AIMC Topic: Enzymes

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PreTKcat: A pre-trained representation learning and machine learning framework for predicting enzyme turnover number.

Computational biology and chemistry Jan 1, 2025
The enzyme turnover number (k) is crucial for understanding enzyme kinetics and optimizing biotechnological processes. However, experimentally measured k values are limited due to the high cost and labor intensity of wet-lab measurements, necessitati...
Kinetics Enzymes Machine Learning
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Deep Learning-Driven Insights into Enzyme-Substrate Interaction Discovery.

Journal of chemical information and modeling Dec 25, 2024
Enzymes are ubiquitous catalysts with enormous application potential in biomedicine, green chemistry, and biotechnology. However, accurately predicting whether a molecule serves as a substrate for a specific enzyme, especially for novel entities, rem...
Deep Learning Substrate Specificity Enzymes Neural Networks, Computer
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Improved enzyme functional annotation prediction using contrastive learning with structural inference.

Communications biology Dec 23, 2024
Recent years have witnessed the remarkable progress of deep learning within the realm of scientific disciplines, yielding a wealth of promising outcomes. A prominent challenge within this domain has been the task of predicting enzyme function, a comp...
Proteome Databases, Protein Computational Biology Enzymes Prochlorococcus Amino Acid Sequence Molecular Sequence Annotation Deep 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...
Molecular Dynamics Simulation Ligands Biocatalysis Enzymes Algorithms Deep Learning Machine Learning
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Parallel Convolutional Contrastive Learning Method for Enzyme Function Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
The function labeling of enzymes has a wide range of application value in the medical field, industrial biology and other fields. Scientists define enzyme categories by enzyme commission (EC) numbers. At present, although there are some tools for enz...
Enzymes Databases, Protein Machine Learning Neural Networks, Computer Algorithms Deep Learning Computational Biology
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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...
Proteins Enzymes Neural Networks, Computer Biocatalysis Machine Learning
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Enzymes from Fishery and Aquaculture Waste: Research Trends in the Era of Artificial Intelligence and Circular Bio-Economy.

Marine drugs Sep 10, 2024
In the era of the blue bio-economy, which promotes the sustainable utilization and exploitation of marine resources for economic growth and development, the fisheries and aquaculture industries still face huge sustainability issues. One of the major ...
Enzymes Fisheries Aquatic Organisms Industrial Waste Aquaculture Artificial Intelligence Animals Humans
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EnzChemRED, a rich enzyme chemistry relation extraction dataset.

Scientific data Sep 9, 2024
Expert curation is essential to capture knowledge of enzyme functions from the scientific literature in FAIR open knowledgebases but cannot keep pace with the rate of new discoveries and new publications. In this work we present EnzChemRED, for Enzym...
Databases, Protein Natural Language Processing Enzymes PubMed Knowledge Bases
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Approaching Optimal pH Enzyme Prediction with Large Language Models.

ACS synthetic biology Aug 28, 2024
Enzymes are widely used in biotechnology due to their ability to catalyze chemical reactions: food making, laundry, pharmaceutics, textile, brewing─all these areas benefit from utilizing various enzymes. Proton concentration (pH) is one of the key fa...
Enzymes Computer Simulation Machine Learning Hydrogen-Ion Concentration
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Multi-modal deep learning enables efficient and accurate annotation of enzymatic active sites.

Nature communications Aug 27, 2024
Annotating active sites in enzymes is crucial for advancing multiple fields including drug discovery, disease research, enzyme engineering, and synthetic biology. Despite the development of numerous automated annotation algorithms, a significant trad...
Catalytic Domain Molecular Sequence Annotation Databases, Protein Algorithms Deep Learning Enzymes Computational Biology
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