Missense mutations in transmembrane domains of proteins: Phenotypic propensity of polar residues for human disease
Why this work is in the frame
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Bibliographic record
Abstract
Previous experiments on the cystic fibrosis transmembrane conductance regulator suggested that non-native polar residues within membrane domains can compromise protein structure/function. However, depending on context, replacement of a native residue by a non-native residue can result either in genetic disease or in benign effects (e.g., polymorphisms). Knowledge of missense mutations that frequently cause protein malfunction and subsequent disease can accordingly reveal information as to the impact of these residues in local protein environments. We exploited this concept by performing a statistical comparison of disease-causing mutations in protein membrane-spanning domains versus soluble domains. Using the Human Gene Mutation Database of 240 proteins (including 80 membrane proteins) associated with human disease, we compared the relative phenotypic propensity to cause disease of the 20 naturally occurring amino acids when removed from-or inserted into-native protein sequences. We found that in transmembrane domains (TMDs), mutations involving polar residues, and ionizable residues in particular (notably arginine), are more often associated with protein malfunction than soluble proteins. To further test the hypothesis that interhelical cross-links formed by membrane-embedded polar residues stabilize TMDs, we compared the occurrence of such residues in the TMDs of mesophilic and thermophilic prokaryotes. Results showed a significantly higher proportion of ionizable residues in thermophilic organisms, reinforcing the notion that membrane-embedded electrostatic interactions play critical roles in TMD stability.
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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 | 0.000 | 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) | 0.000 | 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