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pH dependence of ligand-induced human epidermal growth factor receptor activation investigated by molecular dynamics simulations

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Abstract

The activation of human epidermal growth factor receptor (hEGFR) involves a large conformational change in its soluble extracellular domains (sECD, residues 1–620), from a tethered to an extended conformation upon binding of ligands, such as EGF. It has been reported that this dynamic process is pH-dependent, that is, hEGFR can be activated by EGF at high pH to form an extended dimer but remains as an inactive monomer at low pH. In this paper, we perform all-atom molecular dynamics (MD) simulations starting from the tethered conformation of sECD:EGF complex, at pH 5.0 and 8.5, respectively. Simulation results indicate that sECD:EGF shows different dynamic properties between the two pHs, and the complex may have a higher tendency of activation at pH 8.5. Twenty residues, including 13 histidines, in sECD:EGF have different protonation states between the two pHs (calculated by the H++ server). The charge distribution at pH 8.5 is more favorable for forming an extended conformation toward the active state of sECD than that at pH 5.0. Our study may shed light on the mechanism of pH dependence of hEGFR activation.

pH dependence of ligand-induced human epidermal growth factor receptor activation

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References

  1. Ferguson KM (2008) Structure-based view of epidermal growth factor receptor regulation. Annu Rev Biophys 37:353–373. doi:10.1146/annurev.biophys.37.032807.125829

    Article  CAS  Google Scholar 

  2. Yarden Y, Sliwkowski MX (2001) Untangling the ErbB signalling network. Nat Rev Mol Cell Biol 2(2):127–137. doi:10.1038/35052073

    Article  CAS  Google Scholar 

  3. Harris RC, Chung E, Coffey RJ (2003) EGF receptor ligands. Exp Cell Res 284(1):2–13. doi:10.1016/s0014-4827(02)00105-2

    Article  CAS  Google Scholar 

  4. Citri A, Yarden Y (2006) EGF-ERBB signalling: towards the systems level. Nat Rev Mol Cell Biol 7(7):505–516. doi:10.1038/nrm1962

    Article  CAS  Google Scholar 

  5. Riese DJ 2nd, Gallo RM, Settleman J (2007) Mutational activation of ErbB family receptor tyrosine kinases: insights into mechanisms of signal transduction and tumorigenesis. Bioessays 29(6):558–565. doi:10.1002/bies.20582

    Article  CAS  Google Scholar 

  6. Nicholson RI, Gee JM, Harper ME (2001) EGFR and cancer prognosis. Eur J Cancer 37(Suppl 4):S9–S15

    Article  CAS  Google Scholar 

  7. Yarden Y (2001) The EGFR family and its ligands in human cancer: signalling mechanisms and therapeutic opportunities. Eur J Cancer 37(Suppl 4):S3–S8

    Article  CAS  Google Scholar 

  8. Wujcik D (2006) EGFR as a target: rationale for therapy. Semin Oncol Nurs 22(1 Suppl 1):5–9. doi:10.1016/j.soncn.2006.01.010

    Article  Google Scholar 

  9. Grandal MV, Madshus IH (2008) Epidermal growth factor receptor and cancer: control of oncogenic signalling by endocytosis. J Cell Mol Med 12(5A):1527–1534. doi:10.1111/j.1582-4934.2008.00298.x

    Article  CAS  Google Scholar 

  10. Ullrich A, Coussens L, Hayflick JS, Dull TJ, Gray A, Tam AW, Lee J, Yarden Y, Libermann TA, Schlessinger J et al (1984) Human epidermal growth factor receptor cDNA sequence and aberrant expression of the amplified gene in A431 epidermoid carcinoma cells. Nature 309(5967):418–425. doi:10.1038/309418a0

    Article  CAS  Google Scholar 

  11. Bajaj M, Waterfield MD, Schlessinger J, Taylor WR, Blundell T (1987) On the tertiary structure of the extracellular domains of the epidermal growth factor and insulin receptors. Biochim Biophys Acta 916(2):220–226. doi:10.1016/0167-4838(87)90112-9

