathrm{ext}^2 =0.728)\) confirmed the rationality and good predictive ability of the model. Using the crystal structure of Mer kinase, the selected pyridine/pyrimidine compounds were docked into the enzyme active site. Some key amino acid residues were determined, and hydrogen bonding and hydrophobic interactions between Mer kinase and inhibitors were identified. The satisfactory results from this study may aid in the research and development of novel potent Mer kinase inhibitors.

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References

  1. Chen J, Carey K, Godowski PJ (1997) Identification of Gas6 as a ligand for Mer, a neural cell adhesion molecule related receptor tyrosine kinase implicated in cellular transformation. Oncogene 14:2033–2039. doi:10.1038/sj.onc.1201039

    Article  CAS  PubMed  Google Scholar 

  2. Fisher PW, Brigham-Burke M, Wu SJ, Luo J, Carton J, Staquet K, Gao W, Jackson S, Bethea D, Chen C (2005) A novel site contributing to growth-arrest-specific gene 6 binding to its receptors as revealed by a human monoclonal antibody. Biochem J 387:727–735. doi:10.1042/BJ20040859

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  3. Nagata K, Ohashi K, Nakano T, Arita H, Zong C, Hanafusa H, Mizuno K (1996) Identification of the product of growth arrest-specific gene 6 as a common ligand for Axl, Sky, and Mer receptor tyrosine kinases. J Biol Chem 271:30022–30027. doi:10.1074/jbc.271.47.30022

    Article  CAS  PubMed  Google Scholar 

  4. Caberoy NB, Zhou Y, Li W (2010) Tubby and tubby-like protein 1 are new Mer TK ligands for phagocytosis. Embo J 29:3898–3910. doi:10.1038/emboj.2010.265

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  5. Caberoy NB, Alvarado G, Bigcas JL, Li W (2012) Galectin-3 is a new Mer TK-specific eat-me signal. J Cell Physiol 227:401–407. doi:10.1002/jcp.22955

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  6. Linger RMA, Keating AK, Earp HS, Graham DK (2008) TAM receptor tyrosine kinases: biologic functions, signaling, and potential therapeutic targeting in human cancer. Adv Cancer Res 100:35–83. doi:10.1016/S0065-230X(08)00002-X

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  7. Angelillo-Scherrer A, Burnier L, Lambrechts D, Fish RJ, Tjwa M (2008) Role of Gas6 in erythropoiesis and anemia in mice. J Clin Invest 118:583–596. doi:10.1172/JCI30375

    CAS  PubMed Central  PubMed  Google Scholar 

  8. Tang H, Chen S, Wang H, Wu H, Lu Q, Han D (2009) TAM receptors and the regulation of erythropoiesis in mice. Haematologica 94:326–334. doi:10.3324/haematol.13635

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  9. Behrens EM, Gadue P, Gong SY, Garrett S, Stein PL, Cohen PL (2003) The mer receptor tyrosine kinase: expression and function suggest a role in innate immunity. Eur J Immunol 33:2160–2167. doi:10.1002/eji.200324076

    Article  CAS  PubMed  Google Scholar 

  10. Caraux A, Lu Q, Fernandez N, Riou S, Di Santo JP, Raulet DH, Lemke G, Roth C (2006) Natural killer cell differentiation driven by Tyro3 receptor tyrosine kinases. Nat Immunol 7:747–754. doi:10.1038/ni1353

    Article  CAS  PubMed  Google Scholar 

  11. Rochlitz C, Lohri A, Bacchi M, Schmidt M, Nagel S, Fopp M, Fey MF, Herrmann R, Neubauer A (1999) Axl expression is associated with adverse prognosis and with expression of Bcl-2 and CD34 in de novo acute myeloid leukemia (AML): results from a multicenter trial of the Swiss Group for Clinical Cancer Research (SAKK). Leukemia 13:1352–1358. doi:10.1097/00129492-200305000-00022

