journal article·2021-02Open access

Multivalency Pattern Recognition to Sort Colloidal Assemblies

Sebastian Loescher, Andreas Walther

Small· Volume 17· Issue 5

Abstract

Abstract Multivalent interaction is an important principle for self‐assembly and has been widely used to assemble colloids. However, surface binding partners are statistically distributed, which falls short of the interaction possibilities arising from geometrically controlled multivalency patterns as seen in viruses. Herein, the precision provided by 3D DNA origami is exploited to introduce multivalency pattern recognition via designing geometrically precise interaction patterns at patches of patchy nanocylinders. This gives rise to self‐sorting of colloidal assemblies despite having the same type and number of supramolecular binding motifs—solely based on the pattern located on a 20 × 20 nm 2 cross‐section. The degree of sorting can be modulated by the geometric overlap of patterns and homo; mixed and alternating supracolloidal polymerizations are demonstrated. Multivalency patterns are able to provide an additional information layer to organize soft matter, important towards engineering of biological responses and functional materials design.
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Research context

OpenAlex topics: Advanced biosensing and bioanalysis techniques · Polymer Surface Interaction Studies · Bacteriophages and microbial interactions

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Institute for Macromolecular Chemistry University of Freiburg Stefan‐Meier‐Strasse 31 79104 Freiburg Germany

Freiburg Materials Research Center University of Freiburg Stefan‐Meier‐Strasse 21 79104 Freiburg Germany

Freiburg Center for Interactive Materials and Bioinspired Technologies (FIT) University of Freiburg Georges‐Köhler‐Allee 105 79110 Freiburg Germany

Funding

European Research Council

References (40)

Show source-provided references
1. 10.1126/science.107082110.1126/science.1070821 ↗
2. 10.1002/(SICI)1521-3773(19981102)37:20<2754::AID-ANIE2754>3.0.CO;2-310.1002/(SICI)1521-3773(19981102)37:20<2754::AID-ANIE2754>3.0.CO;2-3 ↗
3. 10.1021/ja410918a10.1021/ja410918a ↗
4. 10.1021/jacs.7b0996710.1021/jacs.7b09967 ↗
5. 10.1038/s41565-020-0660-210.1038/s41565-020-0660-2 ↗
6. 10.1038/s41565-020-0719-010.1038/s41565-020-0719-0 ↗
7. 10.1038/nchem.107010.1038/nchem.1070 ↗
8. 10.1039/b413971b10.1039/b413971b ↗
9. 10.1560/AF3P-K2A6-MDCK-167810.1560/AF3P-K2A6-MDCK-1678 ↗
10. 10.1126/science.121049310.1126/science.1210493 ↗
11. 10.1021/la503187210.1021/la5031872 ↗
12. 10.1021/acsnano.0c0016410.1021/acsnano.0c00164 ↗
13. 10.1021/acs.accounts.7b0037010.1021/acs.accounts.7b00370 ↗
14. 10.1039/C9CS00804G10.1039/C9CS00804G ↗
15. 10.1002/adma.20110020310.1002/adma.201100203 ↗
16. 10.1126/science.117425110.1126/science.1174251 ↗
17. 10.1038/nature0801610.1038/nature08016 ↗
18. 10.1002/anie.20180170010.1002/anie.201801700 ↗
19. 10.1021/jacs.5b0214410.1021/jacs.5b02144 ↗
20. 10.1038/ncomms770510.1038/ncomms7705 ↗
21. 10.1021/jacs.7b0989210.1021/jacs.7b09892 ↗
22. 10.1021/acssynbio.9b0049410.1021/acssynbio.9b00494 ↗
23. 10.1038/ncomms394810.1038/ncomms3948 ↗
24. 10.1038/nmat403110.1038/nmat4031 ↗
25. 10.1039/c3nr06006c10.1039/c3nr06006c ↗
26. 10.1038/ncomms1061910.1038/ncomms10619 ↗
27. 10.1126/sciadv.160097410.1126/sciadv.1600974 ↗
28. 10.1126/science.aah597410.1126/science.aah5974 ↗
29. 10.1021/acsnano.6b0709710.1021/acsnano.6b07097 ↗
30. 10.1126/science.125094410.1126/science.1250944 ↗
31. 10.1021/acs.nanolett.6b0414610.1021/acs.nanolett.6b04146 ↗
32. 10.1038/nature2465510.1038/nature24655 ↗
33. 10.1126/science.aaa537210.1126/science.aaa5372 ↗
34. 10.1038/nature2465110.1038/nature24651 ↗
35. 10.1021/acsnano.7b0601210.1021/acsnano.7b06012 ↗
36. 10.1002/anie.20191179510.1002/anie.201911795 ↗
37. 10.1021/jacs.9b1115810.1021/jacs.9b11158 ↗
38. 10.1021/acsnano.9b0425110.1021/acsnano.9b04251 ↗
39. 10.1021/nl503441v10.1021/nl503441v ↗
40. 10.1038/s41563-018-0231-110.1038/s41563-018-0231-1 ↗