    Article  CAS  Google Scholar 

  12. Ward CW, Hoyne PA, Flegg RH (1995) Insulin and epidermal growth factor receptors contain the cysteine repeat motif found in the tumor necrosis factor receptor. Proteins 22(2):141–153. doi:10.1002/prot.340220207

    Article  CAS  Google Scholar 

  13. Garrett TP, McKern NM, Lou M, Elleman TC, Adams TE, Lovrecz GO, Zhu HJ, Walker F, Frenkel MJ, Hoyne PA, Jorissen RN, Nice EC, Burgess AW, Ward CW (2002) Crystal structure of a truncated epidermal growth factor receptor extracellular domain bound to transforming growth factor alpha. Cell 110(6):763–773

    Article  CAS  Google Scholar 

  14. Ogiso H, Ishitani R, Nureki O, Fukai S, Yamanaka M, Kim JH, Saito K, Sakamoto A, Inoue M, Shirouzu M, Yokoyama S (2002) Crystal structure of the complex of human epidermal growth factor and receptor extracellular domains. Cell 110(6):775–787

    Article  CAS  Google Scholar 

  15. Lu C, Mi LZ, Grey MJ, Zhu J, Graef E, Yokoyama S, Springer TA (2010) Structural evidence for loose linkage between ligand binding and kinase activation in the epidermal growth factor receptor. Mol Cell Biol 30(22):5432–5443. doi:10.1128/MCB.00742-10

    Article  CAS  Google Scholar 

  16. Ferguson KM, Berger MB, Mendrola JM, Cho HS, Leahy DJ, Lemmon MA (2003) EGF activates its receptor by removing interactions that autoinhibit ectodomain dimerization. Mol Cell 11(2):507–517. doi:10.1016/S1097-2765(03)00047-9

    Article  CAS  Google Scholar 

  17. Karplus M, McCammon JA (2002) Molecular dynamics simulations of biomolecules. Nat Struct Biol 9:646–652

    Article  CAS  Google Scholar 

  18. Adcock SA, McCammon JA (2006) Molecular dynamics: survey of methods for simulating the activity of proteins. Chem Rev 106(5):1589–1615

    Article  CAS  Google Scholar 

  19. Dror RO, Dirks RM, Grossman JP, Xu H, Shaw DE (2012) Biomolecular simulation: a computational microscope for molecular biology. Annu Rev Biophys 41:429–452. doi:10.1146/annurev-biophys-042910-155245

    Article  CAS  Google Scholar 

  20. Kastner J, Loeffler HH, Roberts SK, Martin-Fernandez ML, Winn MD (2009) Ectodomain orientation, conformational plasticity and oligomerization of ErbB1 receptors investigated by molecular dynamics. J Struct Biol 167(2):117–128. doi:10.1016/j.jsb.2009.04.007

    Article  Google Scholar 

  21. Tynan CJ, Roberts SK, Rolfe DJ, Clarke DT, Loeffler HH, Kastner J, Winn MD, Parker PJ, Martin-Fernandez ML (2011) Human Epidermal Growth Factor Receptor (EGFR) aligned on the plasma membrane adopts key features of drosophila EGFR asymmetry. Mol Cell Biol 31(11):2241–2252. doi:10.1128/MCB.01431-10

    Article  CAS  Google Scholar 

  22. Zhang Z, Wriggers W (2011) Polymorphism of the epidermal growth factor receptor extracellular ligand binding domain: the dimer interface depends on domain stabilization. Biochemistry 50(12):2144–2156. doi:10.1021/bi101843s

    Article  CAS  Google Scholar 

  23. Arkhipov A, Shan Y, Das R, Endres NF, Eastwood MP, Wemmer DE, Kuriyan J, Shaw DE (2013) Architecture and membrane interactions of the EGF receptor. Cell 152(3):557–569. doi:10.1016/j.cell.2012.12.030

    Article  CAS  Google Scholar 

  24. Arkhipov A, Shan Y, Kim ET, Dror RO, Shaw DE (2013) Her2 activation mechanism reflects evolutionary preservation of asymmetric ectodomain dimers in the human EGFR family. Elife 2:e00708. doi:10.7554/eLife.00708

