PL‐100, a novel HIV‐1 protease inhibitor displaying a high genetic barrier to resistance: An in vitro selection study
Bibliographic record
Abstract
The development of new HIV inhibitors with distinct resistance profiles is essential in order to combat the development of multi-resistant viral strains. A drug discovery program based on the identification of compounds that are active against drug-resistant viruses has produced PL-100, a novel potent protease inhibitor (PI) that incorporates a lysine-based scaffold. A selection for resistance against PL-100 in cord blood mononuclear cells was performed, using the laboratory-adapted IIIb strain of HIV-1, and it was shown that resistance appears to develop slower against this compound than against amprenavir, which was studied as a control. Four mutations in protease (PR) were selected after 25 weeks: two flap mutations (K45R and M46I) and two novel active site mutations (T80I and P81S). Site-directed mutagenesis revealed that all four mutations were required to develop low-level resistance to PL-100, which is indicative of the high genetic barrier of the compound. Importantly, these mutations did not cause cross-resistance to currently marketed PIs. In contrast, the P81S mutation alone caused hypersensitivity to two other PIs, saquinavir (SQV) and nelfinavir (NFV). Analysis of p55Gag processing showed that a marked defect in protease activity caused by mutation P81S could only be compensated when K45R and M46I were present. These data correlated well with the replication capacity (RC) of the mutant viruses as measured by a standard viral growth assay, since only viruses containing all four mutations approached the RC of wild type virus. X-ray crystallography provided insight on the structural basis of the resistance conferred by the identified mutations.
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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".