Cellular crowding imposes global constraints on the chemistry and evolution of proteomes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In living cells, functional protein-protein interactions compete with a much larger number of nonfunctional, or promiscuous, interactions. Several cellular properties contribute to avoiding unwanted protein interactions, including regulation of gene expression, cellular compartmentalization, and high specificity and affinity of functional interactions. Here we investigate whether other mechanisms exist that shape the sequence and structure of proteins to favor their correct assembly into functional protein complexes. To examine this question, we project evolutionary and cellular abundance information onto 397, 196, and 631 proteins of known 3D structure from Escherichia coli, Saccharomyces cerevisiae, and Homo sapiens, respectively. On the basis of amino acid frequencies in interface patches versus the solvent-accessible protein surface, we define a propensity or "stickiness" scale for each of the 20 amino acids. We find that the propensity to interact in a nonspecific manner is inversely correlated with abundance. In other words, high abundance proteins have less sticky surfaces. We also find that stickiness constrains protein evolution, whereby residues in sticky surface patches are more conserved than those found in nonsticky patches. Finally, we find that the constraint imposed by stickiness on protein divergence is proportional to protein abundance, which provides mechanistic insights into the correlation between protein conservation and protein abundance. Overall, the avoidance of nonfunctional interactions significantly influences the physico-chemical and evolutionary properties of proteins. Remarkably, the effects observed are consistently larger in E. coli and S. cerevisiae than in H. sapiens, suggesting that promiscuous protein-protein interactions may be freer to accumulate in the human lineage.
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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 | 0.001 | 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 | 0.001 |
| 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