Human endogenous retrovirus-K (HERV-K) reverse transcriptase (RT) structure and biochemistry reveals remarkable similarities to HIV-1 RT and opportunities for HERV-K–specific inhibition
Bibliographic record
Abstract
Human endogenous retroviruses (HERVs) comprise nearly 8% of the human genome and are derived from ancient integrations of retroviruses into the germline. The biology of HERVs is poorly defined, but there is accumulating evidence supporting pathological roles in diverse diseases, such as cancer, autoimmune, and neurodegenerative diseases. Functional proteins are produced by HERV-encoded genes, including reverse transcriptases (RTs), which could be a contributor to the pathology attributed to aberrant HERV-K expression. To facilitate the discovery and development of HERV-K RT potent and selective inhibitors, we expressed active HERV-K RT and determined the crystal structure of a ternary complex of this enzyme with a double-stranded DNA substrate. We demonstrate a range of RT inhibition with antiretroviral nucleotide analogs, while classic nonnucleoside analogs do not inhibit HERV-K RT. Detailed comparisons of HERV-K RT with other known RTs demonstrate similarities to diverse RT families and a striking similarity to the HIV-1 RT asymmetric heterodimer. Our analysis further reveals opportunities for selective HERV-K RT inhibition.
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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) | 0.001 | 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 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".