The Role of Protein Thermodynamics and Primary Structure in Fibrillogenesis of Variable Domains from Immunoglobulin Light Chains
Bibliographic record
Abstract
Immunoglobulin light-chain amyloidosis is a protein aggregation disease that leads to proteinaceous deposits in a variety of organs in the body and, if untreated, ultimately results in death. The mechanisms by which light-chain aggregation occurs are not well understood. Here we have used solution NMR spectroscopy and biophysical studies to probe immunoglobulin variable domain λV6-57 V L aggregation, a process that appears to drive the degenerative phenotypes in amyloidosis patients. Our results establish that aggregation proceeds via the unfolded state. We identify, through NMR relaxation experiments recorded on the unfolded domain ensemble, a series of hotspots that could be involved in the initial phases of aggregate formation. Mutational analysis of these hotspots reveals that the region that includes K16-R24 is particularly aggregation prone. Notably, this region includes the site of the R24G substitution, a mutation that is found in variable domains of λ light-chain deposits in 25% of patients. The R24G λV6-57 V L domain aggregates more rapidly than would be expected on the basis of thermodynamic stability alone, while substitutions in many of the aggregation-prone regions significantly slow down fibril formation.
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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 | 0.001 | 0.002 |
| 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".