Identification and Characterization of a Novel HIV-1 Nucleotide-Competing Reverse Transcriptase Inhibitor Series
Bibliographic record
Abstract
Several groups have recently reported on the identification of nucleotide-competing reverse transcriptase inhibitors (NcRTIs), a new class of RT inhibitors. NcRTIs reversibly inhibit binding of the incoming nucleotide to the RT active site but do not act as chain terminators, unlike the nucleos(t)ide reverse transcriptase inhibitor (NRTI) class. We identified a novel benzo[4,5]furo[3,2,d]pyrimidin-2-one NcRTI chemical series. Structure-activity relationship evaluation of this series with both RT and viral replication assays led to the identification of compound A, a new NcRTI. Compound A inhibited HIV-1 RT in a primer extension assay (50% inhibitory concentration, 2.6 nM) but had no measurable activity against human DNA polymerase γ at 10 μM. It potently inhibited HIV-1 replication in vitro (50% effective concentration, 1.5 nM). The antiviral potency of compound A was unaffected by the presence of nonnucleotide RT inhibitor (NNRTI) mutations tested (L100I, K103N/Y181C, V106A, or Y188L). Notably, viruses encoding K65R were hypersusceptible to inhibition by compound A. Compound A also retained full activity against viruses encoding M184V. In vitro selection for resistant virus to compound A led to the selection of a single substitution within RT: W153L. A recombinant virus encoding the RT W153L was highly resistant to compound A (fold change, 160). W153 is a highly conserved residue in HIV RT and has not been previously associated with drug resistance. In summary, a novel NcRTI series with optimized antiviral activity, minimal cross-resistance to existing RT inhibitor classes, and a distinct resistance profile has been discovered. These results further establish NcRTIs as an emerging class of antiretroviral agents.
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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) | 0.002 | 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".