Differential impact of the HIV-1 non-nucleoside reverse transcriptase inhibitor mutations K103N and M230L on viral replication and enzyme function
Bibliographic record
Abstract
OBJECTIVES: We wished to study the resistance profile of etravirine, a novel non-nucleoside reverse transcriptase inhibitor (NNRTI) active against common human immunodeficiency virus type-1 (HIV-1) drug-resistant strains. METHODS: We compared the effects of K103N, the most prevalent NNRTI resistance mutation, and M230L on enzyme function, virus replication and extent of biochemical inhibition by etravirine, efavirenz and nevirapine. RESULTS: Growth kinetics analyses in cord blood mononuclear cells (CBMCs) demonstrated that K103N-containing virus replicated as well as wild-type (WT) virus and that the M230L-containing virus was severely impaired in replication ability in the absence of NNRTIs. K103N-containing viruses replicated well in the presence of efavirenz and nevirapine, while virus containing M230L displayed substantial replication in the presence of all NNRTIs tested. RNA-dependent DNA polymerase assays using a heterogeneous HIV-1 RNA template and purified recombinant WT or mutated reverse transcriptase enzymes revealed that the fold change (FC) for etravirine was 0.7 for K103N and 8 for M230L. K103N and M230L conferred high-level resistance to both efavirenz (FC=39 and 15.3, respectively) and nevirapine (FC=43.5 and 33), confirming that M230L confers cross-resistance to both drugs while K103N-containing viruses remain susceptible to etravirine. In enzymatic assays, the K103N mutation was associated with moderate reductions in the efficiency of 3' DNA end-directed RNA template cleavage, while comparable efficiency to WT enzyme was observed with regard to minus-strand strong stop DNA synthesis and polymerase processivity. CONCLUSIONS: These properties help to explain differences in the evolution and prevalence of these two NNRTI mutations.
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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".