The Pattern of Amino Acid Replacements in α/β-Barrels
Bibliographic record
Abstract
The determinants of site-to-site variability in the rate of amino acid replacement in alpha/beta-barrel enzyme structures are investigated. Of 125 available alpha/beta-barrel structures, only 25 meet a variety of phylogenetic and statistical criteria necessary to ensure sufficient data for reliable analysis. These 25 enzyme structures (from a wide variety of taxa with diverse lifestyles in diverse habitats) differ greatly in size, number, and topology of domains in addition to the alpha/beta-barrel, quaternary structure, metabolic role, reaction catalyzed, presence of prosthetic groups, regulatory mechanisms, use of cofactors, and catalytic mechanisms. Yet, with the exception of ribulose-1,5-bisphosphate carboxylase, all structures have similar frequency distributions of amino acid replacement rates. Hence, site-specific variability in rates of evolution is largely independent of differences in biology, biochemistry, and molecular structure. A correlation between site-specific rate variation and (1) distance from the active site, (2) solvent accessibility, and (3) treating glycines in unusual main-chain conformations as a separate class, explains approximately half the causal variation. Secondary structure exerts little influence on the pattern and distribution of replacements. Additional domains and subunits, side-chain hydrogen bonds, unusual side-chain rotamers, nonplanar peptide bonds, strained main-chain conformations, and buried hydrophilic-charged residues contribute little to variability among sites because they are rare. Nonlinear models do not improve the fits. In several enzymes, deviations from the typical pattern of replacements suggest the possible action of natural selection. A statistical analysis shows that, in all cases, much of the remaining unexplained variation is not attributable to chance and that other, as yet unidentified, causal relations must exist.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".