SARS-CoV-2 NSP13; A Target Enabling Package
Bibliographic record
Abstract
To contribute towards the development of novel anti-viral therapeutics targeting the current and future emerging coronavirus threats, the Gileadi lab at the University of Oxford, together with the XChem team at Diamond Light Source, have teamed up to perform a crystallographic fragment screen against SARS-CoV-2 NSP13 helicase. NSP13 is believed to act in concert with the replication-transcription complex (NSP7/NSP82/NSP12), possibly being involved in either disrupting downstream RNA secondary structures or template switching, and plays an essential role in the life cycle of SARS-CoV-2. This TEP includes expression clones and methods for producing the full length NSP13, and fluorescence-based activity assays suitable for compound screening. We provide a crystallisation system that produces reproducible crystals that diffract to high resolution, and have performed a crystallographic fragment screen revealing 63 fragment hits across 51 datasets. The fragment hits include several hits in pockets predicted to be of functional importance, including the nucleotide and nucleic acid binding sites, opening the way to development of novel antiviral agents.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.024 |
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".