Preparation of Glycerol Facilitator for Protein Structure and Folding Studies in Solution
Bibliographic record
Abstract
Progress in the elucidation of protein folding pathways is contributing to a deeper understanding of the information encoded in genomes (). However, the study of membrane protein folding lags behind similar studies of water-soluble proteins (). Some of the impediments include poor expression of membrane proteins possibly caused by their misfolding, aggregation, improper transport, and insertion into membranes, or their toxicity when overexpressed (). In vitro, poor solubility properties lead to difficulties in purification, refolding, crystallization, and nuclear magnetic resonance analysis. The Escherichia coli glycerol facilitator (GF) is an attractive model for studying membrane protein folding (, , ). E. coli is by far the most successful and versatile vehicle for the production of recombinant proteins and by expressing a native bacterial protein in E. coli difficulties associated with the expression of foreign genes, such as rare codon usage () and posttranslational modifications, are avoided. High levels of GF protein are unlikely to be toxic to the cell; the facilitator is highly specific for glycerol transport (,) and glycerol can be omitted from the growth medium. Uncontrolled water transport might be problematic owing to osmotic pressure effects, however, the facilitator does not transport water nearly as efficiently as the aquaporins, and aquaporin-1 is naturally highly expressed in red blood cells (,). In addition, it seems unlikely that high levels of intracellular glycerol would be toxic to E. coli and in indeed we find maximum expression using the glycerol-rich medium Terrific Broth (TB) ().
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".