In Vitro Antiviral Activity and Cross-Resistance Profile of PL-100, a Novel Protease Inhibitor of Human Immunodeficiency Virus Type 1
Bibliographic record
Abstract
Despite the success of highly active antiretroviral therapy, the current emergence and spread of drug-resistant variants of human immunodeficiency virus (HIV) stress the need for new inhibitors with distinct properties. We designed, produced, and screened a library of compounds based on an original l-lysine scaffold for their potentials as HIV type 1 (HIV-1) protease inhibitors (PI). One candidate compound, PL-100, emerged as a specific and noncytotoxic PI that exhibited potent inhibition of HIV-1 protease and viral replication in vitro (K(i), approximately 36 pM, and 50% effective concentration [EC(50)], approximately 16 nM, respectively). To confirm that PL-100 possessed a favorable resistance profile, we performed a cross-resistance study using a panel of 63 viral strains from PI-experienced patients selected for the presence of primary PI mutations known to confer resistance to multiple PIs now in clinical use. The results showed that PL-100 retained excellent antiviral activity against almost all of these PI-resistant viruses and that its performance in this regard was superior to those of atazanavir, amprenavir, indinavir, lopinavir, nelfinavir, and saquinavir. In almost every case, the increase in the EC(50) for PL-100 observed with viruses containing multiple mutations in protease was far less than that obtained with the other drugs tested. These data underscore the potential for PL-100 to be used in the treatment of drug-resistant HIV disease and argue for its further development.
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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".