    Article  CAS  PubMed  Google Scholar 

  12. Gjerdrum C, Tiron C, Hoiby T, Stefansson I, Haugen H, Sandal T, Collett K, Li S, McCormack E, Gjertsen BT, Micklem DR, Akslen LA, Glackin C, Lorens JB (2010) Axl is an essential epithelial-to-mesenchymal transitioninduced regulator of breast cancer metastasis and patient survival. Proc Natl Acad Sci USA 107:1124–1129. doi:10.1073/pnas.0909333107

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  13. Wang SB, Yu Z, Cui LH, Si HZ (2014) The relationship of erbB family genes and chemosensitivity of Pemetrexed treated non-squamous NSCLC patients. Cancer Cell Res 1:1–8

    Google Scholar 

  14. Koorstra JB, Karikari CA, Feldmann G, Bisht S, Rojas PL, Offerhaus GJ, Alvarez H, Maitra A (2009) The Axl receptor tyrosine kinase confers an adverse prognostic influence in pancreatic cancer and represents a new therapeutic target. Cancer Biol Ther 8:618–626. doi:10.4161/cbt.8.7.7923

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  15. Lu XQ, Xiao WJ, Li X, Shen FZ, Sun TL (2014) Dose-effect relationship of celecoxib, a selective cyclooxygenase-2 inhibitor prevents lymphangiogenesis in a lewis lung carcinoma. Cancer Cell Res 1:9–18

    Google Scholar 

  16. Hafizi S, Dahlback B (2006) Gas 6 and protein S. Vitamin K-dependent ligands for the Axl receptor tyrosine kinase subfamily. FEBS J 273:5231–5244. doi:10.1111/j.1742-4658.2006.05529.x

    Article  CAS  PubMed  Google Scholar 

  17. Manfioletti G, Brancolini C, Avanzi G, Schneider C (1993) The protein encoded by a growth arrest-specific gene (gas6) is a new member of the vitamin K-dependent proteins related to protein S, a negative coregulator in the blood coagulation cascade. Mol Cell Biol 13:4976–4985. doi:10.1128/MCB.13.8.4976

    CAS  PubMed Central  PubMed  Google Scholar 

  18. Li Y, Ye X, Tan C, Hongo JA, Zha J, Liu J, Kallop D, Ludlam MJ, Pei L (2009) Axl as a potential therapeutic target in cancer: role of Axl in tumor growth, metastasis and angiogenesis. Oncogene 28:3442–3455. doi:10.1038/onc.2009.212

    Article  CAS  PubMed  Google Scholar 

  19. Ye X, Li Y, Stawicki S, Couto S, Eastham-Anderson J, Kallop D, Weimer R, Wu Y, Pei L (2010) An anti-Axl monoclonal antibody attenuates xenograft tumor growth and enhances the effect of multiple anticancer therapies. Oncogene 29:5254–5264. doi:10.1038/onc.2010.268

    Article  CAS  PubMed  Google Scholar 

  20. Linger RM, Cohen RA, Cummings CT, Sather S, Migdall-Wilson J, Middleton DHG, Lu X, Baròn AE, Franklin WA, Merrick DT (2013) Mer or Axl receptor tyrosine kinase inhibition promotes apoptosis, blocks growth and enhances chemosensitivity of human non-small cell lung cancer. Oncogene 12:3420–3431. doi:10.1038/onc.2012.355

    Article  Google Scholar 

  21. Wimmel A, Glitz D, Kraus A, Roeder J, Schuermann M (2001) Axl receptor tyrosine kinase expression in human lung cancer cell lines correlates with cellular adhesion. Eur J Cancer 37:2264–2274. doi:10.1016/S0959-8049(01)00271-4

    Article  CAS  PubMed  Google Scholar 

  22. Linger RM, Middleton DHG, Migdall J (2010) Mer and Axl receptor tyrosine kinases are novel therapeutic targets in NSCLC. In: AACR-IASLC joint conference on molecular origins of lung cancer—prospects for personalized prevention and therapy, Coronado

