Skip to main content

Unfolding mechanism of PHD2 as a vital protein: all-atom simulation approach


Prolyl hydroxylase domain 2 containing protein (PHD2) is a central protein in regulation of cellular response to hypoxia. This protein controls the responses of cell to oxygen level via the regulation of hypoxia inducible factor (HIF) stability. HIF induces the expression of many genes, especially ones orchestrate angiogenesis. There are some reports that mentioned in some tumor types the level of HIF is high in spite of the presence of wild-type PHD2 and normoxic environment. Therefore, the possibility of PHD2 misfolding in some cancer cells arises. Studying such important protein unfolding pathway is insightful for possible therapeutic approaches. In this study, the unfolding pathway of PHD2 illustrates utilizing molecular dynamics simulation of protein thermal denaturation. Based on current study results, we represent the possible mechanisms of PHD2 unfolding in detail. The possible intermediates of PHD2 thermal unfolding are characterized, and the most venomous state of its unfolding pathway is introduced.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8


  1. 1.

    D.A. Tennant, R.V. Duran, H. Boulahbel, E. Gottlieb, Carcinogenesis 30, 1269–1280 (2009)

    Article  CAS  Google Scholar 

  2. 2.

    K. Takenaga, Front Biosci. 16, 31–48 (2011)

    Article  CAS  Google Scholar 

  3. 3.

    D. Fukumura, R.K. Jain, Microvasc. Res. 74, 72–84 (2007)

    Article  CAS  Google Scholar 

  4. 4.

    P. Nyberg, T. Salo, R. Kalluri, Front Biosci. 13, 6537–6553 (2008)

    Article  CAS  Google Scholar 

  5. 5.

    M. Furuya, Y. Yonemitsu, I. Aoki, Curr. Pharm. Des. 15, 1854–1867 (2009)

    Article  CAS  Google Scholar 

  6. 6.

    D. Liao, R.S. Johnson, Cancer Metastasis Rev. 26, 281–290 (2007)

    Article  CAS  Google Scholar 

  7. 7.

    T. Acker, K.H. Plate, Cancer Treat. Res. 117, 219–248 (2004)

    Article  CAS  Google Scholar 

  8. 8.

    Q. Ke, M. Costa, Mol. Pharmacol. 70, 1469–1480 (2006)

    Article  CAS  Google Scholar 

  9. 9.

    K.A. Lee, J.D. Lynd, S. O’Reilly, M. Kiupel, J.J. McCormick, J.J. LaPres, Mol. Cancer Res. 6, 829–842 (2008)

    Article  CAS  Google Scholar 

  10. 10.

    R.J. Appelhoff, Y.M. Tian, R.R. Raval, H. Turley, A.L. Harris, C.W. Pugh, P.J. Ratcliffe, J.M. Gleadle, J. Biol. Chem. 279, 38458–38465 (2004)

    Article  CAS  Google Scholar 

  11. 11.

    D.A. Chan, A.J. Giaccia, Br. J. Cancer 103, 1–5 (2010)

    Article  CAS  Google Scholar 

  12. 12.

    T. Jokilehto, K. Rantanen, M. Luukkaa, P. Heikkinen, R. Grenman, H. Minn, P. Kronqvist, P.M. Jaakkola, Clin. Cancer Res. 12, 1080–1087 (2006)

    Article  CAS  Google Scholar 

  13. 13.

    H. Zhong, A.M. De Marzo, E. Laughner, M. Lim, D.A. Hilton, D. Zagzag, P. Buechler, W.B. Isaacs, G.L. Semenza, J.W. Simons, Cancer Res. 59, 5830–5835 (1999)

    CAS  Google Scholar 

  14. 14.

    S. Seshadri, K.A. Oberg, V.N. Uversky, Curr. Protein Pept. Sci. 10, 456–463 (2009)

    Article  CAS  Google Scholar 

  15. 15.

    A. Sadana, T. Vo-Dinh, Biotechnol. Appl. Biochem. 33, 7–16 (2001)

    Article  CAS  Google Scholar 

  16. 16.

    F. Ding, J.J. LaRocque, N.V. Dokholyan, J. Biol. Chem. 280, 40235–40240 (2005)

    Article  CAS  Google Scholar 

  17. 17.

    B. Urbanc, L. Cruz, F. Ding, D. Sammond, S. Khare, S.V. Buldyrev, H.E. Stanley, N.V. Dokholyan, Biophys. J. 87, 2310–2321 (2004)

    Article  CAS  Google Scholar 

  18. 18.

    V. Daggett, Methods Mol. Biol. 168, 215–247 (2001)

    CAS  Google Scholar 

  19. 19.

    A. Li, V. Daggett, Proc. Natl. Acad. Sci. U S A 91, 10430–10434 (1994)

    Article  CAS  Google Scholar 

  20. 20.

    V. Daggett, M. Levitt, J. Mol. Biol. 232, 600–619 (1993)

    Article  CAS  Google Scholar 

  21. 21.

    M.W. van der Kamp, V. Daggett, Top. Curr. Chem. 305, 169–197 (2011)

    Article  Google Scholar 

  22. 22.

    V. Daggett, Acc. Chem. Res. 35, 422–429 (2002)

    Article  CAS  Google Scholar 

  23. 23.

    A.R. Fersht, V. Daggett, Cell 108, 573–582 (2002)

    Article  CAS  Google Scholar 

  24. 24.

    R. Day, B.J. Bennion, S. Ham, V. Daggett, J. Mol. Biol. 322, 189–203 (2002)

    Article  CAS  Google Scholar 

  25. 25.

