The role of protein complexes in human genetic disease
Bibliographic record
Abstract
Many human genetic disorders are caused by mutations in protein-coding regions of DNA. Taking protein structure into account has therefore provided key insight into the molecular mechanisms underlying human genetic disease. Although most studies have focused on the intramolecular effects of mutations, the critical role of the assembly of proteins into complexes is being increasingly recognized. Here, we review multiple ways in which consideration of protein complexes can help us to understand and explain the effects of pathogenic mutations. First, we discuss disorders caused by mutations that perturb intersubunit interactions in homomeric and heteromeric complexes. Second, we address how protein complex assembly can facilitate a dominant-negative mechanism, whereby mutated subunits can disrupt the activity of wild-type protein. Third, we show how mutations that change protein expression levels can lead to damaging stoichiometric imbalances. Finally, we review how mutations affecting different subunits of the same heteromeric complex often cause similar diseases, whereas mutations in different interfaces of the same subunit can cause distinct phenotypes.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".