    Article  Google Scholar 

  25. Loeffler HH, Winn MD (2013) Ligand binding and dynamics of the monomeric epidermal growth factor receptor ectodomain. Proteins 81(11):1931–1943. doi:10.1002/prot.24339

    Article  CAS  Google Scholar 

  26. Perilla JR, Leahy DJ, Woolf TB (2013) Molecular dynamics simulations of transitions for ECD epidermal growth factor receptors show key differences between human and drosophila forms of the receptors. Proteins 81(7):1113–1126. doi:10.1002/prot.24257

    Article  CAS  Google Scholar 

  27. Poger D, Mark AE (2014) Activation of the epidermal growth factor receptor: a series of twists and turns. Biochemistry 53(16):2710–2721. doi:10.1021/bi401632z

    Article  CAS  Google Scholar 

  28. Webb B, Sali A (2014) Protein structure modeling with MODELLER. Methods Mol Biol 1137:1–15. doi:10.1007/978-1-4939-0366-5_1

    Article  CAS  Google Scholar 

  29. Anandakrishnan R, Aguilar B, Onufriev AV (2012) H++ 3.0: automating pK prediction and the preparation of biomolecular structures for atomistic molecular modeling and simulations. Nucleic Acids Res 40(Web Server issue):W537–W541. doi:10.1093/nar/gks375

    Article  CAS  Google Scholar 

  30. Bashford D, Karplus M (1990) pKa’s of ionizable groups in proteins: atomic detail from a continuum electrostatic model. Biochemistry 29(44):10219–10225. doi:10.1021/bi00496a010

    Article  CAS  Google Scholar 

  31. Li H, Robertson AD, Jensen JH (2005) Very fast empirical prediction and rationalization of protein pKa values. Proteins 61(4):704–721. doi:10.1002/prot.20660

    Article  CAS  Google Scholar 

  32. Dolinsky TJ, Nielsen JE, McCammon JA, Baker NA (2004) PDB2PQR: an automated pipeline for the setup of poisson-boltzmann electrostatics calculations. Nucleic Acids Res 32:W665–W667. doi:10.1093/nar/gkh381

    Article  CAS  Google Scholar 

  33. Hess B, Kutzner C, van der Spoel D, Lindahl E (2008) GROMACS 4: algorithms for highly efficient, load-balanced, and scalable molecular simulation. J Chem Theory Comput 4(3):435–447. doi:10.1021/Ct700301q

    Article  CAS  Google Scholar 

  34. Yong D, Chun W, Chowdhury S, Lee MC, Guoming X, Wei Z, Rong Y, Cieplak P, Ray L, Taisung L, Caldwell J, Junmei W, Kollmann P (2003) A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calculations. J Comput Chem 24(16):1999–2012. doi:10.1002/jcc.10349

    Article  Google Scholar 

  35. Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML (1983) Comparison of simple potential functions for simulating liquid water. J Chem Phys 79(2):926–935. doi:10.1063/1.445869

    Article  CAS  Google Scholar 

  36. Hockney RW, Goel SP, Eastwood JW (1974) Quiet high-resolution computer models of a plasma. J Comput Phys 14(2):148–158. doi:10.1016/0021-9991(74)90010-2

    Article  Google Scholar 

  37. Bussi G, Donadio D, Parrinello M (2007) Canonical sampling through velocity rescaling. J Chem Phys 126(1):014101. doi:10.1063/1.2408420

    Article  Google Scholar 

  38. Berendsen HJC, Postma JPM, Vangunsteren WF, Dinola A, Haak JR (1984) Molecular-dynamics with coupling to an external bath. J Chem Phys 81(8):3684–3690. doi:10.1063/1.448118

    Article  CAS  Google Scholar 

  39. Hess B (2008) P-LINCS: a parallel linear constraint solver for molecular simulation. J Chem Theory Comput 4(1):116–122. doi:10.1021/Ct700200b