  23. Rikova K, Guo A, Zeng Q, Possemato A, Yu J, Haack H, Nardone J, Lee K, Reeves C, Li Y, Hu Y, Tan Z, Stokes M, Sullivan L, Mitchell J, Wetzel R, Macneill J, Ren JM, Yuan J, Bakalarski CE, Villen J, Kornhauser JM, Smith B, Li D, Zhou X, Gygi SP, Gu TL, Polakiewicz RD, Rush J, Comb MJ (2007) Global survey of phosphotyrosine signaling identifies oncogenic kinases in lung cancer. Cell 131:1190–1203. doi:10.1016/j.cell.2007.11.025

    Article  CAS  PubMed  Google Scholar 

  24. Tai KY, Shieh YS, Lee CS, Shiah SG, Wu CW (2008) Axl promotes cell invasion by inducing MMP-9 activity through activation of NF-kappaB and Brg-1. Oncogene 27:4044–4055. doi:10.1038/onc.2008.57

    Article  CAS  PubMed  Google Scholar 

  25. Linger RM, Keating AK, Earp HS, Graham DK (2010) Taking aim at Mer and Axl receptor tyrosine kinases as novel therapeutic targets in solid tumors. Expert Opin Ther Targets 14:1073–1090. doi:10.1517/14728222.2010.515980

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  26. Mahadevan D, Cooke L, Riley C, Swart R, Simons B, Della Croce K, Wisner L, Iorio M, Shakalya K, Garewal H, Nagle R, Bearss D (2007) A novel tyrosine kinase switch is a mechanism of imatinib resistance in gastrointestinal stromal tumors. Oncogene 26:3909–3919. doi:10.1038/sj.onc.1210173

  27. Quintas-Cardama A, Kantarjian H, Cortes J (2009) Imatinib and beyond-exploring the full potential of targeted therapy for CML. Nat Rev Clin Oncol 6:535–543. doi:10.1038/nrclinonc.2009

    Article  CAS  PubMed  Google Scholar 

  28. Liu L, Greger J, Shi H, Liu Y, Greshock J, Annan R, Halsey W, Sathe GM, Martin AM, Gilmer TM (2009) Novel mechanism of lapatinib resistance in HER2-positive breast tumor cells: activation of AXL. Cancer Res 69:6871–6878. doi:10.1158/0008-5472

    Article  CAS  PubMed  Google Scholar 

  29. Schroeder GM, An Y, Cai ZW, Chen XT, Clark C, Cornelius LA, Dai J, Gullo-Brown J, Gupta A, Henley B, Hunt JT, Jeyaseelan R, Kamath A, Kim K, Lippy J, Lombardo LJ, Manne V, Oppenheimer S, Sack JS, Schmidt RJ, Shen G, Stefanski K, Tokarski JS, Trainor GL, Wautlet BS, Wei D, Williams DK, Zhang Y, Zhang Y, Fargnoli J, Borzilleri RM (2009) Discovery of N-(4-(2-amino-3-chloropyridin-4-yloxy)-3-fluorophenyl)-4-ethoxy-1-(4-fluorophenyl)-2-oxo- 1,2-dihydropyridine-3-carboxamide (BMS-777607), a selective and orally efficacious inhibitor of the Met kinase superfamily. J Med Chem 52:1251–1254. doi:10.1021/jm801586s

    Article  CAS  PubMed  Google Scholar 

  30. Holland SJ, Pan A, Franci C, Hu Y, Chang B, Li W, Duan M, Torneros A, Yu J, Heckrodt TJ, Zhang J, Ding P, Apatira A, Chua J, Brandt R, Pine P, Goff D, Singh R, Payan DG, Hitoshi Y (2010) R428, a selective small molecule inhibitor of Axl kinase, blocks tumor spread and prolongs survival in models of metastatic breast cancer. Cancer Res 70:1544–1554. doi:10.1158/0008-5472

    Article  CAS  PubMed  Google Scholar 

  31. Brandao L, Molk D, Sather S, Graham DK (2010) Inhibition of Mer as a novel therapeutic strategy in acute lymphoblastic leukemia. In: Keystone symposia: new paradigms in cancer therapeutics, Victoria

