Backbone Dynamics of TEM-1 Determined by NMR: Evidence for a Highly Ordered Protein
Bibliographic record
Abstract
Backbone dynamics of TEM-1 beta-lactamase (263 amino acids, 28.9 kDa) were studied by 15N nuclear magnetic resonance relaxation at 11.7, 14.1, and 18.8 T. The high quality of the spectra allowed us to measure the longitudinal relaxation rate (R1), the transverse relaxation rate (R2), and the {1H}-15N NOE for up to 227 of the 250 potentially observable backbone amide groups. The model-free formalism was used to determine internal motional parameters using an axially anisotropic model. TEM-1 exhibits a small prolate axial anisotropy (D(parallel)/D(perpendicular) = 1.23 +/- 0.01) and a global correlation time (tau(m)) of 12.41 +/- 0.01 ns. The unusually high average generalized order parameter (S2) of 0.90 +/- 0.02 indicates that TEM-1 is one of the most ordered proteins studied by liquid-state NMR to date. Although the omega-loop has a high degree of order in the picosecond-to-nanosecond time scale (mean S2 value of 0.90 +/- 0.02), we observed the presence of microsecond-to-millisecond time scale motions for this loop, as for the vicinity of the active site. These motions could be relevant for the catalytic function of TEM-1. Amide exchange experiments were also performed, and several amide groups were not exchanged after 12 days, an indication that global motions in TEM-1 are also very limited. Although detailed dynamics characterization by NMR cannot be readily applied to TEM-1 in the presence of relevant substrates, the unusual picosecond-to-nanosecond dynamics behavior of TEM-1 presented here will be essential to the validation and improvement of future molecular dynamics simulations of TEM-1 in the presence of functionally relevant substrates.
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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) | 0.000 | 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".