Potential of 4′-C-Substituted Nucleosides for the Treatment of HIV-1
Bibliographic record
Abstract
Extensive efforts have been made to identify nucleoside reverse transcriptase inhibitors (NRTIs). Eight NRTIs have now been approved for clinical use; however, variants of HIV-1 resistant to these antiviral agents have emerged in patients even when they are treated with combinations [highly active antiretroviral therapy (HAART)]. Thus, the development of novel compounds that are active against drug-resistant HIV-1 variants and that prevent or delay the emergence of resistant HIV-1 variants is urgently needed. Previously, 4'-C-substituted nucleosides (4'-SNs) were designed as new types of NRTIs. They were synthesized and examined as potential therapeutic agents against HIV infection. Among them, several 4'-substituted-2'-deoxynucleosides (4'-SdNs), especially those that bear an ethynyl group, were shown to be active against various laboratory and clinical HIV-1 strains including known drug-resistant variants. These results were recently reported by our collaborators. In this review, we summarize the design, synthesis and demonstrations of the anti-HIV activity of 4'-SNs, and then consider 4'-SNs as potential therapeutic agents for HIV-1.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".