AIMC Topic: Fungal Proteins

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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...

Structure-guided secretome analysis of gall-forming microbes offers insights into effector diversity and evolution.

eLife
Phytopathogens secrete effector molecules to manipulate host immunity and metabolism. Recent advances in structural genomics have identified fungal effector families whose members adopt similar folds despite sequence divergence, highlighting their im...

Discovering of novel umami-enhancing peptides from Flammulina filiformis: Combining virtual screening, machine learning, molecular dynamics simulations, and sensory evaluation.

Food chemistry
This research employed integrated machine learning and bioinformatics approaches to identify umami-enhancing peptides from Flammulina filiformis, elucidate their mechanisms of umami augmentation, and validate their efficacy through sensory evaluation...

Machine learning reveals genes impacting oxidative stress resistance across yeasts.

Nature communications
Reactive oxygen species (ROS) are highly reactive molecules encountered by yeasts during routine metabolism and during interactions with other organisms, including host infection. Here, we characterize the variation in resistance to the ROS-inducing ...

Landscape of essential growth and fluconazole-resistance genes in the human fungal pathogen Cryptococcus neoformans.

PLoS biology
Fungi can cause devastating invasive infections, typically in immunocompromised patients. Treatment is complicated both by the evolutionary similarity between humans and fungi and by the frequent emergence of drug resistance. Studies in fungal pathog...

Identification of potent phytochemicals against Magnaporthe oryzae through machine learning aided-virtual screening and molecular dynamics simulation approach.

Computers in biology and medicine
Magnaporthe oryzae stands as a notorious fungal pathogen responsible for causing devastating blast disease in cereals, leading to substantial reductions in grain production. Despite the usage of chemical fungicides to combat the pathogen, their effec...

Machine Learning-Assisted SERS Reveals the Biochemical Signature of Enhanced Protein Secretion from Surface-Modified Magnetic Nanoparticles.

ACS applied materials & interfaces
This study introduces a novel investigation of the interaction between cells and iron oxide-based magnetic nanoparticles (FeO MNPs) via protein secretion and machine learning (ML)-assisted surface-enhanced Raman scattering (SERS). For the first time...

Inverse design of chemoenzymatic epoxidation of soyabean oil through artificial intelligence-driven experimental approach.

Bioresource technology
This paper presents an inverse design methodology that utilizes artificial intelligence (AI)-driven experiments to optimize the chemoenzymatic epoxidation of soyabean oil using hydrogen peroxide and lipase (Novozym 435). First, experiments are conduc...

Random forest machine-learning algorithm classifies white- and brown-rot fungi according to the number of the genes encoding Carbohydrate-Active enZyme families.

Applied and environmental microbiology
UNLABELLED: Wood-rotting fungi play an important role in the global carbon cycle because they are the only known organisms that digest wood, the largest carbon stock in nature. In the present study, we used linear discriminant analysis and random for...