Degradation of Mutant Proteins, Underlying "Loss of Function" Phenotypes, Plays a Major Role in Genetic Disease
Bibliographic record
Abstract
Many Mendelian monogenic disorders are caused by loss of the function of a single protein. This can result from rapid degradation of the mutant protein by cellular proteases, which reduces the steady-state concentration of the protein within the cell. The susceptibility of a protein to such proteolytic breakdown depends upon its kinetics of monomer folding and oligomer assembly and upon the intrinsic (thermodynamic) stability of its functional native-state conformation. Other cellular proteins, notably molecular chaperones, promote correct protein folding and assembly and thus provide some protection against degradation. An accumulation of recent evidence indicates that premature or accelerated degradation of mutant proteins, provoked by aberrations in their conformation, occurs in various subcellular compartments and represents a significant and prevalent pathogenic mechanism underlying genetic diseases. Inter-individual variability in proteolytic and folding systems can in part explain why "simple monogenic diseases" often display inconsistent genotype-phenotype correlations which show these disorders to be in reality quite complex. Protein folding and degradation may also be modulated artificially using exogenous small molecules. The identification or design of compounds which can interact specifically with particular target proteins, and which in so doing can exert beneficial effects on protein folding, assembly and/or stability, is beginning to open up a new and remarkably promising avenue for the treatment of diverse genetic disorders.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.006 |
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".