AIMC Topic: Oxidoreductases

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Recent Advances in Oxidase-like Nanozymes: Mechanisms, Prediction Models, and Applications.

ACS applied materials & interfaces
Nanozymes, defined as nanomaterials exhibiting intrinsic enzyme-like catalytic properties, represent a rapidly expanding interdisciplinary frontier. Since the initial discovery of peroxidase-like nanozymes, a wide variety of nanomaterials have demons...

Engineering a Metal-Organic Framework-Dominated Bioinspired Multienzymatic Sensor Array for Portable Detection of Perfluoroalkyl Substances.

Analytical chemistry
Accurate identification of perfluoroalkyl substances (PFASs) is essential for environmental regulation and public health protection. However, current analytical techniques struggle to differentiate PFASs due to their structural similarity. Herein, we...

Machine learning reveals genes impacting oxidative stress resistance across yeasts.

Nature communications
Reactive oxygen species (ROS) are highly reactive molecules encountered by yeasts during routine metabolism and during interactions with other organisms, including host infection. Here, we characterize the variation in resistance to the ROS-inducing ...

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

Nature communications
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...

Design and performance analysis of multi-enzyme activity-doped nanozymes assisted by machine learning.

Colloids and surfaces. B, Biointerfaces
Traditional design approaches for nanozymes typically rely on empirical methods and trial-and-error, which hampers systematic optimization of their structure and performance, thus limiting the efficiency of developing innovative nanozymes. This study...

AI-Powered Knowledge Base Enables Transparent Prediction of Nanozyme Multiple Catalytic Activity.

The journal of physical chemistry letters
Nanozymes are unique materials with many valuable properties for applications in biomedicine, biosensing, environmental monitoring, and beyond. In this work, we developed a machine learning (ML) approach to search for new nanozymes and deployed a web...

Machine learning assisted methods for the identification of low toxicity inhibitors of Enoyl-Acyl Carrier Protein Reductase (InhA).

Computational biology and chemistry
Tuberculosis (TB) is one of the life-threatening infectious diseases with prehistoric origins and occurs in almost all habitable parts of the world. TB mainly affects the lungs, and its etiological agent is Mycobacterium tuberculosis (Mtb). In 2022, ...

NIFtHool: an informatics program for identification of NifH proteins using deep neural networks.

F1000Research
Atmospheric nitrogen fixation carried out by microorganisms has environmental and industrial importance, related to the increase of soil fertility and productivity. The present work proposes the development of a new high precision system that allows ...

Generating functional protein variants with variational autoencoders.

PLoS computational biology
The vast expansion of protein sequence databases provides an opportunity for new protein design approaches which seek to learn the sequence-function relationship directly from natural sequence variation. Deep generative models trained on protein sequ...

Effects of corn straw on dissipation of polycyclic aromatic hydrocarbons and potential application of backpropagation artificial neural network prediction model for PAHs bioremediation.

Ecotoxicology and environmental safety
In order to provide a viable option for remediation of PAHs-contaminated soils, a greenhouse experiment was conducted to assess the effect of corn straw amendment (1%, 2%, 4% or 6%, w/w) on dissipation of aged polycyclic aromatic hydrocarbons (PAHs) ...