Design and Thermodynamics Principles to Program the Cooperativity of Molecular Assemblies
Bibliographic record
Abstract
Abstract Most functional nanosystems in living organisms are constructed using multimeric assemblies that provide multiple advantages over their monomeric counterparts such as cooperative or anti‐cooperative responses, integration of multiple signals and self‐regulation. Inspired by these natural nanosystems, chemists have been synthesizing self‐assembled supramolecular systems over the last 50 years with increasing complexity with applications ranging from biosensing, drug delivery, synthetic biology, and system chemistry. Although many advances have been made concerning the design principles of novel molecular architectures and chemistries, little is still known, however, about how to program their dynamic of assembly so that they can assemble at the required concentration and with the right sensitivity. Here, we used synthetic DNA assemblies and double‐mutant cycle analysis to explore the thermodynamic basis to program the cooperativity of molecular assemblies. The results presented here exemplify how programmable molecular assemblies can be efficiently built by fusing interacting domains and optimizing their compaction. They may also provide the rational basis for understanding the thermodynamic and mechanistic principles driving the evolution of multimeric biological complexes.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".