Thermodynamic Basis for Engineering High-Affinity, High-Specificity Binding-Induced DNA Clamp Nanoswitches
Bibliographic record
Abstract
Naturally occurring chemoreceptors almost invariably employ structure-switching mechanisms, an observation that has inspired the use of biomolecular switches in a wide range of artificial technologies in the areas of diagnostics, imaging, and synthetic biology. In one mechanism for generating such behavior, clamp-based switching, binding occurs via the clamplike embrace of two recognition elements onto a single target molecule. In addition to coupling recognition with a large conformational change, this mechanism offers a second advantage: it improves both affinity and specificity simultaneously. To explore the physics of such switches we have dissected here the thermodynamics of a clamp-switch that recognizes a target DNA sequence through both Watson-Crick base pairing and triplex-forming Hoogsteen interactions. When compared to the equivalent linear DNA probe (which relies solely on Watson-Crick interactions), the extra Hoogsteen interactions in the DNA clamp-switch increase the probe's affinity for its target by ∼0.29 ± 0.02 kcal/mol/base. The Hoogsteen interactions of the clamp-switch likewise provide an additional specificity check that increases the discrimination efficiency toward a single-base mismatch by 1.2 ± 0.2 kcal/mol. This, in turn, leads to a 10-fold improvement in the width of the "specificity window" of this probe relative to that of the equivalent linear probe. Given these attributes, clamp-switches should be of utility not only for sensing applications but also, in the specific field of DNA nanotechnology, for applications calling for a better control over the building of nanostructures and nanomachines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".