Measurement of bond vector orientations in invisible excited states of proteins
Why this work is in the frame
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Bibliographic record
Abstract
The focus of structural biology is on studies of the highly populated, ground states of biological molecules; states that are only sparsely and transiently populated are more difficult to probe because they are invisible to most structural methods. Yet, such states can play critical roles in biochemical processes such as ligand binding, enzyme catalysis, and protein folding. A description of these states in terms of structure and dynamics is, therefore, of great importance. Here, we present a method, based on relaxation dispersion NMR spectroscopy of weakly aligned molecules in a magnetic field, that can provide such a description by direct measurement of backbone amide bond vector orientations in transient, low populated states that are not observable directly. Such information, obtained through the measurement of residual dipolar couplings, has until now been restricted to proteins that produce observable spectra. The methodology is applied and validated in a study of the binding of a target peptide to an SH3 domain from the yeast protein Abp1p and subsequently used in an application to protein folding of a mutational variant of the Fyn SH3 domain where (1)H-(15)N dipolar couplings of the invisible unfolded state of the domain are obtained. The approach, which can be used to obtain orientational restraints at other sites in proteins as well, promises to significantly extend the available information necessary for providing a site-specific characterization of structural properties of transient, low populated states that have to this point remained recalcitrant to detailed analysis.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 it