    J.C. Phillips, R. Braun, W. Wang, J. Gumbart, E. Tajkhorshid, E. Villa, C. Chipot, R.D. Skeel, L. Kale, K. Schulten, J. Comput. Chem. 26, 1781–1802 (2005)

    Article  CAS  Google Scholar 

  26. 26.

    M.A. McDonough, V. Li, E. Flashman, R. Chowdhury, C. Mohr, B.M. Lienard, J. Zondlo, N.J. Oldham, I.J. Clifton, J. Lewis, L.A. McNeill, R.J. Kurzeja, K.S. Hewitson, E. Yang, S. Jordan, R.S. Syed, C.J. Schofield, Proc. Natl. Acad. Sci. USA 103, 9814–9819 (2006)

    Article  CAS  Google Scholar 

  27. 27.

    A.D. Mackerell Jr, M. Feig, C.L. Brooks 3rd, J. Comput. Chem. 25, 1400–1415 (2004)

    Article  CAS  Google Scholar 

  28. 28.

    W. Humphrey, A. Dalke, K. Schulten, J. Mol. Graph. 14(33–38), 27–38 (1996)

    Google Scholar 

  29. 29.

    K. Lindorff-Larsen, S. Piana, R.O. Dror, D.E. Shaw, Science 334, 517–520 (2011)

    Article  CAS  Google Scholar 

  30. 30.

    B. Zagrovic, C.D. Snow, S. Khaliq, M.R. Shirts, V.S. Pande, J. Mol. Biol. 323, 153–164 (2002)

    Article  CAS  Google Scholar 

  31. 31.

    J.K. Myers, C.N. Pace, J.M. Scholtz, Protein Sci. 4, 2138–2148 (1995)

    Article  CAS  Google Scholar 

  32. 32.

    R. Chowdhury, M.A. McDonough, J. Mecinovic, C. Loenarz, E. Flashman, K.S. Hewitson, C. Domene, C.J. Schofield, Structure 17, 981–989 (2009)

    Article  CAS  Google Scholar 

  33. 33.

    S.J. Sheather, C. Jones, J. R. Stat. Soc: Ser. B (Stat. Methodol.) 53, 683–690 (1991)

    Google Scholar 

  34. 34.

    T.F. Cox, M.A.A. Cox, Multidimensional scaling (Chapman & Hall, London, 1994)

    Google Scholar 

  35. 35.

    N.A. Baker, D. Sept, S. Joseph, M.J. Holst, J.A. McCammon, Proc. Natl. Acad. Sci. 98, 10037–10041 (2001)

    Article  CAS  Google Scholar 

  36. 36.

    A. Rajan, P.L. Freddolino, K. Schulten, PLoS ONE 5, e9890 (2010)

    Article  Google Scholar 

  37. 37.

    M.S. Cheung, A.E. Garcia, J.N. Onuchic, PNAS 99, 685–690 (2002)

    Article  CAS  Google Scholar 

  38. 38.

    Y. Levy, J.N. Onuchic, Proc. Natl. Acad. Sci. USA 101, 3325–3326 (2004)

    Article  CAS  Google Scholar 

  39. 39.

    Y.M. Rhee, E.J. Sorin, G. Jayachandran, E. Lindahl, V.S. Pande, Proc. Natl. Acad. Sci. USA 101, 6456–6461 (2004)

    Article  CAS  Google Scholar 

Download references


We gratefully acknowledge the support of the University of Tehran, Iran National Science Foundation (INSF), and the Center of Excellence in Biothermodynamics (CEBiotherm).

Author information



Corresponding author

Correspondence to Ali A. Moosavi-Movahedi.

Electronic supplementary material

Below is the link to the electronic supplementary material.


SI-1 To have estimation about the correspondence of PHD2 3D structure and 2D map of X, Y coordinates of PHD2 Cα along 25-ns MD, this graph is generated. Equal regions of 2D map and 3D structure are clarified via arrows. Darker regions are more populated. (TIF 1.48 mb)


SI-2 This animated image shows the distribution of Cl+ ions in simulation space around PHD2 protein along 25-ns MD. PHD2 is represented by ribbon structure. Cl+ ions are presented via color points. Each color of point represents a specific ion with unique atom ID. As this animation demonstrates, a very small fraction of Cl+ atoms penetrated to PHD2 core. (GIF 3.91 mb)


SI-3 This animated image shows the distribution of Na+ ions in simulation space around PHD2 protein along 25-ns MD. PHD2 is represented by ribbon structure. Na+ ions are presented via color points. Each color of point represents a specific ion with unique atom ID. As this animation demonstrates, substantial fraction of Na+ atoms penetrated to PHD2 core. (GIF 7.04 mb)


SI-4 The APBS computed electrostatic potential (EP) of PHD2 is represented. Red surface stands for regions with negative EP. Regions with positive EP are highlighted by blue surface. (TIF 680 kb)


SI-5 The negative electrostatic potential of PHD2 is represented via EP filed lines. This animated image shows that negative EP penetrates into PHD2 lumen, and therefore, such EP attracts positive ions to protein core. (GIF 3.73 mb)


SI-6 This graph represents the interaction energy between ion and PHD2 residue’s types along 25-ns simulation time. Panel (a) shows interaction energies smaller than −0.5 kcal/mol. The (b) and (c) sections represent interaction energies smaller than 1.0 and 2.0 kcal/mol, respectively. The most strong attraction energies between ions and residues present in panel (c). (TIF 1.15 mb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Hadi-Alijanvand, H., Moosavi-Movahedi, A.A. & Goliaei, B. Unfolding mechanism of PHD2 as a vital protein: all-atom simulation approach. J IRAN CHEM SOC 10, 907–914 (2013).

Download citation


  • PHD2
  • Angiogenesis
  • Protein unfolding pathway
  • Molecular dynamics simulation
  • Intermediate states
  • Unfolding mechanism