Skip to main content
Log in

Computer simulation of biological interactions and reactivity

  • Research Papers
  • Published:
Journal of Computer-Aided Molecular Design Aims and scope Submit manuscript

Summary

Computer simulations of molecular motion provide a useful tool for analyzing dynamic aspects of macromolecular structure and function. In many cases, simulations can be compared to experimental results that provide an average estimate of molecular flexibility. For example, variations in computed molecular motions in different regions of a protein structure can be compared to refined B-values obtained from X-ray crystallographic refinement. Such comparisons both provide a detailed view of the motions responsible for crystalline disorder, and allow an evaluation of how crystal packing affects mobility of groups on the protein surface. In these applications, dynamics simulations provide a means of regenerating the temporal dimension of a structure whose average behavior is experimentally well defined in the crystal lattice.

An additional benefit of the detailed and instantaneous view of molecular flexibility offered by simulation methods lies in its potential for exploring infrequent structural fluctuations or dynamic states of molecular association that cannot be examined in detail by X-ray methods, but are suggested on the basis of alternative structural information. For example, studies of the effects of surface chemical modifications on interacting proteins can produce information concerning the sites, if not the exact details, of the intermolecular interactions. The present work describes some applications of molecular dynamics methods to the study of large molecular aggregates whose dynamic properties thus far have precluded detailed structural descriptions. These include simulations of an electrostatically associated electron transfer complex between cytochromes c and b5, some model systems for trans-membrane ion channels, and a phospholipid micelle.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. McCammon, J.A. and Harvey, C., Dynamics of Proteins and Nucleic Acids. Cambridge University Press. Cambridge, 1987.

    Google Scholar 

  2. Salemme, F.R., Genieser, L., Finzel, B.C., Hilmer, R. and Wendoloski, J.J., submitted to J. Crys. Growth.

  3. Weiner, P. and Kollman, P.A., J. Comput. Chem. 2 (1981) 287–303.

    Google Scholar 

  4. Singh, U.C. and Kollman, P.A., ibid., 5 (1984) 129–145.

    Google Scholar 

  5. Weiner, S.J., Kollman, P.A., Case, D.A., Singh, U.C., Ghio, C., Alagona, G., Profeta Jr., S. and Weiner, P., J. Am. Chem. Soc., 106 (1984) 765–784.

    Google Scholar 

  6. Berendsen, H.J.C., Postma, J.P.M., di Nola, A., van Gunsteren, W.F., and Haak, J.R., J. Chem. Phys. 81 (1984) 3684–3690.

    Google Scholar 

  7. Jorgensen, W.L., Chandrasekhar, J., Madura, J., Impey, R.W. and Klein, M.L., J. Chem. Phys., 79 (1983) 926–935.

    Google Scholar 

  8. Brooks, B.R., Applications of Molecular Dynamics for Structural Analysis of Proteins and Peptides, In Jensen, C. and Truhlar, D. (Eds.) Supercomputer Research in Chemistry and Chemical Engineering, American Chemical Society, Washington, D.C., 1987, pp. 123–145.

    Google Scholar 

  9. Scott, R.A., Mauk, A.G. and Gray, H.B., J. Chem. Educ., 62 (1985) 932–937.

    Google Scholar 

  10. Marcus, R.A., Annu. Rev. Phys. Chem., 15 (1964) 155–196.

    Google Scholar 

  11. Wherland, S. and Gray, H.B., Proc. Natl. Acad. Sci. U.S.A., 73 (1976) 2950–2954.

    Google Scholar 

  12. Mayo, S.L., Ellis Jr., W.R., Crutchley, R.J. and Gray, H.B., Science, 233 (1986) 948.

    Google Scholar 

  13. Salemme, F.R., J. Mol. Biol., 102 (1976) 563–568.

    Google Scholar 

  14. Hopfield, J.J., Proc. Natl. Acad. Sci. U.S.A., 71 (1974) 3640–3644.

    Google Scholar 

  15. Fox, R.G. and Richards F.M., Nature, 300 (1982) 325.

    Google Scholar 

  16. Noda, M., Takahashi, H., Tanabe, T., Toyosato, M., Kikyotani, S., Furutani, Y., Hirose, T., Takashima, H., Inayama, S., Miyata, T. and Numa, S., Nature, 302 (1983) 528–532.

    Google Scholar 

  17. Numa, S. and Noda, M., Ann. N.Y. Acad. Sci., 479 (1986) 338.

    Google Scholar 

  18. Elder, M., Hitchcock, P., Mason, R., and Shipley, G.G., Proc. R. Soc. London, Ser. A., 354 (1977) 157–170.

    Google Scholar 

  19. Dill, K.A. and Flory, P.J., Proc. Natl. Acad. Sci. U.S.A., 77 (1980) 3115–3119.

    Google Scholar 

  20. Dill, K.A. and Flory, P.J., ibid. 78 (1981) 676–680.

    Google Scholar 

  21. Dill, K.A., Koppel, D.E., Cantor, R.S., Dill, J.A., Bendedouch, D. and Chen, S.-H., Nature, 309 (1984) 42–45.

    Google Scholar 

  22. Haile, J.M. and O'Connell, J.P., J. Phys. Chem., 88 (1984) 6363–6366.

    Google Scholar 

  23. Woods, M.C., Haile, J.M., and O'Connell, J.P., J. Phys. Chem., 90 (1986) 1875–1884.

    Google Scholar 

  24. Jonsson, B., Edholm, O. and Teleman, O., J. Chem. Phys., 85 (1986) 2259–2271.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wendoloski, J.J., Wasserman, Z.R. & Salemme, F.R. Computer simulation of biological interactions and reactivity. J Computer-Aided Mol Des 1, 313–322 (1988). https://doi.org/10.1007/BF01677279

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01677279

Key words

Navigation