Bibliographic record
Abstract
Abstract As the only commonly occurring imino acid in proteins, proline has been found to play unique structural and dynamic roles in guiding protein folding, fibre formation and protein–protein interactions. The cyclic pyrrolidine side‐chain fixes the backbone dihedral ϕ angle and renders proline unable to act as a hydrogen bond donor. These properties are reflected in its preference for protein secondary structure elements such as turns and polyproline II helices, and its generally destabilizing effect on α helix and β‐strand conformation. The ability of proline to undergocis‐transisomerization is important in protein folding and forms the basis of molecular switches that help to control cellular growth and regulation. Proline and its posttranslationally modified analogue, hydroxyproline, are additionally the major components of collagens, proteins that are the major fibrous proteins in animals and account for approximately 30% of total human body protein. Key Concepts: The structural and dynamic properties imparted to proteins by the amino acid proline arise from the unique cyclic structure of its side‐chain. Interconversion of proline fromcistotransconformation, which can be facilitated by peptidylprolyl isomerases, is a rate‐limiting step in protein folding and can act as a molecular switch in the regulation of cellular growth and signalling. Proline residues facilitate the formation of protein secondary structure elements such as turns and the polyproline II helix, but typically disfavour α helix and β‐strand conformations. Proline and its posttranslationally modified analogue hydroxyproline are key components of the structural protein collagen. Regions of water‐soluble proteins rich in proline residues are often sites of protein–protein interaction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".