Revealing Domain Structure through Linker-Scanning Analysis of the Murine Leukemia Virus (MuLV) RNase H and MuLV and Human Immunodeficiency Virus Type 1 Integrase Proteins
Bibliographic record
Abstract
Linker-scanning libraries were generated within the 3' terminus of the Moloney murine leukemia virus (M-MuLV) pol gene encoding the connection-RNase H domains of reverse transcriptase (RT) as well as the structurally related M-MuLV and human immunodeficiency virus type 1 (HIV-1) integrase (IN) proteins. Mutations within the M-MuLV proviral vectors were Tn7 based and resulted in 15-bp insertions. Mutations within an HIV-1 IN bacterial expression vector were based on Tn5 and resulted in 57-bp insertions. The effects of the insertions were examined in vivo (M-MuLV) and in vitro (HIV-1). A total of 178 individual M-MuLV constructs were analyzed; 40 in-frame insertions within RT connection-RNase H, 108 in-frame insertions within IN, 13 insertions encoding stop codons within RNase H, and 17 insertions encoding stop codons within IN. For HIV-1 IN, 56 mutants were analyzed. In both M-MuLV and HIV-1 IN, regions are identified which functionally tolerate multiple-linker insertions. For MuLV, these correspond to the RT-IN proteolytic junction, the junction between the IN core and C terminus, and the C terminus of IN. For HIV-1 IN, in addition to the junction between the IN core and C terminus and the C terminus of IN, insertions between the N terminus and core domains maintained integration and disintegration activity. Of the 40 in-frame insertions within the M-MuLV RT connection-RNase H domains, only the three C-terminal insertions mapping to the RT-IN proteolytic junction were viable. These results correlate with deletion studies mapping the domain and subdomain boundaries of RT and IN. Importantly, these genetic footprints provide a means to identify nonessential regions within RT and IN for targeted gene therapy applications.
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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) | 0.001 | 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".