Integrating ensemble machine learning and multi-omics approaches to identify Dp44mT as a novel anti-Candida albicans agent targeting cellular iron homeostasis DOI Creative Commons

Xiaowei Chai,

Yuanying Jiang,

Hui Lü

и другие.

Frontiers in Pharmacology, Год журнала: 2025, Номер 16

Опубликована: Апрель 24, 2025

Candidiasis, mainly caused by Candida albicans, poses a serious threat to human health. The escalating drug resistance in C. albicans and the limited antifungal options highlight critical need for novel therapeutic strategies. We evaluated 12 machine learning models on self-constructed dataset with known anti-C. activity. Based their performance, optimal model was selected screen our separate in-house compound library unknown activity potential agents. of compounds confirmed through vitro susceptibility assays, hyphal growth biofilm formation assays. Through transcriptomics, proteomics, iron rescue experiments, CTC staining, JC-1 DAPI molecular docking, dynamics simulations, we elucidated mechanism underlying compound. Among models, best predictive an ensemble constructed from Random Forests Categorical Boosting using soft voting. It predicts that Dp44mT exhibits potent tests further verified this finding can inhibit planktonic growth, formation, albicans. Mechanistically, exerts disrupting cellular homeostasis, leading collapse mitochondrial membrane ultimately causing apoptosis. This study presents practical approach predicting com-pounds provides new insights into development homeostasis

Язык: Английский

Mechanisms of Azole Potentiation: Insights from Drug Repurposing Approaches DOI
Juan Xiong, Hui Lu, Yuanying Jiang

и другие.

ACS Infectious Diseases, Год журнала: 2025, Номер unknown

Опубликована: Янв. 3, 2025

The emergence of azole resistance and tolerance in pathogenic fungi has emerged as a significant public health concern, emphasizing the urgency for innovative strategies to bolster efficacy azole-based treatments. Drug repurposing stands promising practical avenue advancing antifungal therapy, with potential swift clinical translation. This review offers comprehensive overview synergistic agents uncovered through drug strategies, alongside an in-depth exploration mechanisms by which these augment potency. Drawing from mechanisms, we delineate aimed at enhancing effectiveness, such inhibiting efflux pumps elevate concentrations within fungal cells, intensifying ergosterol synthesis inhibition, mitigating cell azoles, disrupting biological processes extending beyond synthesis. is beneficial development potentiators, it meticulously examines instances provides nuanced discussions on underlying progression potentiators strategies.

Язык: Английский

Процитировано

2

Otilonium Bromide Exhibits Potent Antifungal Effects by Blocking Ergosterol Plasma Membrane Localization and Triggering Cytotoxic Autophagy in Candida Albicans DOI Creative Commons
Cheng Zhen, Li Wang,

Yanru Feng

и другие.

Advanced Science, Год журнала: 2024, Номер unknown

Опубликована: Июль 12, 2024

Abstract Candidiasis, which presents a substantial risk to human well‐being, is frequently treated with azoles. However, drug‐drug interactions caused by azoles inhibiting the CYP3A4 enzyme, together increasing resistance of Candida species azoles, represent serious issues this class drug, making it imperative develop innovative antifungal drugs tackle growing clinical challenge. A drug repurposing approach used examine library Food and Drug Administration (FDA)‐approved drugs, ultimately identifying otilonium bromide (OTB) as an exceptionally encouraging agent. Mechanistically, OTB impairs vesicle‐mediated trafficking targeting Sec31, thereby impeding plasma membrane (PM) localization ergosterol transporters, such Sip3. Consequently, obstructs movement across membranes triggers cytotoxic autophagy. It noteworthy that C. albicans encounters challenges in developing because not substrate for transporters. This study opens new door therapy, wherein disrupts subcellular distribution induces Additionally, circumvents hepatotoxicity associated azole‐mediated liver enzyme inhibition avoids export‐mediated .

Язык: Английский

Процитировано

3

Integrating ensemble machine learning and multi-omics approaches to identify Dp44mT as a novel anti-Candida albicans agent targeting cellular iron homeostasis DOI Creative Commons

Xiaowei Chai,

Yuanying Jiang,

Hui Lü

и другие.

Frontiers in Pharmacology, Год журнала: 2025, Номер 16

Опубликована: Апрель 24, 2025

Candidiasis, mainly caused by Candida albicans, poses a serious threat to human health. The escalating drug resistance in C. albicans and the limited antifungal options highlight critical need for novel therapeutic strategies. We evaluated 12 machine learning models on self-constructed dataset with known anti-C. activity. Based their performance, optimal model was selected screen our separate in-house compound library unknown activity potential agents. of compounds confirmed through vitro susceptibility assays, hyphal growth biofilm formation assays. Through transcriptomics, proteomics, iron rescue experiments, CTC staining, JC-1 DAPI molecular docking, dynamics simulations, we elucidated mechanism underlying compound. Among models, best predictive an ensemble constructed from Random Forests Categorical Boosting using soft voting. It predicts that Dp44mT exhibits potent tests further verified this finding can inhibit planktonic growth, formation, albicans. Mechanistically, exerts disrupting cellular homeostasis, leading collapse mitochondrial membrane ultimately causing apoptosis. This study presents practical approach predicting com-pounds provides new insights into development homeostasis

Язык: Английский

Процитировано

0