    Article  CAS  Google Scholar 

  40. Essmann U, Perera L, Berkowitz ML, Darden T, Lee H, Pedersen LG (1995) A smooth particle mesh Ewald method. J Chem Phys 103(19):8577–8593. doi:10.1063/1.470117

    Article  CAS  Google Scholar 

  41. Amadei A, Linnsen ABM, Berendsen HJC (1993) Essential dynamics of proteins. Proteins 17:412–425

    Article  CAS  Google Scholar 

  42. Kollman PA, Massova I, Reyes C, Kuhn B, Huo SH, Chong L, Lee M, Lee T, Duan Y, Wang W, Donini O, Cieplak P, Srinivasan J, Case DA, Cheatham TE (2000) Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models. Acc Chem Res 33(12):889–897. doi:10.1021/ar000033j

    Article  CAS  Google Scholar 

  43. Onufriev A, Bashford D, Case DA (2004) Exploring protein native states and large-scale conformational changes with a modified generalized born model. Proteins 55(2):383–394. doi:10.1002/prot.20033

    Article  CAS  Google Scholar 

  44. Andricioaei I, Karplus M (2001) On the calculation of entropy from covariance matrices of the atomic fluctuations. J Chem Phys 115(14):6289–6292. doi:10.1063/1.1401821

    Article  CAS  Google Scholar 

  45. Balsera MA, Wriggers W, Oono Y, Schulten K (1996) Principal component analysis and long time protein dynamics. J Phys Chem 100(7):2567–2572. doi:10.1021/jp9536920

    Article  CAS  Google Scholar 

  46. Dolinsky TJ, Czodrowski P, Li H, Nielsen JE, Jensen JH, Klebe G, Baker NA (2007) PDB2PQR: expanding and upgrading automated preparation of biomolecular structures for molecular simulations. Nucleic Acids Res 35(Web Server issue):W522–W525. doi:10.1093/nar/gkm276

    Article  Google Scholar 

  47. Baker NA, Sept D, Joseph S, Holst MJ, McCammon JA (2001) Electrostatics of nanosystems: application to microtubules and the ribosome. Proc Natl Acad Sci U S A 98(18):10037–10041. doi:10.1073/pnas.181342398

    Article  CAS  Google Scholar 

  48. Humphrey W, Dalke A, Schulten K (1996) VMD: visual molecular dynamics. J Mol Graph 14(1):33–38. doi:10.1016/0263-7855(96)00018-5

  49. Alexov E, Mehler EL, Baker N, Baptista AM, Huang Y, Milletti F, Nielsen JE, Farrell D, Carstensen T, Olsson MHM, Shen JK, Warwicker J, Williams S, Word JM (2011) Progress in the prediction of pK(a) values in proteins. Proteins 79(12):3260–3275. doi:10.1002/prot.23189

    Article  CAS  Google Scholar 

  50. Swails JM, York DM, Roitberg AE (2014) Constant pH replica exchange molecular dynamics in explicit solvent using discrete protonation states: implementation, testing, and validation. J Chem Theory Comput 10(3):1341–1352. doi:10.1021/ct401042b

    Article  CAS  Google Scholar 

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Acknowledgments

This work is supported by the National Key Basic Research Program of China (grant 2013CB910203), the National Natural Science Foundation of China (grants 31270760, 21573205), the Anhui Natural Science Foundation (grant 1208085MC38), and the supercomputing center of USTC.

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    Authors and Affiliations

    1. Hefei National Laboratory for Physical Science at Microscale and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui, 230026, People’s Republic of China

      Jun Dong, Yonghui Zhang & Zhiyong Zhang

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    1. Jun Dong
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    2. Yonghui Zhang
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    Correspondence to Zhiyong Zhang.

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    Jun Dong and Yonghui Zhang contributed equally to this work.

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    Dong, J., Zhang, Y. & Zhang, Z. pH dependence of ligand-induced human epidermal growth factor receptor activation investigated by molecular dynamics simulations. J Mol Model 22, 131 (2016). https://doi.org/10.1007/s00894-016-3000-6

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