Real-Time Monitoring of the Interactions of Two-Stranded <i>de Novo</i> Designed Coiled-Coils: Effect of Chain Length on the Kinetic and Thermodynamic Constants of Binding
Bibliographic record
Abstract
We have de novo designed a heterodimeric coiled-coil formed by two peptides as a capture/delivery system that can be used in applications such as affinity tag purification, immobilization in biosensors, etc. The two strands are designated as K coil (KVSALKE heptad sequence) and E coil (EVSALEK heptad sequence), where positively charged or negatively charged residues occupy positions e and g of the heptad repeat. In this study, for each E coil or K coil, three peptides were synthesized with lengths varying from three to five heptads. The effect of the chain length of each partner upon the kinetic and thermodynamic constants of interaction were determined using a surface plasmon resonance-based biosensor. Global fitting of the interactions revealed that the E5 coil interacted with the K5 coil according to a simple binding model. All the other interactions involving shorter coils were better described by a more complex kinetic model involving a rate-limiting reorganization of the coiled-coil structure. The affinities of these de novo designed coiled-coil interactions were found to range from 60 pM (E5/K5) to 30 microM (E3/K3). From these K(d) values, we were able to determine the free energy contribution of each heptad, depending on its relative position within the coiled-coils. We found that the free energy contribution of a heptad occupying a central position was 3-fold higher than that of a heptad at either end of the coiled-coil. The wide range of stabilities and affinities for the E/K coil system provides considerable flexibility for protein engineering and biotechnological applications.
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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".