DNA-Encoded Protein Janus Nanoparticles
Bibliographic record
Abstract
Asymmetric functionality and directional interactions, which are characteristic of noncentrosymmetric particles, such as Janus particles, present an opportunity to encode particles with properties, but also a great synthetic challenge. Here, we exploit the chemical anisotropy of proteins, and the versatile chemistry of DNA to synthesize a protein-based Janus nanoparticle comprised of two proteins encoded with sequence-specific nucleic acid domains, tethered together by an interprotein "DNA bond". We use these novel nanoparticles to realize a new class of three-dimensional superlattice, only possible when two sides of the particle are modified with orthogonal oligonucleotide sequences. The low symmetry, intrinsic to Janus particles, enables the realization of unprecedented multicomponent nanoparticle superlattices with unique, hexagonal layered architectures. In addition, the interprotein "DNA bond" can be modulated to selectively expand the lattice in a single direction. The results presented herein not only emphasize the power of rationally designing nanoscale building blocks to create highly engineered colloidal crystals, but also establish a precedent for applications of multidomain DNA-encoded nanoparticles, especially in the field of colloidal crystallization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".