Resonance assignments and secondary structure analysis of dynein light chain 8 by magic-angle spinning NMR spectroscopy
Bibliographic record
Abstract
Dynein light chain LC8 is the smallest subunit of the dynein motor complex and has been shown to play important roles in both dynein dependent and dynein independent physiological functions via its interaction with a number of its binding partners. It has also been linked to pathogenesis including roles in viral infections and tumorigenesis. Structural information for LC8-target proteins is critical to understanding the underlying function of LC8 in these complexes. However, some LC8-target interactions are not amenable for structural characterization by conventional structural biology techniques due to their large size, low solubility and crystallization difficulties. Here, we report magic angle spinning (MAS) NMR studies of the homodimeric apo-LC8 protein as a first effort in addressing more complex, multi-partner LC8-based protein assemblies. We have established site-specific backbone and side chain resonance assignments for the majority of the residues of LC8, and show TALOS+ predicted torsion angles ϕ and ψ in close agreement with most residues in the published LC8 crystal structure. Data obtained through these studies will provide the first step toward using MAS NMR to examine the LC8 structure, which will eventually be used to investigate protein-protein interactions in larger systems, which cannot be determined by conventional structural studies.
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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".