Mutations in the SARS-CoV-2 RNA-dependent RNA polymerase confer resistance to remdesivir by distinct mechanisms
Bibliographic record
Abstract
The nucleoside analog remdesivir (RDV) is a Food and Drug Administration–approved antiviral for treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Thus, it is critical to understand factors that promote or prevent RDV resistance. We passaged SARS-CoV-2 in the presence of increasing concentrations of GS-441524, the parent nucleoside of RDV. After 13 passages, we isolated three viral lineages with phenotypic resistance as defined by increases in half-maximal effective concentration from 2.7- to 10.4-fold. Sequence analysis identified nonsynonymous mutations in nonstructural protein 12 RNA-dependent RNA polymerase ( nsp12 -RdRp): V166A, N198S, S759A, V792I, and C799F/R. Two lineages encoded the S759A substitution at the RdRp Ser 759 -Asp-Asp active motif. In one lineage, the V792I substitution emerged first and then combined with S759A. Introduction of S759A and V792I substitutions at homologous nsp12 positions in murine hepatitis virus demonstrated transferability across betacoronaviruses; introduction of these substitutions resulted in up to 38-fold RDV resistance and a replication defect. Biochemical analysis of SARS-CoV-2 RdRp encoding S759A demonstrated a roughly 10-fold decreased preference for RDV-triphosphate (RDV-TP) as a substrate, whereas nsp12 -V792I diminished the uridine triphosphate concentration needed to overcome template-dependent inhibition associated with RDV. The in vitro–selected substitutions identified in this study were rare or not detected in the greater than 6 million publicly available nsp12 -RdRp consensus sequences in the absence of RDV selection. The results define genetic and biochemical pathways to RDV resistance and emphasize the need for additional studies to define the potential for emergence of these or other RDV resistance mutations in clinical settings.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".