Rapid evolution in conformational space: A study of loop regions in a ubiquitous GTP binding domain
Why this work is in the frame
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Bibliographic record
Abstract
The rapidly evolving subsets of a protein are often evident in multiple sequence alignments as poorly defined, gap-containing regions. We investigated the 3D context of these regions observed in 28 protein structures containing a GTP-binding domain assumed to be homologous to the transforming factor p21-RAS. The phylogenetic depth of this data set is such that it is possible to observe lineages sharing a common protein core that diverged early in the eukaryotic cell history. The sequence variability among these homolog proteins is directly linked to the structural variability of surface loops. We demonstrate that these regions are self-contained and thus mostly free of the evolutionary constraints imposed by the conserved core of the domain. These intraloop interactions have the property to create stem-like structures. Interestingly, these stem-like structures can be observed in loops of varying size, up to the size of small protein domains. We propose a model under which the diversity of protein topologies observed in these loops can be the product of a stochastic sampling of sequence and conformational space in a near-neutral fashion, while the proximity of the functional features of the domain core allows novel beneficial traits to be fixed. Our comparative observations, limited here to the proteins containing the RAS-like GTP-binding domain, suggest that a stochastic process of insertion/deletion analogous to "budding" of loops is a likely mechanism of structural innovation. Such a framework could be experimentally exploited to investigate the folding of increasingly complex model inserts.
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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 | 0.001 |
| 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