AIMC Topic: Fungal Proteins

Clear Filters Showing 21 to 30 of 34 articles

An improved method for functional similarity analysis of genes based on Gene Ontology.

BMC systems biology
BACKGROUND: Measures of gene functional similarity are essential tools for gene clustering, gene function prediction, evaluation of protein-protein interaction, disease gene prioritization and other applications. In recent years, many gene functional...

Machine Learning of Protein Interactions in Fungal Secretory Pathways.

PloS one
In this paper we apply machine learning methods for predicting protein interactions in fungal secretion pathways. We assume an inter-species transfer setting, where training data is obtained from a single species and the objective is to predict prote...

Detection of overlapping protein complexes in gene expression, phenotype and pathways of Saccharomyces cerevisiae using Prorank based Fuzzy algorithm.

Gene
Proteins show their functional activity by interacting with other proteins and forms protein complexes since it is playing an important role in cellular organization and function. To understand the higher order protein organization, overlapping is an...

EffectorP: predicting fungal effector proteins from secretomes using machine learning.

The New phytologist
Eukaryotic filamentous plant pathogens secrete effector proteins that modulate the host cell to facilitate infection. Computational effector candidate identification and subsequent functional characterization delivers valuable insights into plant-pat...

mycoCLAP, the database for characterized lignocellulose-active proteins of fungal origin: resource and text mining curation support.

Database : the journal of biological databases and curation
Enzymes active on components of lignocellulosic biomass are used for industrial applications ranging from food processing to biofuels production. These include a diverse array of glycoside hydrolases, carbohydrate esterases, polysaccharide lyases and...

AlphaFold modeling uncovers global structural features of class I and class II fungal hydrophobins.

Protein science : a publication of the Protein Society
Hydrophobins are a family of small fungal proteins that self-assemble at hydrophobic-hydrophilic interfaces. Hydrophobins not only play crucial roles in filamentous fungal growth and development but also have attracted substantial attention due to th...

Deep Learning-Guided Discovery of Celestolide as a Natural Allosteric Inhibitor Targeting CYP51 and Its Application in Strawberry Preservation.

Journal of agricultural and food chemistry
Most CYP51 inhibitors act competitively and are prone to resistance, whereas allosteric inhibitors hold promise but are difficult to develop. In this study, we employed the neural relational inference framework alongside the Gaussian network-based de...

ActiMut-XGB: Predicting thermodynamic stability of point mutations for CALB with protein language model.

International journal of biological macromolecules
Predicting the functional impact of single-point mutations on protein residual activity, especially after high-temperature incubation, is critical in protein engineering. We present an innovative machine learning model based on eXtreme Gradient Boost...

DeepMBEnzy: An AI-Driven Database of Mycotoxin Biotransformation Enzymes.

Journal of agricultural and food chemistry
Mycotoxins are toxic fungal metabolites that pose significant health risks. Enzyme biotransformation is a promising option for detoxifying mycotoxins and for elucidating their intracellular metabolism. However, few mycotoxin-biotransformation enzymes...

Effector-GAN: prediction of fungal effector proteins based on pretrained deep representation learning methods and generative adversarial networks.

Bioinformatics (Oxford, England)
MOTIVATION: Phytopathogenic fungi secrete effector proteins to subvert host defenses and facilitate infection. Systematic analysis and prediction of candidate fungal effector proteins are crucial for experimental validation and biological control of ...