In vitro and structural evaluation of PL-100 as a potential second-generation HIV-1 protease inhibitor
Bibliographic record
Abstract
OBJECTIVES: HIV-1 protease inhibitors (PIs) are key components of HIV therapy. PL-100 is a novel lysine sulphonamide that demonstrates potent antiviral activity against multiresistant HIV-1 strains as well as a higher genetic barrier for development of resistance mutations compared with first-generation PIs. In the present study, we compared the antiviral activity of PL-100 against HIV-1 subtype B with that of darunavir. METHODS: We used tissue culture experiments to evaluate the in vitro development of resistance to PL-100 and tested the antiviral activity of several clinically approved PIs against PL-100-selected resistant variants. Structural modelling was also used to compare the binding of PL-100 and darunavir to the HIV-1 protease (PR) enzyme. RESULTS: PL-100-resistant variants that emerged within 8-48 weeks showed low- to high-level resistance (3.5- to 21.6-fold) to PL-100, but commonly retained susceptibility to darunavir, which, in contrast, did not select for resistance mutations over a period of 40 weeks. Structural modelling demonstrated that binding of PL-100 was predominantly based on polar interactions and delocalized hydrophobic interactions through its diphenyl groups, while darunavir has numerous interactions with PR that include hydrogen bonding to PR backbone oxygens at amino acid positions A28, D29 and D30 via di-tetrahydrofuran (di-THF) groups. CONCLUSIONS: Hydrogen-bonding contacts and the di-THF group in darunavir, as well as the hydrophobic nature of PL-100, contribute to PI binding and a high genetic barrier for resistance. Redesigning the structure of PL-100 to include a di-THF group might improve it.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 | 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".