Understanding the mechanism of proteasome 20S core particle gating
Bibliographic record
Abstract
The 20S core particle proteasome is a molecular machine playing an important role in cellular function by degrading protein substrates that no longer are required or that have become damaged. Regulation of proteasome activity occurs, in part, through a gating mechanism controlling the sizes of pores at the top and bottom ends of the symmetric proteasome barrel and restricting access to catalytic sites sequestered in the lumen of the structure. Although atomic resolution models of both open and closed states of the proteasome have been elucidated, the mechanism by which gates exchange between these states remains to be understood. Here, this is investigated by using magnetization transfer NMR spectroscopy focusing on the 20S proteasome core particle from Thermoplasma acidophilum. We show from viscosity-dependent proteasome gating kinetics that frictional forces originating from random solvent motions are critical for driving the gating process. Notably, a small effective hydrodynamic radius (EHR; <4Å) is obtained, providing a picture in which gate exchange proceeds through many steps involving only very small segment sizes. A small EHR further suggests that the kinetics of gate interconversion will not be affected appreciably by large viscogens, such as macromolecules found in the cell, so long as they are inert. Indeed, measurements in cell lysate reveal that the gate interconversion rate decreases only slightly, demonstrating that controlled studies in vitro provide an excellent starting point for understanding regulation of 20S core particle function in complex, biologically relevant environments.
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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 | 0.001 |
| 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 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".