Development of a red-shifted fluorescence-based assay for SARS-coronavirus 3CL protease: identification of a novel class of anti-SARS agents from the tropical marine sponge Axinella corrugata
Bibliographic record
Abstract
SARS-coronavirus (SARS-CoV) encodes a main protease, 3CLpro, which plays an essential role in the viral life cycle and is currently the prime target for discovering new anti-coronavirus agents. In this article, we report our success in developing a novel red-shifted (RS) fluorescence-based assay for 3CLpro and its application for identifying small-molecule anti-SARS agents from marine organisms. We have synthesised and characterised the first generation of a red-shifted internally quenched fluorogenic substrate (RS-IQFS) for 3CLpro based on resonance energy transfer between the donor and acceptor pair CAL Fluor Red 610 and Black Hole Quencher-1 (Km and kcat values of 14 microM and 0.65 min-1). The RS-IQFS primary sequence was selected based on the results of our screening analysis of 3CLpro performed using a series of blue-shifted (BS)-IQFSs corresponding to the 3CLpro-mediated cleavage junctions of the SARS-CoV polyproteins. In contrast to BS-IQFSs, the RS-IQFS was not susceptible to fluorescence interference from coloured samples and allowed for successful screening of marine natural products and identification of a coumarin derivative, esculetin-4-carboxylic acid ethyl ester, a novel 3CLpro inhibitor (IC50=46 microM) and anti-SARS agent (EC50=112 microM; median toxic concentration>800 microM) from the tropical marine sponge Axinella corrugata.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 | 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 teacher head, 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".