Skip to main content
Springer Nature Link
Log in

Recent developments of the quantum chemical cluster approach for modeling enzyme reactions

  • Minireview
  • Published:
JBIC Journal of Biological Inorganic Chemistry Aims and scope Submit manuscript

Abstract

The quantum chemical cluster approach for modeling enzyme reactions is reviewed. Recent applications have used cluster models much larger than before which have given new modeling insights. One important and rather surprising feature is the fast convergence with cluster size of the energetics of the reactions. Even for reactions with significant charge separation it has in some cases been possible to obtain full convergence in the sense that dielectric cavity effects from outside the cluster do not contribute to any significant extent. Direct comparisons between quantum mechanics (QM)-only and QM/molecular mechanics (MM) calculations for quite large clusters in a case where the results differ significantly have shown that care has to be taken when using the QM/MM approach where there is strong charge polarization. Insights from the methods used, generally hybrid density functional methods, have also led to possibilities to give reasonable error limits for the results. Examples are finally given from the most extensive study using the cluster model, the one of oxygen formation at the oxygen-evolving complex in photosystem II.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+
from $39.99 /Month
  • Starting from 10 chapters or articles per month
  • Access and download chapters and articles from more than 300k books and 2,500 journals
  • Cancel anytime
View plans

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Explore related subjects

Discover the latest articles and news from researchers in related subjects, suggested using machine learning.

Notes

  1. For a recent comprehensive review on QM/MM methods for biological systems see Ref. [2].

References

  1. Siegbahn PEM, Crabtree RH (1997) J Am Chem Soc 119:3103–3113

    Article  CAS  Google Scholar 

  2. Senn HM, Thiel W (2007) Top Curr Chem 268:173

    Google Scholar 

  3. Becke AD (1993) J Chem Phys 98:5648–5652

    Article  CAS  Google Scholar 

  4. Siegbahn PEM (2006) J Biol Inorg Chem 11:695–701

    Article  PubMed  CAS  Google Scholar 

  5. Reiher M, Salomon O, Hess BA (2001) Theor Chem Acc 107:48–55

    CAS  Google Scholar 

  6. Siegbahn PEM (2007) C R Chim 10:766–774

    CAS  Google Scholar 

  7. Nilsson Lill SO, Siegbahn PEM (2009) Biochemistry 48:1056–1066

    Google Scholar 

  8. Grimme S (2006) J Chem Phys 124:034108

    Article  PubMed  Google Scholar 

  9. Schwabe T, Grimme S (2007) Phys Chem Chem Phys 9:3397–3406

    Article  PubMed  CAS  Google Scholar 

  10. Piacenza M, Hyla-Krypsin I, Grimme S (2007) J Comput Chem 28:2275–2285

    Article  PubMed  CAS  Google Scholar 

  11. Radon M, Pierloot K (2008) J Phys Chem 112:11824–11832

    Article  PubMed  CAS  Google Scholar 

  12. Harayama S, Rekik M, Ngai K-L, Ornston NJ (1989) Bacteriology 171:6251

    CAS  Google Scholar 

  13. Harayama S, Rekik M (1989) J Biol Chem 264:15328

    PubMed  CAS  Google Scholar 

  14. Subramanya HS, Roper DI, Dauter Z, Dodson EJ, Davies GJ, Wilson KS, Wigley DB (1996) Biochemistry 35:792

    Article  PubMed  CAS  Google Scholar 

  15. Taylor AB, Czerwinski RM, Johnson WH Jr, Whitman CP, Hackert ML (1998) Biochemistry 37:14692

    Article  PubMed  CAS  Google Scholar 

  16. Harris TK, Czerwinski RM, Johnson WH Jr, Legler PM, Abeygunawardana C, Massiah MA, Stivers JT, Whitman CP, Mildvan AS (1999) Biochemistry 38:12343

    Article  PubMed  CAS  Google Scholar 

  17. Czerwinski RM, Harris TK, Johnson WH Jr, Legler PM, Stivers JT, Mildvan AS, Whitman CP (1999) Biochemistry 38:12358

    Article  PubMed  CAS  Google Scholar 

  18. Metanis N, Brik A, Dawson PE, Keinan E (2004) J Am Chem Soc 126:12726

    Article  PubMed  CAS  Google Scholar 

  19. Metanis N, Keinan E, Dawson PE (2005) J Am Chem Soc 127:5862

    Article  PubMed  CAS  Google Scholar 

  20. Sevastik R, Himo F (2007) Bioorg Chem 35:444

    Article  PubMed  CAS  Google Scholar 

  21. Barone V, Cossi M (1998) J Phys Chem A 102:1995

    Article  CAS  Google Scholar 

  22. Cisneros GA, Liu H, Zhang Y, Yang W (2003) J Am Chem Soc 125:10384

    Article  PubMed  CAS  Google Scholar 

  23. Cisneros GA, Wang M, Silinski P, Fitzgerald MC, Yang W (2004) Biochemistry 43:6885

    Article  PubMed  CAS  Google Scholar 

  24. Cisneros GA, Wang M, Silinski P, Fitzgerald MC, Yang WJ (2006) Phys Chem A 110:700

    Article  CAS  Google Scholar 

  25. Nakamura T, Nagasawa T, Yu F, Watanabe I, Yamada H (1994) Appl Environ Microbiol 60:1297

    PubMed  CAS  Google Scholar 

  26. van den Wijngaard AJ, Reuvekamp PTW, Janssen DB (1991) J Bacteriol 173:124

    PubMed  Google Scholar 

  27. van Hylckama Vlieg JET, Tang L, Lutje Spelberg JH, Smilda T, Poelarends GJ, Bosma T, van Merode AE, Fraaije MW, Janssen DB (2001) J Bacteriol 183:5058

