AIMC Topic: Biocatalysis

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Machine learning applied to enzyme turnover numbers reveals protein structural correlates and improves metabolic models.

Nature communications
Knowing the catalytic turnover numbers of enzymes is essential for understanding the growth rate, proteome composition, and physiology of organisms, but experimental data on enzyme turnover numbers is sparse and noisy. Here, we demonstrate that machi...

Optimization and modelling of enzymatic polymerization of ε-caprolactone to polycaprolactone using Candida Antartica Lipase B with response surface methodology and artificial neural network.

Enzyme and microbial technology
Recently enzymatic catalysts have replaced organic and organometallic catalysts in the synthesis of bio-resorbable polymers. Enzymatic polymerization is considered as an alternative to conventional polymerization as they are less toxic, environmental...

Multiclassification Prediction of Enzymatic Reactions for Oxidoreductases and Hydrolases Using Reaction Fingerprints and Machine Learning Methods.

Journal of chemical information and modeling
Drug metabolism is a complex procedure in the human body, including a series of enzymatically catalyzed reactions. However, it is costly and time consuming to investigate drug metabolism experimentally; computational methods are hence developed to pr...

Ultrasound-assisted d-tartaric acid whole-cell bioconversion by recombinant Escherichia coli.

Ultrasonics sonochemistry
d-Tartaric acid has wide range of application in the pharmaceutical industry and scarcely exists in nature. In this study, cis-epoxysuccinate hydrolase (CESH)-containing Escherichia coli was used to perform whole-cell bioconversion of cis-epoxysuccin...

Manipulation of Biomolecule-Modified Liquid-Metal Blobs.

Angewandte Chemie (International ed. in English)
Soft and deformable liquid metals (LMs) are building components in various systems related to uncertain and dynamic task environments. Herein we describe the development of a biomolecule-triggered external-manipulation method involving LM conjugates ...

Engineering catalytically promiscuous enzymes to serve new functions.

Biotechnology advances
Catalytic promiscuity in enzymes refers to their ability to catalyze multiple chemically distinct reactions in addition to their native activity. The increasing discovery of additional enzymes exhibiting catalytic promiscuity has underscored the sign...

Catalytic mechanism and engineering of aromatic prenyltransferase: A review.

International journal of biological macromolecules
The prenylation of aromatic compounds significantly enhances their metabolic stability and bioactivity. Prenyltransferases, as essential biocatalysts, facilitate the regioselective transfer of prenyl groups from donors to aromatic substrates. This re...

Tackling a textbook example of multistep enzyme catalysis with deep learning-driven design.

Molecular cell
Enzyme design has struggled to emulate the complexity and catalytic proficiency of natural enzymes. Lauko et al. show that with the help of deep learning, the design of serine hydrolases that rival nature's ingenuity is possible.

Data-driven enzyme engineering to identify function-enhancing enzymes.

Protein engineering, design & selection : PEDS
Identifying function-enhancing enzyme variants is a 'holy grail' challenge in protein science because it will allow researchers to expand the biocatalytic toolbox for late-stage functionalization of drug-like molecules, environmental degradation of p...