Precise Simulation Model for DNA Tile Self-Assembly

• Published in: IEEE transactions on nanotechnology Vol. 8; no. 3; pp. 361 - 368
• Main Authors: Fujibayashi, K., Murata, S.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.05.2009; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applied sciences; Assembly; Crystals; Deoxyribonucleic acid; Distributed algorithms; DNA; Electronics; Error analysis; Exact sciences and technology; molecular electronics; Molecular electronics, nanoelectronics; Monte Carlo methods; nanotechnology; Predictive models; Protocols; Self-assembly; self-organizing control; Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices; simulation; Studies; Temperature; Thermodynamics; Crystal growth; Self assembly; Monte Carlo method; Growth rate; simulation; Error rate; Algorithmics; Nanoelectronics; self-organizing control; Nanometer scale; Molecular electronics; Monte Carlo methods; Self organization; Thermodynamic model; DNA; Distributed algorithm; Self control; Numerical simulation; Reliability; Distributed algorithms; Nanotechnology
• ISSN: 1536-125X; 1941-0085
• DOI: 10.1109/TNANO.2008.2011776

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.