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Enzymatic malonylation of natural glycosides provides a promising alternative method for drug-like malonylated glycosides supply. However, the catalytic potential and structural basis of plant malonyltransferase are far from being fully elucidated. This work identified a new malonyltransferase CtMaT1 from It displayed unprecedented mono- and/or di-malonylation activity toward diverse glucosides with different aglycons. A "one-pot" system by CtMaT1 and a malonyl-CoA synthetase was established to biosynthesize nine new malonylated glucosides. Structural investigations revealed that CtMaT1 possesses an adequately spacious acyl-acceptor pocket capable of accommodating diverse glucosides. Additionally, it recognizes malonyl-CoA through strong electrotactic and hydrogen interactions. QM/MM calculation revealed the H167-mediated 2 reaction mechanism of CtMaT1, while dynamic simulations detected the formation of stable hydrogen bonds between the glucose-6-OH group and H167, resulting in its high malonylation regiospecificity. Calculated energy profiles of two isomeric glycosides highlighted lower reaction energy barriers towards glucoside substrates, emphasizing CtMaT1's preference for glucosides. Furthermore, a mutant CtMaT1 with notably increased di-malonylation activity was obtained. The underlying molecular mechanism was illuminated through MM/GBSA binding free energy calculation. This study significantly advances the understanding of plant acyltransferases from both functional and protein structural perspectives, while also providing a versatile tool for enzymatic malonylation applications in pharmacology.
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http://dx.doi.org/10.1016/j.apsb.2024.02.007 | DOI Listing |
Microb Cell Fact
July 2025
Key Laboratory of Microbiological Metrology, Measurement & Bio-Product Quality Security, State Administration for Market Regulation, College of Life Sciences, China Jiliang University, Xueyuan Street, Xiasha Higher Education District, Hangzhou, 310018, Zhejiang Province, P.R. China.
Background: We previously identified a regulator NsdA, which negatively regulated rimocidin biosynthesis in Streptomyces rimosus M527. However, the exact regulatory mechanism of NsdA on rimocidin production remains unknown.
Results: In this study, firstly, transcriptomic data demonstrated that the differentially expressed genes resulting from the over-expression of nsdA were primarily associated with several key metabolic pathways, including glycolysis, oxidative phosphorylation, and ribosome-related genes, all of which were downregulated.
J Proteomics
May 2025
Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening, College of Pharmacy, Jiangsu Ocean University, Lianyungang, China; Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Guangdong, China; Guangzhou University of Chinese Medicine
Staphylococcus aureus (S. aureus) is a major pathogen whose post-translational modifications (PTMs) regulate key biological processes that exert a substantial impact on protein function within this pathogen. In this study, we comprehensively analyzed the overall patterns of three lysine acylation in S.
View Article and Find Full Text PDFFront Microbiol
December 2024
School of Chinese Materia Medica, Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China.
Zhongguo Zhong Yao Za Zhi
September 2024
Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700, China.
The activity of rare saponins is generally better than that of their prototypes. There are significant differences in the proportions and pharmacological effects of rare saponins/prototype saponins in Gynostemma pentaphyllum samples dried with different methods, which may be related to the reaction catalyzed by glucosidase. To explore the pattern of the enzymatic reaction catalyzed by glucosidase during the processing of G.
View Article and Find Full Text PDFSci Rep
November 2024
Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Nara, 8916-5, Japan.
The discrepancy between model predictions and actual processes, known as process-model mismatch (PMM), remains a substantial challenge in bioprocess optimization. We previously introduced a hybrid in silico/in-cell controller (HISICC) that combines model-based optimization with cell-based feedback to address this problem. Here, we extended this approach to regulate a key enzyme level using intracellular biosensing.
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