A High-Throughput Continuous Assay for Screening and Characterization of Inhibitors of HIV Reverse-Transcriptase DNA Polymerase Activity
Bibliographic record
Abstract
The authors have devised a continuous fluorescence-based assay to measure HIV reverse transcriptase (RT) polymerase activity for both high-throughput screening (HTS) and mechanistic characterization of inhibitors. The designed substrate is composed of a recessed DNA primer annealed to a DNA template that is labeled at the 5'-terminus with a donor fluorophore (AlexaFluor 488). RT-catalyzed incorporation of an acceptor-labeled deoxyuridine (dUTP-AlexaFluor 555) at the 3'-terminus of the fully extended DNA primer juxtaposes donor and acceptor fluorophores, resulting in robust fluorescence resonance energy transfer that can be monitored kinetically in real time. The assay is sensitive, permitting the use of low enzyme concentrations (<0.5 nM), and can be miniaturized for use in 384-well HTS mode. The authors further show that this assay is capable of evaluating inhibitor mechanism of action by confirming the binding mechanism of a set of nonnucleoside RT inhibitors. Given the versatility and the lack of requirement for costly platforms or radioactivity, this assay may serve to accelerate and streamline the discovery and characterization process for future antiviral 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".