Mapping the FF domain folding pathway via structures of transiently populated folding intermediates
Bibliographic record
Abstract
Despite the tremendous accomplishments of AlpaFold2/3 in predicting biomolecular structure, the protein folding problem remains unsolved in the sense that accurate atomistic models of how protein molecules fold into their native conformations from an unfolded ensemble are still elusive. Here, using chemical exchange saturation transfer (CEST) NMR experiments and a comprehensive four-state kinetic model of the folding trajectory of a 71 residue four-helix bundle FF domain from human HYPA/FBP11 we present an atomic resolution structure of a transiently formed intermediate, I2, that along with the structure of a second intermediate, I1, provides a description of the FF domain folding trajectory. By recording CEST profiles as a function of urea concentration the extent of compaction along the folding pathway is evaluated. Our data establish that unlike the partially disordered I1 state, the I2 intermediate that is also formed before the rate-limiting folding barrier is well ordered and compact like the native conformer, while retaining nonnative interactions similar to those found in I1. The slow-interconversion from I2 to F, involving changes in secondary structure and the breaking of nonnative interactions, proceeds via a compact transition-state. Interestingly, the native state of the FF1 domain from human p190-A Rho GAP resembles the I2 conformation, suggesting that well-ordered folding intermediates can be repurposed by nature in structurally related proteins to assume functional roles. It is anticipated that the strategy for elucidation of sparsely populated and transiently formed structures of intermediates along kinetic pathways described here will be of use in other studies of protein dynamics.
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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".