Mutational analysis of the active centre of coronavirus 3C-like proteases.
Bibliographic record
Abstract
Formation of the coronavirus replication-transcription complex involves the synthesis of large polyprotein precursors that are extensively processed by virus-encoded cysteine proteases. In this study, the coding sequence of the feline infectious peritonitis virus (FIPV) main protease, 3CL(pro), was determined. Comparative sequence analyses revealed that FIPV 3CL(pro) and other coronavirus main proteases are related most closely to the 3C-like proteases of potyviruses. The predicted active centre of the coronavirus enzymes has accepted unique replacements that were probed by extensive mutational analysis. The wild-type FIPV 3CL(pro) domain and 25 mutants were expressed in Escherichia coli and tested for proteolytic activity in a peptide-based assay. The data strongly suggest that, first, the FIPV 3CL(pro) catalytic system employs His(41) and Cys(144) as the principal catalytic residues. Second, the amino acids Tyr(160) and His(162), which are part of the conserved sequence signature Tyr(160)-Met(161)-His(162) and are believed to be involved in substrate recognition, were found to be indispensable for proteolytic activity. Third, replacements of Gly(83) and Asn(64), which were candidates to occupy the position spatially equivalent to that of the catalytic Asp residue of chymotrypsin-like proteases, resulted in proteolytically active proteins. Surprisingly, some of the Asn(64) mutants even exhibited strongly increased activities. Similar results were obtained for human coronavirus (HCoV) 3CL(pro) mutants in which the equivalent Asn residue (HCoV 3CL(pro) Asn(64)) was substituted. These data lead us to conclude that both the catalytic systems and substrate-binding pockets of coronavirus main proteases differ from those of other RNA virus 3C and 3C-like proteases.
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 | 0.000 | 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".