AIMC Topic: Hydrolases

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Enzymatic carbon-fluorine bond cleavage by human gut microbes.

Proceedings of the National Academy of Sciences of the United States of America Jun 13, 2025
Fluorinated compounds are used for agrochemical, pharmaceutical, and numerous industrial applications, resulting in global contamination. In many molecules, fluorine is incorporated to enhance the half-life and improve bioavailability. Fluorinated co...
Gastrointestinal Microbiome Carbon Humans Hydrolases Fluorine Halogenation Bacterial Proteins Molecular Dynamics Simulation
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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 ...
Substrate Specificity Quantum Theory Hydrolysis Catalytic Domain Neural Networks, Computer Hydrolases Molecular Dynamics Simulation
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Biochemical and Computational Characterization of Haloalkane Dehalogenase Variants Designed by Generative AI: Accelerating the S2 Step.

Journal of the American Chemical Society Jan 10, 2025
Generative artificial intelligence (AI) models trained on natural protein sequences have been used to design functional enzymes. However, their ability to predict individual reaction steps in enzyme catalysis remains unclear, limiting the potential u...
Artificial Intelligence Kinetics Molecular Dynamics Simulation Hydrolases Protein Engineering
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Enabling high-throughput enzyme discovery and engineering with a low-cost, robot-assisted pipeline.

Scientific reports Jun 24, 2024
As genomic databases expand and artificial intelligence tools advance, there is a growing demand for efficient characterization of large numbers of proteins. To this end, here we describe a generalizable pipeline for high-throughput protein purificat...
High-Throughput Screening Assays Hydrolases Escherichia coli Robotics Protein Engineering Polyethylene Terephthalates Reproducibility of Results
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Semantic segmentation of urban environments: Leveraging U-Net deep learning model for cityscape image analysis.

PloS one Apr 5, 2024
Semantic segmentation of cityscapes via deep learning is an essential and game-changing research topic that offers a more nuanced comprehension of urban landscapes. Deep learning techniques tackle urban complexity and diversity, which unlocks a broad...
Deep Learning Image Processing, Computer-Assisted Semantics Hydrolases Empirical Research City Planning
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Survival prediction of glioblastoma patients using modern deep learning and machine learning techniques.

Scientific reports Jan 29, 2024
In this study, we utilized data from the Surveillance, Epidemiology, and End Results (SEER) database to predict the glioblastoma patients' survival outcomes. To assess dataset skewness and detect feature importance, we applied Pearson's second coeffi...
Databases, Factual Deep Learning Hydrolases Glioblastoma Humans Machine Learning
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Explainable artificial intelligence approaches for COVID-19 prognosis prediction using clinical markers.

Scientific reports Jan 20, 2024
The COVID-19 influenza emerged and proved to be fatal, causing millions of deaths worldwide. Vaccines were eventually discovered, effectively preventing the severe symptoms caused by the disease. However, some of the population (elderly and patients ...
Prognosis Aged Hydrolases Algorithms Biomarkers Artificial Intelligence Humans COVID-19
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RVCNet: A hybrid deep neural network framework for the diagnosis of lung diseases.

PloS one Dec 28, 2023
Early evaluation and diagnosis can significantly reduce the life-threatening nature of lung diseases. Computer-aided diagnostic systems (CADs) can help radiologists make more precise diagnoses and reduce misinterpretations in lung disease diagnosis. ...
Computer Systems COVID-19 Humans Hydrolases COVID-19 Testing Neural Networks, Computer Algorithms
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A knowledge-guided pre-training framework for improving molecular representation learning.

Nature communications Nov 21, 2023
Learning effective molecular feature representation to facilitate molecular property prediction is of great significance for drug discovery. Recently, there has been a surge of interest in pre-training graph neural networks (GNNs) via self-supervised...
Hydrolases Artificial Intelligence Electric Power Supplies Drug Discovery Anti-HIV Agents
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The use of artificial intelligence tools in cancer detection compared to the traditional diagnostic imaging methods: An overview of the systematic reviews.

PloS one Oct 5, 2023
BACKGROUND AND PURPOSE: In comparison to conventional medical imaging diagnostic modalities, the aim of this overview article is to analyze the accuracy of the application of Artificial Intelligence (AI) techniques in the identification and diagnosis...
Algorithms Adult Humans Artificial Intelligence Hydrolases Machine Learning Neoplasms Systematic Reviews as Topic
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