AIMC Topic: Peptides

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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...

Multidimensional strategy for discovering saltiness-enhancing peptides in shrimp heads integrating ultra-high pressure hydrolysis and machine learning.

Food chemistry
This study aims to develop a comprehensive strategy to investigate whether the integration of ultra-high pressure (UHP)-assisted enzymatic hydrolysis with machine learning and molecular docking can effectively identify salty peptides (SPs) from Litop...

Prediction of peptide cleavage sites using protein language models and graph neural networks.

Scientific reports
The growing interest in using peptide molecules as therapeutic agents, driven by their high selectivity and efficacy, has become a significant trend in the pharmaceutical industry. However, their oral administration remains challenging due to their l...

DeepBPred: blood-brain barrier peptide predictor using stacked BiGRU model with novel features.

BMC biology
BACKGROUND: The blood-brain barrier (B) acts as a membrane that is a major concern in treating central nervous system (CNS) disorders. The B penetrating peptides (BPPs) play a significant role in delivering therapeutic drugs to a wide range of disord...

In silico Techniques for the Investigation of Bioactive Compounds in Quinoa (Chenopodium quinoa Willd.): Recent Advances in Molecular Modeling and Identification of Therapeutic Targets.

Plant foods for human nutrition (Dordrecht, Netherlands)
Quinoa (Chenopodium quinoa Willd.) is a valuable source of bioactive compounds with therapeutic potential, including peptides, saponins, and polyphenols. In recent years, in silico tools have emerged as key strategies for predicting, characterizing, ...

Predicted peptide scaffolds for drug screening in endometrial cancer organoids.

Scientific reports
AlphaFold, a deep learning-based platform widely used to predict protein and peptide structures, was employed in this study to model the self-assembling peptide RFC, which demonstrated a stable α-helical structure with high confidence. This structura...

Design of Specific Peptide Inhibitors of Toxin-Antitoxin-Mediated Antiphage Defense.

ACS synthetic biology
Toxin-antitoxin (TA) systems are widespread antiphage defense elements in bacteria that may impede successful phage therapy. Phage-encoded inhibitors of these systems have been discovered that enhance phage infection capacity. We used fragment-based ...

Curvature-Sensing Peptides for Virus and Extracellular Vesicle Applications.

ACS nano
Membrane curvature is a key biophysical feature that regulates diverse biological processes. A wide range of natural proteins have distinct structural motifs that can sense membrane curvature and function independently as curvature-sensing peptides. ...

Serum Fingerprinting-Based Integrative Dual-Omics Machine Learning for Endometriosis-Associated Ovarian Cancer.

Analytical chemistry
Dual-omics, by integrating molecular information from two distinct dimensions, can offer more comprehensive perspective for complex disease. Herein, we developed an efficient functionalized mesoporous nanoparticle-coupled laser desorption/ionization ...

T cell receptor specificity landscape revealed through de novo peptide design.

Proceedings of the National Academy of Sciences of the United States of America
T cells play a key role in adaptive immunity by mounting specific responses against diverse pathogens. Effective bindings between T cell receptors (TCRs) and pathogen derived peptides presented on major histocompatibility complexes (MHCs) mediate imm...