Nucleoside Analogue Inhibitors of Human Immunodeficiency Virus Reverse Transcriptase
Bibliographic record
Abstract
More than 20 different antiretroviral agents have been approved for human immunodeficiency virus (HIV) treatment. These compounds target distinct stages in the life cycle of this retrovirus that include (i) its entry into the cytoplasm, which marks the beginning of the infection; (ii) the process of reverse transcription, i.e., the conversion of the single-stranded RNA genome into double-stranded DNA; (iii) the integration of proviral, double-stranded DNA into the host chromosome; and (iv) the processing of viral precursor proteins at later stages. These steps are vital for viral replication, and with the exception of the entry process, each of the aforementioned reactions involves viral enzymes, i.e., the reverse transcriptase (RT), the integrase, and the protease, respectively, that can be targeted by antiretroviral drugs. This chapter focuses on nucleoside analogue RT inhibitors (NRTIs) in the context of mechanisms of action and resistance and on the implications for the development of future strategies designed to counteract resistance. All approved NRTIs show a broad spectrum of antiviral activity against HIV-1, HIV- 2, and sometimes even hepatitis B virus (HBV), which points to structurally highly related active sites. A given mutation or mutational cluster can affect susceptibility to different NRTIs to various degrees, which makes it difficult to group the mutations. It will be interesting to investigate how established and novel NRTIs can be most effectively combined with new classes of compounds with the ultimate goal of further reducing the risk of resistance development, while maintaining high standards regarding problems associated with toxicities and dosing.
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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) | 0.003 | 0.001 |
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".