  32. Liu J, Zhang W, Stashko MA, Deryckere D, Cummings CT, Hunter D, Yang C, Jayakody CN, Cheng N, Simpson C, Norris-Drouin J, Sather S, Kireev D, Janzen WP, Earp HS, Graham DK, Frye SV, Wang X (2013) UNC1062, a new and potent Mer inhibitor. Eur J Med Chem 65:83–93. doi:10.1016/j.ejmech.2013.03.035

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  33. Ling L, Templeton D, Kung HJ (1996) Identification of the major autophosphorylation sites of Nyk/Mer, an NCAM-related receptor tyrosine kinase. J Biol Chem 271:18355–18362. doi:10.1074/jbc.271.31.18355

    Article  CAS  PubMed  Google Scholar 

  34. Zheng MY, Liu X, Xu Y, Li HL, Luo C, Jiang HL (2013) Computational methods for drug design and discovery: focus on China. Trends Pharmacol Sci 34:549–559. doi:10.1016/j.tips.2013.08.004

    Article  CAS  PubMed  Google Scholar 

  35. Si HZ, Li XC, Fu AP, Yuan SP, Hao M, Zhang KJ, Duan YB, Hu ZD (2013) An accurate model for predicting retention time of coffee flavor in cigarette. Adv Mater Res 798–799:1091–1094. doi:10.4028/www.scientific.net/AMR.798-799.1091

    Article  Google Scholar 

  36. Li XC, Si HZ, Gao H, Zhai HL, Duan YB (2013) Quantitative structure activity relationship of new 7-oxycoumarin derivatives as potent and selective monoamine oxidase A inhibitors. Adv Mater Res 798–799:1109–1112. doi:10.4028/www.scientific.net/AMR.798-799.1109

    Google Scholar 

  37. Dong YM, Liu CJ, Si HZ (2011) Quantitative structure–activity relationship study for 2,3-ben-zodiazepin-4(thi)one- and 1,2-phthalazine-related negative allosteric modulators of AMPA receptor by heuristic and support vector machine method. J Comput Sci Eng 1:54–64

    Google Scholar 

  38. Zhang WH, Zhang DH, Stashko MA, DeRyckere D, Hunter D, Kireev D, Miley MJ, Cummings C, Lee M, Norris-Drouin J, Stewart WM (2013) Pseudo-cyclization through Intramolecular hydrogen bond enables discovery of pyridine substituted pyrimidines as new Mer kinase inhibitors. J Med Chem 56:9683–9692. doi:10.1021/jm401387j

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  39. Cambridge Soft Corp. (2014) Cambridge, USA. http://www.Cambridgesoft.com

  40. Tripos Inc. (2006) Docking suite manual for Tripos 7.3. Tripos Inc., St. Louis

  41. Clark M, Cramer RDI, Opdenbosch NV (1989) Validation of the general purpose tripos 5.2 force field. J Comput Chem 10:982–1012. doi:10.1002/jcc.540100804

    Article  CAS  Google Scholar 

  42. Gasteiger J, Marsili M (1980) Iterative partial equalization of orbital electronegativity—a rapid access to atomic charges. Tetrahedron 36:3219–3228. doi:10.1016/0040-4020(80)80168-2

    Article  CAS  Google Scholar 

  43. Protein Database Bank (PDB). http://www.pdb.org/pdb/home/home.do

  44. Jain AN (2007) Surflex-Dock 2.1: robust performance from ligand energetic modeling, ring flexibility, and knowledge-based search. J Comput-Aided Mol Des 21:281–306. doi:10.1007/s10822-007-9114-2

    Article  CAS  PubMed  Google Scholar 

  45. Jain AN (2003) Surflex: fully automatic flexible molecular docking using a molecular similarity-based search engine. J Med Chem 46:499–511. doi:10.1021/jm020406h

    Article  CAS  PubMed  Google Scholar 

  46. Li XL, Li Y, Wang XX, Wang XZ, Liu HL, Qian XP, Zhu YL, Yu HX (2012) Molecular docking, molecular dynamics simulation, and structure-based 3D-QSAR studies on estrogenic activity of hydroxylated polychlorinated biphenyls. Sci Total Environ 441:230–238. doi:10.1016/j.scitotenv.2012.08.072

