AIMC Topic: Plant Proteins

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Candidate genes for anthracnose resistance in Senegalese sorghum: a machine learning-based exploration.

Functional & integrative genomics
Anthracnose, caused by the hemibiotrophic fungal pathogen Colletotrichum sublineola, is a significant constraint to sorghum production worldwide. Developing resistant cultivars is the most sustainable control strategy, but it requires constant additi...

Artificial Intelligence-Aided Virtual Screening and Molecular Dynamics Analysis of Novel Xanthine Oxidase Inhibitory Peptides Derived from Sunflower () Proteins.

Journal of agricultural and food chemistry
Gout is an inflammatory arthritis caused by urate crystal accumulation, and discovering natural xanthine oxidase (XO) inhibitors from food and agricultural sources is of growing interest. In this study, we employed AI-driven virtual screening to iden...

Hybrid plant-dairy cheese: Effects of lactic acid bacteria and plant proteins on composition, proteolysis, and flavor profile.

Food chemistry
In the search to improve the sustainability of the food supply chain, the market for plant-based cheese analogs is growing. However, sensory defects, particularly related to flavor, remain a challenge. Here we developed a hybrid plant-dairy cheese th...

Black pepper knowledge base (BlackPepKB): a centralized web resource for functional genomics of black pepper (Piper nigrum L.).

BMC genomics
BACKGROUND: Black pepper (Piper nigrum L.) is a highly valued spice crop with significant economic, medicinal, and cultural importance. While genomic and transcriptomic data for black pepper have rapidly accumulated in recent years, there is currentl...

PhyCysID: Plant Cystatin Protein Prediction by an Artificial Intelligence Approach.

Journal of chemical information and modeling
Phytocystatins are proteinaceous inhibitors found in plants that competitively target various classes of cysteine proteinases, including papain-like enzymes, cathepsins, and legumains. Based on structural characteristics and gene organization, phytoc...

Proteomics coupled machine learning-innovative approach in geographical origin authentication of green Coffea arabica.

Food chemistry
The geographical authentication of green specialty coffee is an economically sensitive analytical task that is not yet fully resolved. We used an innovative combination of proteomic profiling with linear discriminant analysis for the authentication o...

MultiRepPI: a cross-modal feature fusion-based multiple characterization framework for plant peptide-protein interaction prediction.

BMC plant biology
Plant peptide-protein interactions (PepPI) play a crucial role in plant growth, development, immune regulation, and environmental adaptation. However, existing computational methods still face several challenges in PepPI prediction. First, most metho...

Integration of pre-trained GRU and molecular docking for virtual screening of quinoa seed derived ACE inhibitory peptides: An innovative prediction strategy.

Food chemistry
Recent developments in AI, particularly deep learning, are sparking a revolution in bioactive peptide discovery. This study introduced a pretrained Gated Recurrent Unit model (Pre-GRU) to predict the IC values of ACE inhibitory peptides derived from ...

Analysis of Protein-Protein Interactions in CC125 by Co-Fractionation Mass Spectrometry.

Journal of proteome research
, a unicellular eukaryotic green alga, is an important biological model. Previous studies on protein complexes in have primarily focused on photosynthesis and ciliary movement, while understanding the overall protein complex network is still limited...

Structure and Functions of NDR1/HIN1-Like (NHL) Proteins in Plant Development and Response to Environmental Stresses.

Plant, cell & environment
The NON-RACE-SPECIFIC DISEASE RESISTANCE 1/harpin-induced 1-LIKE (NHL) gene family plays pivotal roles, including pathogen resistance, abiotic stress tolerance, and developmental regulation, underscoring their functional versatility in developmental ...