AIMC Topic: Hydrolysis
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Substrate Activation Efficiency in Active Sites of Hydrolases Determined by QM/MM Molecular Dynamics and Neural Networks.
International journal of molecular sciences
May 26, 2025
The active sites of enzymes are able to activate substrates and perform chemical reactions that cannot occur in solutions. We focus on the hydrolysis reactions catalyzed by enzymes and initiated by the nucleophilic attack of the substrate's carbonyl ...
Enabling malic acid production from corn-stover hydrolysate in Lipomyces starkeyi via metabolic engineering and bioprocess optimization.
Microbial cell factories
May 21, 2025
BACKGROUND: Lipomyces starkeyi is an oleaginous yeast with a native metabolism well-suited for production of lipids and biofuels from complex lignocellulosic and waste feedstocks. Recent advances in genetic engineering tools have facilitated the deve...
In-situ conversion of hemicellulose to furfural by Lewis acid-enhanced deep eutectic solvents to maintain stable pretreatment performance and trigger profitable biorefining processes.
International journal of biological macromolecules
Apr 30, 2025
Deep eutectic solvents (DESs) are gaining attention for lignocellulose pretreatment, yet screening methods and stable cyclic processes remain underexplored. This study compared solubility and machine learning to predict delignification, screening the...
HEPOM: Using Graph Neural Networks for the Accelerated Predictions of Hydrolysis Free Energies in Different pH Conditions.
Journal of chemical information and modeling
Apr 4, 2025
Hydrolysis is a fundamental family of chemical reactions where water facilitates the cleavage of bonds. The process is ubiquitous in biological and chemical systems, owing to water's remarkable versatility as a solvent. However, accurately predicting...
Targeted conversion of cellulose and hemicellulose macromolecules in the phosphoric acid/acetone/water system: An exploration of machine learning evaluation and product prediction.
International journal of biological macromolecules
Mar 8, 2025
The simultaneous hydrolysis of cellulose and hemicellulose involves trade-offs, making precise control of hydrolysis products crucial for sustainable development. This study employed three machine learning (ML) models-Random Forest (RF), Extreme Grad...
Enhancing beef tallow flavor through enzymatic hydrolysis: Unveiling key aroma precursors and volatile compounds using machine learning.
Food chemistry
Feb 26, 2025
Lipids are critical precursors of aroma compounds in beef tallow. This study investigated how enzymatic hydrolysis treatment affected the aroma precursors and flavor of beef tallow during the manufacturing process. Using gas chromatography-mass spect...
Extraction of polysaccharides from Camellia oleifera leaves by dual enzymes combined with deep eutectic solvents screened by ANN and COSMO-RS.
International journal of biological macromolecules
Feb 16, 2025
Camellia oleifera leaves were byproduct of the C. oleifera industry which was rich in polysaccharides. Deep eutectic solvent-dual enzyme system (DES-dEAE) was established to achieve the simultaneous hydrolysis reaction of dual enzymes and DES extract...
Representative training data sets are critical for accurate machine-learning classification of microscopy images of particles formed by lipase-catalyzed polysorbate hydrolysis.
Journal of pharmaceutical sciences
Jan 15, 2025
Polysorbate 20 (PS20) is commonly used as an excipient in therapeutic protein formulations. However, over the course of a therapeutic protein product's shelf life, minute amounts of co-purified host-cell lipases may cause slow hydrolysis of PS20, rel...
How peptide migration and fraction bioactivity are modulated by applied electrical current conditions during electromembrane process separation: A comprehensive machine learning-based peptidomic approach.
Food research international (Ottawa, Ont.)
Nov 28, 2024
Industrial wastewaters are significant global concerns due to their environmental impact. Yet, protein-rich wastewaters can be valorized by enzymatic hydrolysis to release bioactive peptides. However, achieving selective molecular differentiation and...
Thermodynamics and explainable machine learning assist in interpreting biodegradability of dissolved organic matter in sludge anaerobic digestion with thermal hydrolysis.
Bioresource technology
Aug 28, 2024
Dissolved organic matter (DOM) is essential in biological treatment, yet its specific roles remain incompletely understood. This study introduces a machine learning (ML) framework to interpret DOM biodegradability in the anaerobic digestion (AD) of s...
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