AI-driven engineering of EgtD enabling high-efficiency ergothioneine synthesis with a multi-enzyme cascade.

Ergothioneine (ERG), a sulfur-containing natural antioxidant with significant biomedical potentials, has long been limited by low productivity in microbial fermentation. Here, we report the first high-efficiency in vitro reconstruction of a multi-enzyme cascade for ERG biosynthesis. To address the rate-limiting histidine methylation step, we employed a synergistic strategy integrating machine learning-based kinetic prediction (CataPro, DLkcat), molecular dynamics simulations, and conformational dynamics analysis to guide site-directed mutagenesis of Mycolicibacrterium smegmatis EgtD.

Structural insights and rational engineering strategies for modular polyketide synthases: A review.

Polyketide synthases (PKSs) are among the most complex enzymatic systems in nature, responsible for synthesizing a broad array of polyketides including antibiotics, antifungal agents, and immunosuppressants. Cis-Acyltransferase (AT) PKSs, distinguished by their multiple modules, diverse catalytic domains, and engineering flexibility, hold significant promise for synthetic biology and natural product discovery. However, even minor alterations to individual domains can propagate structural and functional changes throughout the assembly line, posing a major challenge to the rational design of cis-AT PKSs for diverse polyketides production.

Sirtuin 1/sirtuin 3 are robust lysine delactylases and sirtuin 1-mediated delactylation regulates glycolysis.

Lysine lactylation (Kla), an epigenetic mark triggered by lactate during glycolysis, including the Warburg effect, bridges metabolism and gene regulation. Enzymes such as p300 and HDAC1/3 have been pivotal in deciphering the regulatory dynamics of Kla, though questions about additional regulatory enzymes, their specific Kla substrates, and the underlying functional mechanisms persist. Here, we identify SIRT1 and SIRT3 as key "erasers" of Kla, shedding light on their selective regulation of both histone and non-histone proteins.

off-target profiling for enhanced drug safety assessment.

Ensuring drug safety in the early stages of drug development is crucial to avoid costly failures in subsequent phases. However, the economic burden associated with detecting drug off-targets and potential side effects through safety screening and animal testing is substantial. Drug off-target interactions, along with the adverse drug reactions they induce, are significant factors affecting drug safety.

An overview of recent advances and challenges in predicting compound-protein interaction (CPI).

Compound-protein interactions (CPIs) are critical in drug discovery for identifying therapeutic targets, drug side effects, and repurposing existing drugs. Machine learning (ML) algorithms have emerged as powerful tools for CPI prediction, offering notable advantages in cost-effectiveness and efficiency. This review provides an overview of recent advances in both structure-based and non-structure-based CPI prediction ML models, highlighting their performance and achievements.

Efficient chiral synthesis by Saccharomyces cerevisiae spore encapsulation of Candida parapsilosis Glu228Ser/(S)-carbonyl reductase II and Bacillus sp. YX-1 glucose dehydrogenase in organic solvents.

Background: Saccharomyces cerevisiae AN120 osw2∆ spores were used as a host with good resistance to unfavorable environment. This work was undertaken to develop a new yeast spore-encapsulation of Candida parapsilosis Glu228Ser/(S)-carbonyl reductase II and Bacillus sp. YX-1 glucose dehydrogenase for efficient chiral synthesis in organic solvents.