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Lessons from Simulation Regarding the Control of Synthetic Self-Assembly

  • Jack F. Douglas (a1) and Kevin Van Workum (a2)


We investigate the role of particle potential symmetry on self-assembly by Monte Carlo simulation with the particular view towards synthetically creating structures of prescribed form and function. First, we establish a general tendency for the rotational potential symmetries of the particles to be locally preserved upon self-assembly. Specifically, we find that a dipolar particle potential, having a continuous rotational symmetry about the dipolar axis, gives rise to chain formation, while particles with multipolar potentials (e.g., square quadrupole) having discrete rotational symmetries led to the self-assembly of random surface polymers preserving the rotational symmetries of the particles within these sheet structures. Surprisingly, these changes in self-assembly geometry with the particle potential symmetry are also accompanied by significant changes in the thermodynamic character and in the kinetics of the self-assembly process. Linear chain growth involves a continuous chain growth process in which the chains break and reform readily, while the growth of the two-dimensional polymers only occurs after an ‘initiation’ or ‘nucleation’ time that fluctuates from run to run. We show that the introduction of artificial seeds provides an effective method for controlling the structure and growth kinetics of sheet-like polymers. The significance of these distinct modes of polymerization on the functional character of self-assembly growth is illustrated by constructing an artificial centrosome structure derived from particles having continuous and discrete rotational potential symmetries.



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1. Klug, A., Proc. Roy. Soc. A 348, 167 (1994).
2. Oosawa, F. and Asakura, S., Thermodynamics of the Polymerization of Protein (Academic Press, New York, 1975).
3. Caspar, D. L. D. and Klug, A., Cold Spring Harbor Symp. Quant. Biol. 27, 1 (1962);
See also: Caspar, D. L. D., Biophys. J. 32, 103 (1980);
Makowski, L., Biophys. J. 74, 534 (1998);
Klug, A., Nature 303, 378 (1983);
Johnson, J. J. and Spier, J. A., J. Mol. Biol. 269, 665 (1997);
Chapman, M. S., Biophys. J. 74, 639 (1998).
4. Philp, D. and Stoddart, J. F., Angew. Chem.-Int. Edit. Engl. 35, 1155 (1996).
5. Moore, J. S., Current Opinion Coll. Int. Sci. 4, 108 (1999).
6. Lehn, J. M., Supramolecular Chemistry (VCH, Weinheim, 1995).
7. Alivisatos, A. P., Johnsson, K. P., Peng, X. G., Wilson, T. E., Loweth, C. J., Bruchez, M. P. and Schultz, P. G., Nature 382, 609 (1996).
8. Jeneke, S. A. and Chen, X. L., Science 283, 372 (1999).
9. Brunsveld, L., Folmer, B. J. B., Meijer, E. W. and Sijbesma, R. P., Chem. Rev. 101, 4071 (2001).
10. de Gans, B. J., Wiegand, S., Zubarev, E. R., and Stupp, S. I.., J. Phys. Chem. B 106, 9730 (2002).
11. Stupp, S. I., Son, S., Lin, H. C., and Li, L. S., Science 259, 59 (1993);
Stupp, S. I., LeBonheur, V., Walker, K., Li, L. S., Huggins, K. E., Keser, M., and Amstutz, A., Science 276, 384 (1997).
12. Mirkin, C. A., Letsinger, R. L., Mucic, R. C., and Storhoff, J. J., Nature 382, 607 (1996).
13. Schnur, J., Science 262, 1669 (1993).
14. Ghadiri, M. R., Granja, J. R., Milligan, R. A., McRee, D. E. and Khazanovich, N., Nature 366, 324 (1993).
See also: Furhop, J. -H. and Helfrisch, W., Chem. Rev. 93, 1565 (1993).
15. Lawrence, D.S., Jiang, T., Levelt, M., Chem. Rev. 95, 2229 (1995).
16. Crick, F. H. C. and Watson, J. D., Nature 177, 473 (1956).
17. Finch, J. T. and Klug, A., Nature 183, 1709 (1959);
See also: Bancroft, J. B., Advances in Virus Research (Academic, New York, 1970);
Rossmann, M. G. and Johnson, J. E., Ann. Rev. Biochem. 58, 533 (1989).
18. Van Workum, K. and Douglas, J. F., Phys. Rev. E 71, 031502 (2004);
Staumbaugh, J., Van Workum, K. and Douglas, J. F. and Losert, W., Phys. Rev. E 72, 031301 (2005).
19. Shelley, J. C., Patey, G. N., Levesque, D., and Weis, J. J., Phys. Rev. E 59, 3065 (1999).
20. Chen, B. and Siepmann, J. I., J. Phys. Chem. B 105, 11275 (2001).
21. Dudowicz, J., Freed, K. F., and Douglas, J. F., J. Chem. Phys. 112, 1002 (2000);
J. Chem. Phys 113, 434 (2000);
J. Chem. Phys. 119, 12645 (2003).
22. Staumbaugh, J., PhD Thesis, University of Maryland (College Park), 2004. The raw data from which the dipole moments were calculated was obtained from the protein databank.
23. Van Workum, K. and Douglas, J. F., Mackromol. Symp. 227, 1 (2005); Phys. Rev. E (submitted).
24. Wolde, P. R. ten, Oxtoby, D. W. and Frenkel, D., Phys. Rev. Lett. 81, 3695 (1988).
25. Dijkstra, M., Hansen, J. P., and Madden, P. A., Phys. Rev. Lett. 75, 2236 (1995);
Phys. Rev. E 55, 3044 (1997).
26. Cao, Z. and Ferrone, F. A., Biophys. J. 72, 343 (1997);
King, J. and Casjens, S., Nature 251, 112 (1974);
Klug, A., Angew. Chem: Int. Edn. 22, 565 (1983).
27. Fygenson, D. K., Braun, E. and Libchaber, A., Phys. Rev. E 50, 1579 (1994);
Flyvbjerg, H., Holy, T. E. and Leibler, S., Phys. Rev. E 54, 5538 (1996).
28. Holy, T. E., Dogterom, M., Yurke, B. amd Leibler, S., Proc. Nat. Acad. Sci. 94, 6228 (1997);
Nédélec, F. J. et al. , Nature, 389, 305 (1997);
Rodionov, V., Nadezhdina, E., Borisy, G., Proc. Nat. Acad. Sci. 96, 115 (1999).
29. Watts, N. R. et al. , J. Cell Biology 150, 349 (2000).


Lessons from Simulation Regarding the Control of Synthetic Self-Assembly

  • Jack F. Douglas (a1) and Kevin Van Workum (a2)


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