Impairing the interaction between Erg11 and cytochrome P450 reductase Ncp1 enhances azoles’ antifungal activities
Bibliographic record
Abstract
Azole effectiveness against candidiasis can be compromised by Candida albicans resistance and tolerance, and unfortunately, few clinically useful compounds can enhance azole antifungal activities. We find that the amino acids V234, F235 and L238 of Erg11 are critical for its interaction with Ncp1, and the Ncp1-Erg11 association is important in azole response. Ellipticine and its analog phiKan 083 block this Erg11-Ncp1 interaction by targeting Ncp1, and boost antifungal effects of fluconazole in vitro and in vivo. A series of steps influencing this process—an initial elevation in reactive oxygen species, leading to protein oxidation and misfolding in the endoplasmic reticulum (ER) that causes ER stress. This stress leads to Ca2+ release from the ER, mitochondrial Ca2+ accumulation and dysfunction, increased ROS production, and apoptosis of C. albicans cells. Overall, disrupting the Erg11-Ncp1 interaction in C. albicans can serve as a useful approach to enhancing the antifungal properties of azoles. In this work, authors mechanistically explore the impact of the disruption of the Erg11-Ncp1 interaction in Candida albicans. Subsequent cellular stress releases calcium and damages mitochondria, increasing toxic oxidative molecules, and leading fungal cells to self-destruct. These reactions may serve as an approach to enhance antifungal properties of azoles.
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) | 0.000 | 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) | 0.002 | 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".