(R)-Styrene oxide is a high-value chiral intermediate in pharmaceutical and chemical industries, yet its enantioselective synthesis remains challenging. Here, we engineered an epoxide hydrolase from Spatholobus suberectus (SsEH) to address its limita...
International journal of biological macromolecules
Jun 1, 2025
Predicting the functional impact of single-point mutations on protein residual activity, especially after high-temperature incubation, is critical in protein engineering. We present an innovative machine learning model based on eXtreme Gradient Boost...
International journal of biological macromolecules
Jun 1, 2025
Alpha-Galactosidase has significant industrial application value in food processing, animal nutrition and medical applications. Microbial-derived α-galactosidases predominate industrial implementation due to high productivity, yet their inherent ther...
International journal of biological macromolecules
Jun 1, 2025
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...
Human milk oligosaccharides (HMOs) play a pivotal role in infant health through their multifunctional bioactive properties. Recent advances in synthetic biology have revolutionized microbial platforms for HMO biosynthesis, with glycosyltransferases (...
Deep learning has advanced the design of static protein structures, but the controlled conformational changes that are hallmarks of natural signaling proteins have remained inaccessible to de novo design. Here, we describe a general deep learning-gui...
Machine learning (ML) tools have revolutionized protein structure prediction, engineering, and design, but the best ML tool is only as good as the training data it learns from. To obtain high-quality structural or functional data, protein purificatio...
International journal of molecular sciences
May 14, 2025
Engineered scaffold-based proteins that bind to concrete targets with high affinity offer significant advantages over traditional antibodies in theranostic applications. Their development often relies on display methods, where large libraries of vari...
The integration of high-throughput experimentation and machine learning is transforming data-driven antibody engineering, revolutionizing the discovery and optimization of antibody therapeutics. These approaches employ extensive datasets comprising a...
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.
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