Atomic force microscopy reveals parallel mechanical unfolding pathways of T4 lysozyme: Evidence for a kinetic partitioning mechanism
Bibliographic record
Abstract
Kinetic partitioning is predicted to be a general mechanism for proteins to fold into their well defined native three-dimensional structure from unfolded states following multiple folding pathways. However, experimental evidence supporting this mechanism is still limited. By using single-molecule atomic force microscopy, here we report experimental evidence supporting the kinetic partitioning mechanism for mechanical unfolding of T4 lysozyme, a small protein composed of two subdomains. We observed that on stretching from its N and C termini, T4 lysozyme unfolds by multiple distinct unfolding pathways: the majority of T4 lysozymes unfold in an all-or-none fashion by overcoming a dominant unfolding kinetic barrier; and a small fraction of T4 lysozymes unfold in three-state fashion involving unfolding intermediate states. The three-state unfolding pathways do not follow well defined routes, instead they display variability and diversity in individual unfolding pathways. The unfolding intermediate states are local energy minima along the mechanical unfolding pathways and are likely to result from the residual structures present in the two subdomains after crossing the main unfolding barrier. These results provide direct evidence for the kinetic partitioning of the mechanical unfolding pathways of T4 lysozyme, and the complex unfolding behaviors reflect the stochastic nature of kinetic barrier rupture in mechanical unfolding processes. Our results demonstrate that single-molecule atomic force microscopy is an ideal tool to investigate the folding/unfolding dynamics of complex multimodule proteins that are otherwise difficult to study using traditional methods.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".