Structural basis for selective remdesivir incorporation by SARS-CoV-2 RNA polymerase, and S759A resistance
Bibliographic record
Abstract
Nucleoside analogs (NAs) have been successfully used to treat viral infections. dNTP analogs are primarily DNA chain terminators, while NTP analogs, such as remdesivir, can inhibit as delayed chain terminators or when in the template strand. Determining the frequency of remdesivir triphosphate (RTP) incorporation in the presence of the competing ATP can help in understanding different modes of viral RNA-dependent RNA polymerase (RdRp) inhibition by NTP analogs. We employed enzymatic assays, mass spectrometry, and cryo-EM to show that SARS-CoV-2 RdRp preferentially incorporates RTP, outcompeting 10-fold higher ATP concentration; however, successive RTP incorporations are less favoured when ATP is present. Structures of SARS-CoV-2 RdRp in this and previous studies demonstrate resilience of remdesivir:UMP base pair to translocation, explaining the reduced preference for conjugate incorporations. Together, the RTP versus ATP incorporation is driven by their relative concentration and structural rigidity of remdesivir:UMP, ultimately limiting the number of incorporated remdesivir in a fully synthesized RNA strand. The S759A mutant confers RTP resistance, and the structures of S759A RdRp catalytic complexes reveal that altered ribose-ring conformation and repositioning of the primer 3'-end nucleotide contribute to RTP resistance. These findings enhance our understanding of non-obligate NTP analogs and provide insight into S759A resistance mechanism.
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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 | 0.000 |
| 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".