A High-Throughput RNA Displacement Assay for Screening SARS-CoV-2 nsp10-nsp16 Complex toward Developing Therapeutics for COVID-19
Bibliographic record
Abstract
SARS-CoV-2, the coronavirus that causes COVID-19, evades the human immune system by capping its RNA. This process protects the viral RNA and is essential for its replication. Multiple viral proteins are involved in this RNA capping process, including the nonstructural protein 16 (nsp16), which is an S -adenosyl-l-methionine (SAM)-dependent 2′- O -methyltransferase. Nsp16 is significantly active when in complex with another nonstructural protein, nsp10, which plays a key role in its stability and activity. Here we report the development of a fluorescence polarization (FP)-based RNA displacement assay for nsp10-nsp16 complex in a 384-well format with a Z′ factor of 0.6, suitable for high-throughput screening. In this process, we purified the nsp10-nsp16 complex to higher than 95% purity and confirmed its binding to the methyl donor SAM, the product of the reaction, S -adenosyl-l-homocysteine (SAH), and a common methyltransferase inhibitor, sinefungin, using isothermal titration calorimetry (ITC). The assay was further validated by screening a library of 1124 drug-like compounds. This assay provides a cost-effective high-throughput method for screening the nsp10-nsp16 complex for RNA competitive inhibitors toward developing COVID-19 therapeutics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".