This free resource is developed and maintained by the Laboratory for Computational Biology & Biophysics at MIT, which is directed by Professor Mark Bathe.

The 3D solution shape and flexibility of programmed DNA assemblies are predicted using a mechanical model of DNA that assumes the DNA double-helix to be a homogeneous elastic rod with axial, twisting, and bending moduli that have been measured experimentally [8]. These mechanical elements that are constrained to neighbors using double-stranded crossovers provide internal constraints that deform DNA from its straight, rod-like conformation to complex shapes as shown in detail in [4, 9-10].

Computational prediction of deformed DNA shapes is performed using the Finite Element Method implemented in the commercial software program ADINA (ADINA R&D, Inc.), which is a well established numerical technique for the analysis of complex structural mechanics and dynamics [13]. The thermally-induced fluctuations of DNA nanostructures are computed using the equipartition theorem of statistical mechanics and normal mode analysis [14], as shown for proteins in [15-16]. Atomic models of DNA nanostructures are generated from 3D solution shapes and thermal fluctuations, as shown for the design of light-harvesting nanodevices [17] and DNA casting molds for inorganic structures [18].

Setting up the preceding finite element model using CanDo requires input files that specify the sequence topology of the underlying DNA nanostructure, as well as its initial configuration (basepair coordinates and orientations). Our lab has developed the ability to read in these model features from either caDNAno or Tiamat files, which are two popular drawing programs, as well as from our own file format with extension cndo.

The source code needed to generate the finite element models are available upon request by e-mailing Daniel Dardani (ddardani@mit.edu).

The Laboratory for Computational Biology & Biophysics is grateful to its sponsors for financial support including the Office of Naval Research, the Army Research Office, and the National Science Foundation.

 

References

1. Y Krishnan and M Bathe. Designer nucleic acids to probe and program the cell. Trends in Cell Biology, 22: 624-633 (2012). [ Pubmed ]

2. PWK Rothemund. Folding DNA to create nanoscale shapes and patterns. Nature, 440: 297-302 (2006). [ Pubmed ]

3. SM Douglas, H Dietz, T Liedl, B Högberg, F Graf, WM Shih. Self assembly of DNA into nanoscale three-dimensional shapes. Nature, 459: 414-418 (2009). [ Pubmed ]

4. H Dietz, SM Douglas, WM Shih. Folding DNA into twisted and curved nanoscale shapes. Science, 325: 725-730 (2009). [ Pubmed ]

5. Y Ke, SM Douglas, M Liu, J Sharma, A Cheng, A Leung, Y Liu, WM Shih, H Yan. Multilayer DNA origami packed on a square lattice. Journal of the American Chemical Society, 131: 15903-15908 (2009). [ Pubmed ]

6. SM Douglas, AH Marblestone, S Teerapittayanon, A Vazquez, GM Church, WM Shih. Rapid prototyping of 3D DNA origami shapes with caDNAno. Nucleic Acids Research, 37: 5001-5006 (2009). [ Pubmed ]

7. S Williams, K Lund, C Lin, P Wonka, S Lindsay, H Yan. Tiamat: a three-dimensional editing tool for complex DNA structures. in DNA 14, Lecture Notes in Computer Science, Vol. 5347: 90–101 (Springer, 2009). [ Article ]

8. JP Peters and LJ Maher. DNA curvature and flexibility in vitro and in vivo. Quarterly Reviews of Biophysics, 43: 23-63 (2010). [ Pubmed ]

9. CE Castro, F Kilchherr, DN Kim, EL Shiao, T Wauer, P Wortmann, M Bathe, H Dietz. A primer to scaffolded DNA origami. Nature Methods, 8: 221-229 (2011). [ Pubmed ]

10. DN Kim, F Kilchherr, H Dietz, M Bathe. Quantitative prediction of 3D solution shape and flexibility of nucleic acid nanostructures. Nucleic Acids Research, 40(7):2862-2868 (2012). [ Pubmed ]

11. K Pan, DN Kim, F Zhang, MR Adendorff, H Yan, M Bathe. Lattice-free prediction of three-dimensional structure of programmed DNA assemblies. Nature Communications, 5: 5578 (2014). [ PubMed ]

12. T Liedl, B Högberg, J Tytell, DE Ingber, WM Shih. Self-assembly of three-dimensional prestressed tensegrity structures from DNA. Nature Nanotechnology, 5: 520-524 (2010). [ Pubmed ]

13. KJ Bathe. Finite Element Procedures. (1996).

14. RS Sedeh, K Pan, MR Adendorff, O Hallatschek, KJ Bathe, M Bathe. Computing nonequilibrium conformational dynamics of structured nucleic acid assemblies. Journal of Chemical Theory and Computation, 12: 261-273 (2016). [ Pubmed ]

15. M Bathe. A Finite Element framework for computation of protein normal modes and mechanical response. Proteins, 70: 1595-1609 (2008). [ Pubmed ]

16. DN Kim, CT Nguyen, M Bathe. Conformational dynamics of supramolecular protein assemblies. Journal of Structural Biology, 173: 261-270 (2011). [ Pubmed ]

17. K Pan, E Boulais, L Yang, M Bathe. Structure-based model for light-harvesting properties of nucleic acid nanostructures. Nucleic Acids Research, 42: 2159-2170 (2014). [ PubMed ]

18. W Sun, E Boulais, Y Hakobyan, W Wang, A Guan, M Bathe, P Yin. Casting inorganic structures with DNA molds. Science, 346: 1258361 (2014). [ PubMed ]

19. S Kalinin, T Peulen, S Sindbert, PJ Rothwell, S Berger, T Restle, RS Goody, H Gohlke, CA Seidel. A toolkit and benchmark study for FRET-restrained high-precision structural modeling. Nature Methods, 9: 1218-1225 (2012) [ PubMed ]

20. S Sindbert, S Kalinin, H Nguyen, A Kienzler, L Clima, W Bannwarth, B Appel, S Müller, CA Seidel. Accurate distance determination of nucleic acids via Förster resonance energy transfer: implications of dye linker length and rigidity. Journal of the American Chemical Society, 133: 2463-2480 (2011) [ PubMed ]