Protein engineering has recently seen tremendous transformation due to machine learning (ML) tools that predict structure from sequence at unprecedented precision. Predicting catalytic activity, however, remains challenging, restricting our capabilit...
Angewandte Chemie (International ed. in English)
Jun 8, 2025
Typical nanopore sensing depends on slowed translocation through the pore to acquire effective blockade signals. However, this paradigm often suffers from low signal precision and poor resolution, making it challenging to resolve pools of analytes wi...
We present a protein engineering approach to directed evolution with machine learning that integrates a new semi-supervised neural network fitness prediction model, Seq2Fitness, and an innovative optimization algorithm, biphasic annealing for diverse...
Journal of chemical information and modeling
May 26, 2025
Computational protein design (CPD) refers to the use of computational methods to design proteins. Traditional methods relying on energy functions and heuristic algorithms for sequence design are inefficient and do not meet the demands of the big data...
Machine learning applications in protein sciences have ushered in a new era for designing molecules in silico. Antibodies, which currently form the largest group of biologics in clinical use, stand to benefit greatly from this shift. Despite the prol...
Previously, a glycoside hydrolase (GH) family 2 β-galactosidase (PbBGal2A) from Paenibacillus barengoltzii is characterized for its high transglycosylation capability. Here, the cryo-electron microscopy (cryo-EM) structure of PbBGal2A was determined,...
Accurate prediction of enzyme kinetic parameters is crucial for enzyme exploration and modification. Existing models face the problem of either low accuracy or poor generalization ability due to overfitting. In this work, we first developed unbiased ...
Optimizing enzymes to function in novel chemical environments is a central goal of synthetic biology, but optimization is often hindered by a rugged fitness landscape and costly experiments. In this work, we present TeleProt, a machine learning (ML) ...
Journal of agricultural and food chemistry
Mar 11, 2025
Since the structure of enzymes determines their function, elucidating the structure of enzymes lays a solid foundation for deciphering their catalytic mechanism and enabling rational design. The development of artificial intelligence (AI) has sparked...
Terpenoids, also known as isoprenoids, represent the largest and most structurally diverse family of natural products, and their biosynthesis is closely related to cytochrome P450 enzymes (P450s). Given the limitations of direct extraction from natur...
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