Identification and mechanistic study of piceatannol as a natural xanthine oxidase inhibitor.

Natural Xanthine oxidase (XOD) inhibitors represent promising therapeutic agents for hyperuricemia (HUA) treatment due to their potent efficacy and favorable safety profiles. This study involved the construction of a comprehensive database of 315 XOD inhibitors and development of 28 machine learning-based QSAR models. The ChemoPy light gradient boosting machine model exhibited the best performance (AUC = 0.

Predicting variable-length ACE inhibitory peptides based on graph convolutional network.

Traditional molecular descriptors have contributed to the prediction of angiotensin I-converting enzyme (ACE) inhibitory peptides, but they often fall short in capturing the complex structure of the molecule. To address these limitations, this study introduces molecular graphs as an advanced method for peptide characterization. Peptides containing 2-10 amino acids were represented using molecular graphs, and a graph convolutional network (GCN) model was constructed to predict variable-length peptides.