AIMC Topic: Biocatalysis

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ESM-Ezy: a deep learning strategy for the mining of novel multicopper oxidases with superior properties.

Nature communications Apr 6, 2025
The UniProt database is a valuable resource for biocatalyst discovery, yet predicting enzymatic functions remains challenging, especially for low-similarity sequences. Identifying superior enzymes with enhanced catalytic properties is even harder. To...
Deep Learning Data Mining Biocatalysis Oxidoreductases Databases, Protein Hydrogen-Ion Concentration
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Graphene-based FETs for advanced biocatalytic profiling: investigating heme peroxidase activity with machine learning insights.

Mikrochimica acta Mar 3, 2025
Graphene-based field-effect transistors (GFETs) are rapidly gaining recognition as powerful tools for biochemical analysis due to their exceptional sensitivity and specificity. In this study, we utilize a GFET system to explore the peroxidase-based b...
Horseradish Peroxidase Transistors, Electronic Biocatalysis Machine Learning Heme Graphite Hydrogen Peroxide
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Deep learning-driven semi-rational design in phenylalanine ammonia-lyase for enhanced catalytic efficiency.

International journal of biological macromolecules Feb 19, 2025
Phenylalanine ammonia-lyase (PAL) possesses significant potential in agriculture, industry, and the treatment of various diseases, including cancer. In particular, PAL derived from Anabaena variabilis (AvPAL) has been successfully utilized in clinica...
Biocatalysis Protein Engineering Kinetics Molecular Dynamics Simulation Phenylalanine Ammonia-Lyase Anabaena variabilis Deep Learning Catalysis Mutation
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Long-Range Electrostatics in Serine Proteases: Machine Learning-Driven Reaction Sampling Yields Insights for Enzyme Design.

Journal of chemical information and modeling Feb 10, 2025
Computational enzyme design is a promising technique for producing novel enzymes for industrial and clinical needs. A key challenge that this technique faces is to consistently achieve the desired activity. Fundamental studies of natural enzymes reve...
Machine Learning Models, Molecular Quantum Theory Protein Engineering Serine Proteases Biocatalysis Static Electricity Catalytic Domain
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Machine Learning Quantum Mechanical/Molecular Mechanical Potentials: Evaluating Transferability in Dihydrofolate Reductase-Catalyzed Reactions.

Journal of chemical theory and computation Jan 15, 2025
Integrating machine learning potentials (MLPs) with quantum mechanical/molecular mechanical (QM/MM) free energy simulations has emerged as a powerful approach for studying enzymatic catalysis. However, its practical application has been hindered by t...
Tetrahydrofolate Dehydrogenase Biocatalysis Thermodynamics Molecular Dynamics Simulation Quantum Theory Machine Learning
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BioStructNet: Structure-Based Network with Transfer Learning for Predicting Biocatalyst Functions.

Journal of chemical theory and computation Dec 20, 2024
Enzyme-substrate interactions are essential to both biological processes and industrial applications. Advanced machine learning techniques have significantly accelerated biocatalysis research, revolutionizing the prediction of biocatalytic activities...
Machine Learning Deep Learning Molecular Dynamics Simulation Algorithms Ligands Enzymes Biocatalysis
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Protein representations: Encoding biological information for machine learning in biocatalysis.

Biotechnology advances Oct 2, 2024
Enzymes offer a more environmentally friendly and low-impact solution to conventional chemistry, but they often require additional engineering for their application in industrial settings, an endeavour that is challenging and laborious. To address th...
Machine Learning Proteins Enzymes Biocatalysis Neural Networks, Computer
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On synergy between ultrahigh throughput screening and machine learning in biocatalyst engineering.

Faraday discussions Sep 11, 2024
Protein design and directed evolution have separately contributed enormously to protein engineering. Without being mutually exclusive, the former relies on computation from first principles, while the latter is a combinatorial approach based on chanc...
Protein Engineering High-Throughput Screening Assays Machine Learning Biocatalysis
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Navigating the landscape of enzyme design: from molecular simulations to machine learning.

Chemical Society reviews Aug 12, 2024
Global environmental issues and sustainable development call for new technologies for fine chemical synthesis and waste valorization. Biocatalysis has attracted great attention as the alternative to the traditional organic synthesis. However, it is c...
Animals Enzymes Molecular Dynamics Simulation Humans Machine Learning Enzyme Activation Biocatalysis Substrate Specificity Protein Conformation Protein Engineering
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Machine learning-guided co-optimization of fitness and diversity facilitates combinatorial library design in enzyme engineering.

Nature communications Jul 29, 2024
The effective design of combinatorial libraries to balance fitness and diversity facilitates the engineering of useful enzyme functions, particularly those that are poorly characterized or unknown in biology. We introduce MODIFY, a machine learning (...
Directed Molecular Evolution Protein Engineering Mutation Gene Library Machine Learning Biocatalysis Enzymes Algorithms
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