Bibliographic record
Abstract
Fungi and viruses encode a variety of peptidases having a plethora of functions. Many fungal peptidases are extracellular and are likely used to degrade proteins in their environment. Viral peptidases are processing enzymes, intimately involved in the virus infectious cycle. The viral RNA genome is translated by the host-cell machinery into a large polyprotein that is cleaved by the viral peptidases into mature capsid proteins, non-structural proteins and enzymes. I review the structure and catalytic mechanism of scytalidoglutamic peptidase isolated from the wood-destroying fungus Scytalidium lignicolum. This enzyme has a unique beta-sandwich fold and a novel catalytic mechanism based on a glutamate, a glutamine and a nucleophilic water molecule. Hepatitis A virus (HAV) 3C peptidase was the first structure identified for a viral 3C enzyme that exhibited the three-dimensional fold of the chymotrypsin family of serine peptidases but had a cysteine sulfur atom instead of the serine oxygen as the nucleophile. The structure of HAV 3C was unusual in that the Asp residue expected as the third member of the catalytic triad did not interact with the general base His. The present structure is of a beta-lactone-inhibited version of HAV 3C that has a restored catalytic triad.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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".