    Article  CAS  PubMed  Google Scholar 

  47. Li XL, Li Y, Wang XX, Wang XZ, Liu HL, Zhu YL, Yu HX (2012) Combined 3D-QSAR, molecular docking and molecular dynamics study on thyroid hormone activity of hydroxylated polybrominated diphenyl ethers to thyroidreceptors \(\beta \). Toxicol Appl Pharmacol 265:300–307. doi: 10.1016/j.taap.2012.08.030

    Article  CAS  PubMed  Google Scholar 

  48. Yang WH, Mu YS, Giesy JP, Zhang AQ, Yu HX (2009) Anti-androgen activity of polybrominated diphenyl ethers determined by comparative molecular similarity indices and molecular docking. Chemosphere 75:1159–1164. doi:10.1016/j.chemosphere.2009.02.047

    Article  CAS  PubMed  Google Scholar 

  49. Du J, Qin J, Liu HX, Yao XJ (2008) 3D-QSAR and molecular docking studies of selective agonists for the thyroid hormone receptor beta. J Mol Graph 27:95–104. doi:10.1016/j.jmgm.2008.03.003

    Article  CAS  Google Scholar 

  50. Yang W, Shen S, Mu L, Yu H (2011) Structure–activity relationship study on the binding of PBDEs with thyroxine transport proteins. Environ Toxicol Chem 30:2431–2439. doi:10.1002/etc.645

    Article  CAS  PubMed  Google Scholar 

  51. Frank I, Feikema J, Constantine N, Kowalski B (1984) Prediction of product quality from spectral data using the partial least-squares method. J Chem Inf Comput Sci 24:20–24. doi:10.1021/ci00041a602

    Article  Google Scholar 

  52. Rännar S, Lindgren F, Geladi P, Wold S (1994) A PLS kernel algorithm for data sets with many variables and fewer objects. Part 1: theory and algorithm. J Chemom 8:111–125. doi:10.1002/cem.1180080204

    Article  Google Scholar 

  53. Cramer RD, Bunce JD, Patterson DE, Frank IE (1988) Crossvalidation, bootstrapping, and partial least squares compared with multiple regression in conventional QSAR studies. Quant Struct–Act Relat 7:18–25. doi:10.1002/qsar.19880070105

    Article  Google Scholar 

  54. Baumann K (2003) Cross-validation as the objective function for variable-selection techniques. Trends Anal Chem 22:395–406. doi:10.1016/S0165-9936(03)00607-1

    Article  CAS  Google Scholar 

  55. Roy PP, Paul S, Mitra I, Roy K (2009) On two novel parameters for validation of predictive QSAR. Molecules 14:1660–1701. doi:10.3390/molecules14051660

    Article  CAS  PubMed  Google Scholar 

  56. Mouchlis VD, Melagraki G, Mavromoustakos T, Kollias G, Afantitis A (2012) Molecular modeling on pyrimidine-urea inhibitors of TNF-alpha production: an integrated approach using a combination of molecular docking, classification techniques, and 3D-QSAR CoMSIA. J Chem Inf Model 52:711–723. doi:10.1021/ci200579f

    Article  CAS  PubMed  Google Scholar 

  57. Zhang WH, McIver AL, Stashko MA, DeRyckere D, Branchford BR, Hunter D, Kireev D, Miley MJ, Norris-Drouin J, Stewart WM, Lee MJ, Sather S, Zhou YQ, Di Paola JA, Machius M, Janzen WP, Shelton Earp H, Graham DK, Frye SV, Wang XD (2013) Discovery of Mer specific tyrosine kinase inhibitors for the treatment and prevention of thrombosis. J Med Chem 56:9693–9700. doi:10.1021/jm4013888

    Article  CAS  PubMed Central  PubMed  Google Scholar 

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Acknowledgments

This work was supported by the Science and Technology Development Project of Shandong Province: No. 2012YD18038 and No. 2012YD18042.

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Yu, Z., Li, X., Ge, C. et al. 3D-QSAR modeling and molecular docking study on Mer kinase inhibitors of pyridine-substituted pyrimidines. Mol Divers 19, 135–147 (2015). https://doi.org/10.1007/s11030-014-9556-0

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