The K65R Mutation in HIV-1 Reverse Transcriptase: Genetic Barriers, Resistance Profile and Clinical Implications
Bibliographic record
Abstract
Resistance to antiviral therapy is the limiting factor in the successful management of HIV. In general, the K65R mutation is rarely selected (1.7-4%) with tenofovir disoproxil fumarate (TDF), abacavir (ABC), didanosine (ddI), and stavudine (d4T), as compared with the high incidence (>40%) of thymidine analog mutations associated with zidovudine and d4T. The high barrier to the development of K65R may reflect a combination of factors, including the high potency of K65R-selecting drugs, including recommended TDF/emtricitabine and ABC/lamivudine (ABC/3TC) combinations; the partial (low-intermediate level) profile of cross-resistance conferred by K65R to TDF, ABC and 3TC; the favorable viral fitness constraint imposed by K65R and the 3TC/emtricitabine-associated M184V mutations; the bidirectional antagonism between the K65R and thymidine analog mutation pathways; and unique RNA structural considerations in the region surrounding codon 65. Nevertheless, surprisingly high levels of treatment failures and K65R resistance may be associated with triple nucleoside analog regimens. The use of TDF + ABC, TDF + ddI and ABC + d4T in combination with 3TC or emtricitabine should be avoided. This selection of K65R may be reduced by the inclusion of zidovudine in two-four nucleoside reverse-transcriptase regimens. Clinical studies have demonstrated an increased frequency of K65R in association with suboptimal d4T and ddI regimens, as well as nevirapine and its resistance mutations Y181C and G190A. The potential for the development of the K65R mutation in subtype C is particularly problematic wherein a signature KKK nucleotide motif, at codons 64, 65 and 66 in reverse transcriptase, appear to lead to template pausing, facilitating the selection of K65R. Optimizing regimens may attenuate the emergence of K65R, leading to better long-term treatment management in different geographic settings. TDF-based regimens are the leading candidates for first- and second-line therapy, microbicides and chemoprophylaxis strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".