Selective Loss of Cysteine Residues and Disulphide Bonds in a Potato Proteinase Inhibitor II Family
Bibliographic record
Abstract
Disulphide bonds between cysteine residues in proteins play a key role in protein folding, stability, and function. Loss of a disulphide bond is often associated with functional differentiation of the protein. The evolution of disulphide bonds is still actively debated; analysis of naturally occurring variants can promote understanding of the protein evolutionary process. One of the disulphide bond-containing protein families is the potato proteinase inhibitor II (PI-II, or Pin2, for short) superfamily, which is found in most solanaceous plants and participates in plant development, stress response, and defence. Each PI-II domain contains eight cysteine residues (8C), and two similar PI-II domains form a functional protein that has eight disulphide bonds and two non-identical reaction centres. It is still unclear which patterns and processes affect cysteine residue loss in PI-II. Through cDNA sequencing and data mining, we found six natural variants missing cysteine residues involved in one or two disulphide bonds at the first reaction centre. We named these variants Pi7C and Pi6C for the proteins missing one or two pairs of cysteine residues, respectively. This PI-II-7C/6C family was found exclusively in potato. The missing cysteine residues were in bonding pairs but distant from one another at the nucleotide/protein sequence level. The non-synonymous/synonymous substitution (Ka/Ks) ratio analysis suggested a positive evolutionary gene selection for Pi6C and various Pi7C. The selective deletion of the first reaction centre cysteine residues that are structure-level-paired but sequence-level-distant in PI-II illustrates the flexibility of PI-II domains and suggests the functionality of their transient gene versions during evolution.
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 | 0.001 |
| 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 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".