International journal of biological macromolecules
Jun 1, 2025
Alpha-Galactosidase has significant industrial application value in food processing, animal nutrition and medical applications. Microbial-derived α-galactosidases predominate industrial implementation due to high productivity, yet their inherent ther...
Protein science : a publication of the Protein Society
Jun 1, 2025
Protein aggregation is associated with a spectrum of neurodegenerative diseases. Although many small ligands have been found to modulate or inhibit protein aggregation, their molecular mechanisms remain unclear. One reason for this is the inherent he...
International journal of biological macromolecules
Jun 1, 2025
Diabetes mellitus, a chronic metabolic disorder, is characterized by high blood glucose levels. External insulin administration, along with diet and exercise, is recommended to the patients. The increase in the number of diabetics and the adoption of...
International journal of biological macromolecules
Jun 1, 2025
The disposal of recalcitrant dyes in aquatic environments from various industrial sectors is a threat to both the plant and animal kingdom. The presence of dyes in various water bodies undermines the availability of uncontaminated drinking water and ...
This work utilized machine learning (ML) algorithms to predict and validate the drug release kinetics of a short worm-like nanostructured isocyanate-derived aerogel: the first time ML has been employed to study the drug delivery properties of this i...
Machine learning (ML) tools have revolutionized protein structure prediction, engineering, and design, but the best ML tool is only as good as the training data it learns from. To obtain high-quality structural or functional data, protein purificatio...
Journal of chemical theory and computation
May 13, 2025
The dissociation or off rate, , of a drug molecule has been shown to be more relevant to efficacy than affinity for selected systems, motivating the development of predictive computational methodologies. These are largely based on enhanced-sampling m...
The prediction of enzyme kinetic parameters is crucial for screening enzymes with high catalytic efficiency and desired characteristics to catalyze natural or non-natural reactions. Data-driven machine learning models have been explored to reduce exp...
Enzymatic reaction kinetics are central in analyzing enzymatic reaction mechanisms and target-enzyme optimization, and thus in biomanufacturing and other industries. The enzyme turnover number (kcat) and Michaelis constant (Km), key kinetic parameter...
MOTIVATION: Dynamical properties of biochemical pathways (BPs) help in understanding the functioning of living cells. Their in silico assessment requires simulating a dynamical system with a large number of parameters such as kinetic constants and sp...
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