AIMC Topic: Candida albicans

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Fungal virulence factors datasets for inflammatory bowel disease-specific antifungal drug discovery.

Scientific data
Fungi are closely associated with various diseases, among which Candida albicans (C. albicans) is recognized as an important pathogen in inflammatory bowel disease (IBD). Fungal pathogenicity is primarily mediated by virulence factors (VFs); therefor...

Nordihydroguaiaretic acid (NDGA) exhibits potent anti-biofilm and antimicrobial activity against methicillin-resistant Staphylococcus aureus and Candida albicans.

Phytomedicine : international journal of phytotherapy and phytopharmacology
INTRODUCTION: The global rise of antimicrobial resistance (AMR), particularly among biofilm-forming bacteria and fungi, has created an urgent need for novel therapeutics. Nordihydroguaiaretic acid (NDGA), a plant-derived polyphenolic lignan, has demo...

Pathogen virulence genes: Advances, challenges and future directions in infectious disease research (Review).

International journal of molecular medicine
Pathogens, including bacteria, viruses and fungi, employ virulence genes to invade their hosts, circumvent immunity and induce diseases. The present review examines the categorization and regulatory mechanisms of virulence genes and their co‑evolutio...

Antimicrobial Peptides Design Using Deep Learning and Rational Modifications: Activity in Bacteria, Candida albicans, and Cancer Cells.

Current microbiology
Resistance to antimicrobial agents has become a global threat, estimated to cause 10-million deaths annually by 2050. Antimicrobial peptides are emerging as an alternative and offer advantages over traditional antibiotics. Antimicrobial peptides gene...

Identification of potential markers of elevated anticandidal activity of propolis extracts.

Journal of ethnopharmacology
ETHNOPHARMACOLOGICAL RELEVANCE: For centuries, propolis has been one of the most important and popular antimicrobial (antibacterial and antifungal) agents used in traditional medicine worldwide, including Central and Eastern Europe. Despite centuries...

Therapeutic effect and concomitant toxicity of hydrargyrum chloratum compositum on chronic difficult-to-heal wounds in rats.

Journal of ethnopharmacology
ETHNOPHARMACOLOGICAL RELEVANCE: Hydrargyrum chloratum compositum(Hcc) is a traditional Chinese medicine for external use, with the efficacy of 'transforming corrosion and pulling out toxins, removing corrosion and regenerating muscles'. The main comp...

ML-AMPs designed through machine learning show antifungal activity against C. albicans and therapeutic potential on mice model with candidiasis.

Life sciences
AIMS: C. albicans resistant strains have led to increasingly severe treatment challenges. Antimicrobial peptides with low resistance-inducing propensity for pathogens have been developed. A series of antimicrobial peptides de novo designed through ma...

Deep Learning Combined with Quantitative Structure‒Activity Relationship Accelerates De Novo Design of Antifungal Peptides.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Novel antifungal drugs that evade resistance are urgently needed for Candida infections. Antifungal peptides (AFPs) are potential candidates due to their specific mechanism of action, which makes them less prone to developing drug resistance. An AFP ...

Optimizing the production and efficacy of antimicrobial bioactive compounds from in combating multi-drug-resistant pathogens.

Frontiers in cellular and infection microbiology
BACKGROUND: The rise of antibiotic-resistant pathogens has intensified the search for novel antimicrobial agents. This study aimed to isolate from local soil samples and evaluate its antimicrobial properties, along with optimizing the production of ...

DrugSK: A Stacked Ensemble Learning Framework for Predicting Drug Combinations of Multiple Diseases.

Journal of chemical information and modeling
Combination therapy is an important direction of continuous exploration in the field of medicine, with the core goals of improving treatment efficacy, reducing adverse reactions, and optimizing clinical outcomes. Machine learning technology holds gre...