Discovery of a Druggable, Cryptic Pocket in SARS-CoV-2 nsp16 Using Allosteric Inhibitors
Bibliographic record
Abstract
A collaborative, open-science team undertook discovery of novel small molecule inhibitors of the SARS-CoV-2 nsp16-nsp10 2′- O -methyltransferase using a high throughput screening approach with the potential to reveal new inhibition strategies. This screen yielded compound 5a, a ligand possessing an electron-deficient double bond, as an inhibitor of SARS-CoV-2 nsp16 activity. Surprisingly, X-ray crystal structures revealed that 5a covalently binds within a previously unrecognized cryptic pocket near the S -adenosylmethionine binding cleft in a manner that prevents occupation by S -adenosylmethionine. Using a multidisciplinary approach, we examined the mechanism of binding of compound 5a to the nsp16 cryptic pocket and developed 5a derivatives that inhibited nsp16 activity and murine hepatitis virus replication in rat lung epithelial cells but proved cytotoxic to cell lines canonically used to examine SARS-CoV-2 infection. Our study reveals the druggability of this newly discovered SARS-CoV-2 nsp16 cryptic pocket, provides novel tool compounds to explore the site, and suggests a new approach for discovery of nsp16 inhibition-based pan-coronavirus therapeutics through structure-guided drug design.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".