    Article  PubMed  Google Scholar 

  28. Janssen DB, Majeric-Elenkov M, Hasnoui G, Hauer B, Lutje Spelberg JH (2006) Biochem Soc Trans 34:291

    Article  PubMed  CAS  Google Scholar 

  29. Majeric-Elenkov M, Hauer B, Janssen DB (2006) Adv Synth Catal 348:579

    Article  Google Scholar 

  30. Lutje Spelberg JH, van Hylckama Vlieg JET, Tang L, Janssen DB, Kellogg RM (2001) Org Lett 3:41

    Article  Google Scholar 

  31. Lutje Spelberg JH, Tang L, van Gelder M, Kellogg RM, Janssen DB (2002) Tetrahedron Asym 13:1083

    Article  CAS  Google Scholar 

  32. Majeric-Elenkov M, Tang L, Hauer B, Janssen DB (2006) Org Lett 8:4227

    Article  PubMed  CAS  Google Scholar 

  33. Hasnaoui G, Lutje Spelberg JH, de Vries E, Tang L, Hauer B, Janssen DB (2005) Tetrahedron Asym 16:1685

    Article  CAS  Google Scholar 

  34. Nakamura T, Nagasawa T, Yu F, Watanabe I, Yamada H (1991) Biochem Biophys Res Commun 180:124

    Article  PubMed  CAS  Google Scholar 

  35. Hopmann KH, Himo FJ (2008) Chem Theor Comput 4:1129

    Article  CAS  Google Scholar 

  36. Inoue T, Shiota Y, Yoshizawa K (2008) J Am Chem Soc 130:16890–16897

    Article  PubMed  CAS  Google Scholar 

  37. Siegbahn PEM (2003) J Biol Inorg Chem 8:567–576

    PubMed  CAS  Google Scholar 

  38. Schneboom JC, Lin H, Reuter N, Thiel W, Cohen S, Ogliaro F, Shaik S (2002) J Am Chem Soc 124:8142–8151

    Article  Google Scholar 

  39. Altun A, Shaik S, Thiel W (2006) J Comp Chem 27:1324–1337

    Article  CAS  Google Scholar 

  40. Schrödinger (1991–2003) Jaguar 5.5. Schrödinger, Portland

  41. Vreven T, Byun KS, Komaromi I, Dapprich S, Montgomery JA Jr, Morokuma K, Frisch MJ (2006) J Chem Theory Comput 2:815–826

    Article  CAS  Google Scholar 

  42. Frisch MJ et al (2003) Gaussian 03, revision B.03. Gaussian, Pittsburgh

    Google Scholar 

  43. Friesner RA (2005) Adv Protein Chem 72:79–104

    Article  PubMed  Google Scholar 

  44. Riccardi D, Schaefer P, Yang Y, Yu H, Ghosh N, Prat-Resina X, König P, Li G, Xu D, Guo H, Elstner M, Cui Q (2006) J Phys Chem B 110:6458–6469

    Article  PubMed  CAS  Google Scholar 

  45. Senthilkumar K, Mujika JI, Ranaghan KE, Manby FR, Mulholland AJ, Harvey JN (2008) J R Soc Interface 5:S207–S216

    Article  PubMed  CAS  Google Scholar 

  46. Ferreira KN, Iverson TM, Maghlaoui K, Barber J, Iwata S (2004) Science 303:1831–1838

    Article  PubMed  CAS  Google Scholar 

  47. Loll B, Kern J, Saenger W, Zouni A, Biesiadka J (2005) Nature 438:1040–1044

    Article  PubMed  CAS  Google Scholar 

  48. Yano J, Kern J, Irrgang K-D, Latimer MJ, Bergmann U, Glatzel P, Pushkar Y, Biesiadka J, Loll B, Sauer K, Messinger J, Zouni A, Yachandra VK (2005) Proc Natl Acad Sci USA 102:12047–12052

    Article  PubMed  CAS  Google Scholar 

  49. Dau H, Grundmeier A, Loja P, Haumann M (2008) Philos Trans R Soc Lond B 363:1237–1244

    Article  CAS  Google Scholar 

  50. Siegbahn PEM (2006) Chem Eur J 12:9217–9227

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Physics, ALBA NOVA, Arrhenius Laboratory, Stockholm University, 106 91, Stockholm, Sweden

    Per E. M. Siegbahn

  2. Department of Biochemistry and Biophysics, Arrhenius Laboratory, Stockholm University, 106 91, Stockholm, Sweden

    Per E. M. Siegbahn

  3. Department of Theoretical Chemistry, School of Biotechnology, Royal Institute of Technology, 106 91, Stockholm, Sweden

    Fahmi Himo

Authors
  1. Per E. M. Siegbahn
    View author publications

    Search author on:PubMed Google Scholar

  2. Fahmi Himo
    View author publications

    Search author on:PubMed Google Scholar

Corresponding author

Correspondence to Per E. M. Siegbahn.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Siegbahn, P.E.M., Himo, F. Recent developments of the quantum chemical cluster approach for modeling enzyme reactions. J Biol Inorg Chem 14, 643–651 (2009). https://doi.org/10.1007/s00775-009-0511-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00775-009-0511-y

Keywords