Translocation of “Rod-Coil” Polymers: Probing the Structure of Single Molecules within Nanopores
Bibliographic record
Abstract
Using simulation and analytical techniques, we demonstrate that it is possible to extract structural information about biological molecules by monitoring the dynamics as they translocate through nanopores. From Langevin dynamics simulations of polymers exhibiting discrete changes in flexibility (rod-coil polymers), distinct plateaus are observed in the progression towards complete translocation. Characterizing these dynamics via an incremental mean first passage approach, the large steps are shown to correspond to local barriers preventing the passage of the coils while the rods translocate relatively easily. Analytical replication of the results provides insight into the corrugated nature of the free energy landscape as well as the dependence of the effective barrier heights on the length of the coil sections. Narrowing the width of the pore or decreasing the charge on either the rod or the coil segments are both shown to enhance the resolution of structural details. The special case of a single rod confined within a nanopore is also studied. Here, sufficiently long flexible sections attached to either end are demonstrated to act as entropic anchors which can effectively trap the rod within the pore for an extended period of time. Both sets of results suggest new experimental approaches for the control and study of biological molecules within nanopores.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".