• DocumentCode
    1065407
  • Title

    Precise Simulation Model for DNA Tile Self-Assembly

  • Author

    Fujibayashi, K. ; Murata, S.

  • Author_Institution
    Dept. of Comput. Intell. & Syst. Sci., Tokyo Inst. of Technol., Yokohama
  • Volume
    8
  • Issue
    3
  • fYear
    2009
  • fDate
    5/1/2009 12:00:00 AM
  • Firstpage
    361
  • Lastpage
    368
  • Abstract
    Self-assembling DNA complexes have been intensively studied in recent years aiming to achieve bottom-up construction of nanoscale objects. Among them a DNA complex called the DNA tile is known for its high programmability. DNA tiles can form 2-D crystals with programmable patterns via self-assembly. In order to create a wide range of complex objects by algorithmic self-assembly, we need a methodology to predict its behavior. To estimate the behavior, we can use thermodynamic simulations based on the Monte Carlo method. However, the previous simulation model assumed some simplified conditions and was not able to adequately explain the results of crystal growth experiments. Here, we propose the realistic tile assembly model, in which we are able to simulate the detailed conditions of the experimental protocols. By this model, the results of experiments (e.g., error rates, growth rate, and the formation and melting temperatures) are reproduced with high reliability. We think this model is useful to predict the behavior of DNA self-assembly and to design various types of DNA complexes.
  • Keywords
    DNA; crystal growth; melting; molecular biophysics; self-assembly; DNA tile self-assembly; crystal growth; melting; Assembly; Crystals; DNA; Error analysis; Predictive models; Protocols; Self-assembly; Temperature; Thermodynamics; DNA; Distributed algorithms; Monte Carlo methods; molecular electronics; nanotechnology; self-organizing control; simulation;
  • fLanguage
    English
  • Journal_Title
    Nanotechnology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1536-125X
  • Type

    jour

  • DOI
    10.1109/TNANO.2008.2011776
  • Filename
    4749332