Characterization of the R263K Mutation in HIV-1 Integrase That Confers Low-Level Resistance to the Second-Generation Integrase Strand Transfer Inhibitor Dolutegravir
Bibliographic record
Abstract
Integrase (IN) strand transfer inhibitors (INSTIs) have been developed to inhibit the ability of HIV-1 integrase to irreversibly link the reverse-transcribed viral DNA to the host genome. INSTIs have proven their high efficiency in inhibiting viral replication in vitro and in patients. However, first-generation INSTIs have only a modest genetic barrier to resistance, allowing the virus to escape these powerful drugs through several resistance pathways. Second-generation INSTIs, such as dolutegravir (DTG, S/GSK1349572), have been reported to have a higher resistance barrier, and no novel drug resistance mutation has yet been described for this drug. Therefore, we performed in vitro selection experiments with DTG using viruses of subtypes B, C, and A/G and showed that the most common mutation to emerge was R263K. Further analysis by site-directed mutagenesis showed that R263K does confer low-level resistance to DTG and decreased integration in cell culture without altering reverse transcription. Biochemical cell-free assays performed with purified IN enzyme containing R263K confirmed the absence of major resistance against DTG and showed a slight decrease in 3' processing and strand transfer activities compared to the wild type. Structural modeling suggested and in vitro IN-DNA binding assays show that the R263K mutation affects IN-DNA interactions.
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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".