The role of polymorphisms at position 89 in the HIV-1 protease gene in the development of drug resistance to HIV-1 protease inhibitors
Bibliographic record
Abstract
OBJECTIVES: Relatively little is known about the development of resistance to protease inhibitors (PIs) in non-B subtypes. In subtype B viruses, L89 is commonly found at position 89 in the HIV protease (PR) gene, whereas M89 is commonly observed as a polymorphism in other subtypes. We compared the frequencies of substitutions at position 89 in PR in tissue culture selections and in clinical databases of PI-naive and PI-experienced populations. METHODS: Representative subtype A/CRF01_AE (n = 2 and 3) and subtype C (n = 5) isolates were cultured in MT-2 cells and cord blood mononuclear cells (CBMCs), respectively, under increasing drug pressure with PIs, and drug resistance mutations were identified. RESULTS: The M89 natural polymorphism in non-B subtypes commonly led to the appearance of an M89T mutation in selections with atazanavir in subtypes A/AE and C, and was accompanied by other previously recognized atazanavir mutations. The M89T mutation contributed to phenotypic resistance to atazanavir and cross-resistance to lopinavir and nelfinavir, but not to other PIs. A shift from a L89 natural polymorphism to L89I/M arose in two of five subtype C selections with PIs. M89I/V/T mutations were acquired by 10%-11% of individuals harbouring non-B subtypes who were failing PI-based regimens, but were rarely observed in drug-naive persons and in patients failing non-PI-based regimens. CONCLUSIONS: The M/L89 natural polymorphism present in non-B subtypes may lead to the M89T mutational pathway conferring resistance to atazanavir, lopinavir and nelfinavir.
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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 | 0.001 |
| 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".