A survey of proteins encoded by non-synonymous single nucleotide polymorphisms reveals a significant fraction with altered stability and activity
Bibliographic record
Abstract
On average, each human gene has approximately four SNPs (single nucleotide polymorphisms) in the coding region, half of which are nsSNPs (non-synonymous SNPs) or missense SNPs. Current attention is focused on those that are known to perturb function and are strongly linked to disease. However, the vast majority of SNPs have not been investigated for the possibility of causing disease. We set out to assess the fraction of nsSNPs that encode proteins that have altered stability and activity, for this class of variants would be candidates to perturb cellular function. We tested the thermostability and, where possible, the catalytic activity for the most common variant (wild-type) and minor variants (total of 46 SNPs) for 16 human enzymes for which the three-dimensional structures were known. There were significant differences in the stability of almost half of the variants (48%) compared with their wild-type counterparts. The catalytic efficiency of approx. 14 variants was significantly altered, including several variants of human PKM2 (pyruvate kinase muscle 2). Two PKM2 variants, S437Y and E28K, also exhibited changes in their allosteric regulation compared with the wild-type enzyme. The high proportion of nsSNPs that affect protein stability and function, albeit subtly, underscores the need for experimental analysis of the diverse human proteome.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".