AIMC Topic: Hydrolysis

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Nanopore Analysis of Malto-oligosaccharides from Amylose, Amylopectin, and Cyclodextrin Hydrolysates.

Nano letters
Malto-oligosaccharides, structurally diverse glucose polymers comprising 2-10 monosaccharide units, play vital roles in food science, pharmaceuticals, and glycobiology. However, their precise structural characterization remains challenging due to sub...

Intelligent delignification: leveraging explainable AI for ozone transport modeling and optimization.

Scientific reports
Biomass is mainly composed of cellulose, hemicellulose, and lignin, where lignin is almost one-third of the amount of biomass. Lignin is removed from the biomass matrix because its complex, recalcitrant structure acts as a physical and chemical barri...

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...

Drp1 Proteins Released from Hydrolysis-Driven Scaffold Disassembly Trigger Nucleotide-Dependent Membrane Remodeling to Promote Scission.

Journal of the American Chemical Society
Dynamin-related protein (Drp1) drives mitochondrial fission, dysregulation of which leads to neurodegenerative, metabolic, and apoptotic disorders. The precise mechanism of fission completion is unclear. One prevailing model is based on GTP-driven o...

Multi-functionalities of citric acid assisted thermal hydrolysis for sludge pretreatment: A novel method assisting in sludge treatment targeting multiple-objectives.

Journal of hazardous materials
Pretreatment is essential for enhancing sludge treatment efficiency, including anaerobic digestion, phosphorus recovery, sludge dewatering, and heavy metal removal. However, few techniques simultaneously address multiple treatment objectives. In this...

Substrate Activation Efficiency in Active Sites of Hydrolases Determined by QM/MM Molecular Dynamics and Neural Networks.

International journal of molecular sciences
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
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
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
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
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...