Label-free optical observation of disordered-to-ordered transitions in single intrinsically disordered proteins
Bibliographic record
Abstract
Intrinsically disordered proteins (IDPs) and structured proteins with intrinsically disordered regions (IDRs) lack a definitive tertiary structure and contribute to the onset of diseases such as Alzheimer's and cancer. To date, experimental observation of single, label-free IDPs/IDRs poses a significant challenge due to their structural heterogeneity, limiting ensemble techniques from fully capturing their properties, whilst single-molecule measurements require site-specific modifications or non-physiological conditions, perturbing their native biophysics. Here, we demonstrate the first experimental observation of unmodified IDP/IDR conformational dynamics at the single-molecule level, achieved by optical trapping and investigation of individual IDPs/IDRs using nanoaperture optical tweezers. Our results reveal that IDPs/IDRs exhibit significantly larger conformational variations compared to globular proteins of similar size. We demonstrate that phosphorylation of native tau-441 by glycogen synthase kinase 3-beta (GSK3β-tau) induces compaction and reduced conformational dynamics. We further observed a disorder-to-order transition during the binding of the N-terminal region of the Src-associated protein in mitosis of 68 kDa (Sam68) to G8.5 RNA. These findings present nanoaperture optical tweezers as a powerful approach to advance our understanding of IDPs/IDRs and further decode their roles in associated diseases.
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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) | 0.001 | 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".