Programmable molecular recognition based on the geometry of DNA nanostructures

Journal name:
Nature Chemistry
Volume:
3,
Pages:
620–627
Year published:
DOI:
doi:10.1038/nchem.1070
Received
Accepted
Published online
Corrected online

Abstract

From ligand–receptor binding to DNA hybridization, molecular recognition plays a central role in biology. Over the past several decades, chemists have successfully reproduced the exquisite specificity of biomolecular interactions. However, engineering multiple specific interactions in synthetic systems remains difficult. DNA retains its position as the best medium with which to create orthogonal, isoenergetic interactions, based on the complementarity of Watson–Crick binding. Here we show that DNA can be used to create diverse bonds using an entirely different principle: the geometric arrangement of blunt-end stacking interactions. We show that both binary codes and shape complementarity can serve as a basis for such stacking bonds, and explore their specificity, thermodynamics and binding rules. Orthogonal stacking bonds were used to connect five distinct DNA origami. This work, which demonstrates how a single attractive interaction can be developed to create diverse bonds, may guide strategies for molecular recognition in systems beyond DNA nanostructures.

At a glance

Figures

  1. Stacking of rectangles.
    Figure 1: Stacking of rectangles.

    a, A long scaffold strand (black) is folded by multiple short staple strands to form a rectangle; features include edge staples (blue and red), interior staples (grey), dumbbell hairpins (orange ovals) and single-stranded loopouts (black bulges). The grey box indicates an area enlarged in (f). Each column of staples was originally 16 nucleotides (nt) wide5; in twist-corrected rectangles, columns with base deletions (pink) are 15 nt wide. b,c, AFM comparison of rectangle chains without (b) and with (c) twist correction, deposited on mica. Upper left insets show models of single rectangles. Lower right inset (b) models how periodic breaks arise in a twisted chain during deposition. d, Proposed structure of a ‘stressed edge’. e, Model and AFM image of rectangles with ‘stressed edges’. Solid vertical bars indicate that no stacking polarity is expected. Dashed vertical arrows emphasize that edges do not bond in an exclusively antiparallel orientation, as exemplified by rectangles related by 180° horizontal or vertical flips (indicated by half-circle arrows with an in-plane axis of rotation). Rectangles bind in head-to-tail (h2t), rotated (rot), horizontally flipped (h-flip) and vertically flipped (v-flip) orientations. f, Proposed structure of a ‘relaxed edge’. g, Model and AFM images of rectangles with ‘relaxed edges’ (a larger example shown in c). Vertical arrows label stacking polarity; only ‘antiparallel’ bonds form. Half-circle arrows indicate 180° rotation (about an axis going into the plane through the centre of a bond). Scale bars: 500 nm (b,c); 100 nm (e,g).

  2. Recognition based on binary sequences of blunt ends and scaffold loops.
    Figure 2: Recognition based on binary sequences of blunt ends and scaffold loops.

    a, Model and AFM images of a 32-helix tall rectangle that enables 16-bit binary codes. Addition of a staple at a specific edge site creates two blunt ends, which compose an active patch (‘1’); omission of the staple leaves a single-stranded loop that forms an inactive patch (‘0’). Use of an asymmetric sequence ‘0001011110001100’ with seven active patches creates long chains with an exclusively head-to-tail orientation. Active patches can be clearly observed; each doublet of helices typically appears as a single grey bar across the bond. Scaffold loops have a more variable appearance (sometimes invisible, sometimes appearing almost as prominently as an active patch), presumably because of variable conformation or, potentially, some loop–loop binding. b, A bent-patch bond, a common error for binary-coded bonds. Here, helix bending allows a five-patch bond that would otherwise not occur. c, AFM image of a five-rectangle chain built using four orthogonal bond types. Inset shows dumbbell hairpin labels. Scale bars: 60 nm.

  3. Recognition based on complementarity of origami edge shapes.
    Figure 3: Recognition based on complementarity of origami edge shapes.

    a, Models of four origami, A, B, C and D. Orange dots mark positions of dumbbell hairpin labels. b, Test of self-interactions for each edge shape. Subscripts ‘r’ and ‘l’ denote the edge tested. AFM images show common partial self-bonds that result in aggregation. c, Tests of complementary edge shapes. AFM images show correct, full bonds. d, AFM images of the four-origami chain, A–B–C–D. e, AFM image and schematic representation of a three-patch bent-patch bond. Scale bars: 100 nm.

  4. Control of cis-trans isomerism.
    Figure 4: Control of cis-trans isomerism.

    ae, A variety of 60° corner origami whose edges specify particular binary or shape sequences. fj, Assembly of origami based in the bonds encoded by their edges. a, Scaffold path for a corner, with straight edges. Arrows indicate stacking polarity, which allows corners to form two types of antiparallel bond: trans bonds (rotated 180°) or cis bonds (rotated 120°) as indicated in f by 180° or 120° arcs. b, A corner with sequences ‘11001111’ and ‘11110011’, designed to specify all-cis bonds to create triangles (shown in g). c, A corner with sequences ‘01111110’ and ‘11100111’, designed to specify all-trans bonds to create zigzags (shown in h). d, Scaffold path, and AFM image (inset), for a corner with the ‘0110’/‘1001’ shape pair used between B and C in Fig. 3a. This shape pair specifies the formation of all-cis triangles (shown in i). e, Scaffold path for a corner with the same shape pair, but with the polarity of one edge reversed. This specifies the formation of all-trans zigzags (shown in j). ko, AFM images of origami based on the designs in ae. Parts l and o have been stretched and/or sheared to compensate for AFM drift. pt, Large-field AFM images corresponding to ko. Bar graphs indicate the fraction of bond types: cis (grey), trans (white) and disrupted (black, non-bonded or dislocated); the fractions are given as percentages in the text. The normalized cis:trans ratio (c:t such that c + t = 100) and number of origami counted (N) are given next to the bar graphs. White numbers next to zigzag clusters in m, r and t give the number of origami they contain. Scale bars in a,f,ko, 50 nm; in pt, 200 nm.

Change history

Corrected online 15 August 2011
In the version of this Article previously published, in Fig. 2, the series of 1s and 0s on the images were incorrectly placed. Also, in the penultimate paragraph of the section 'Stacking of origami rectangles', the final sentence should have referred to Fig.1e,g. These errors have now been corrected in the HTML and PDF versions of the Article.

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Author information

Affiliations

  1. Department of Bioengineering, California Institute of Technology, Pasadena, California 91125, USA

    • Sungwook Woo &
    • Paul W. K. Rothemund
  2. Department of Computer Science, California Institute of Technology, Pasadena, California 91125, USA

    • Paul W. K. Rothemund
  3. Department of Computation & Neural Systems, California Institute of Technology, Pasadena, California 91125, USA

    • Paul W. K. Rothemund

Contributions

S.W. and P.W.K.R. designed the experiments, analysed the data and co-wrote the paper. S.W. wrote the computer programs for designing bond types and performed binary code, shape code and thermodynamics experiments. P.W.K.R. performed cistrans isomerism experiments.

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The authors declare no competing financial interests.

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Supplementary information

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    Supplementary information

Zip files

  1. Supplementary information (879 KB)

    Computer program codes for designing bond types (MATLAB files)

  2. Supplementary information (758 KB)

    Installer for modified caDNAno program

  3. Supplementary information (423 KB)

    caDNAno design files for shape systems (origami A,B,C, and D) and corner origami designs

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