The catalytic mechanism of SalL chlorinase has been investigated by combining quantum mechanical/molecular mechanical (QM/MM) techniques and umbrella sampling simulations to compute free energy profiles. Our results shed light on the interesting fact that the substitution of chloride with fluorine in SalL chlorinase leads to a loss of halogenase activity. The potential of mean force based on DFTB3/MM analysis shows that fluorination corresponds to a barrier 13.5 kcal·mol higher than chlorination. Additionally, our results present a molecular description of SalL acting as a chlorinase instead of a methyl-halide transferase.
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http://dx.doi.org/10.1021/acs.jcim.9b01079 | DOI Listing |
Chem Sci
January 2025
State Key Laboratory of Physical Chemistry of Solid Surfaces and Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry College of Chemistry and Chemical Engineering, Xiamen University Xiamen 361005 China
Lytic polysaccharide monooxygenases (LPMOs) are a unique group of monocopper enzymes that exhibit remarkable ability to catalyze the oxidative cleavage of recalcitrant carbohydrate substrates, such as cellulose and chitin, by utilizing O or HO as the oxygen source. One of the key challenges in understanding the catalytic mechanism of LPMOs lies in deciphering how they activate dioxygen using diverse reductants. To shed light on this intricate process, we conducted in-depth investigations using quantum mechanical/molecular mechanical (QM/MM) metadynamics simulations, molecular dynamics (MD) simulations, and density functional theory (DFT) calculations.
View Article and Find Full Text PDFJ Chem Theory Comput
January 2025
Department of Chemistry and Biochemistry, University of Texas at Arlington, Arlington, Texas 76019, United States.
Integrating machine learning potentials (MLPs) with quantum mechanical/molecular mechanical (QM/MM) free energy simulations has emerged as a powerful approach for studying enzymatic catalysis. However, its practical application has been hindered by the time-consuming process of generating the necessary training, validation, and test data for MLP models through QM/MM simulations. Furthermore, the entire process needs to be repeated for each specific enzyme system and reaction.
View Article and Find Full Text PDFChembiochem
January 2025
Key Laboratory of Advanced Light Conversion Materials and Biophotonics, School of Chemistry and Life Resources, Renmin University of China, Beijing, 100872, China.
BTG13, a non-heme iron-dependent enzyme with a distinctive coordination environment of four histidines and a carboxylated lysine, has been found to catalyze the cleavage of the C4a-C10 bond in anthraquinone. Contrary to typical dioxygenase mechanisms, our quantum mechanical/molecular mechanical (QM/MM) calculations reveal that BTG13 functions more like a monooxygenase. It selectively inserts an oxygen atom into the C10-C4a bond, creating a lactone species that subsequently undergoes hydrolysis, leading to the formation of a ring-opened product.
View Article and Find Full Text PDFJ Phys Condens Matter
January 2025
Department of Physics, Research Institute for Biomimetics and Soft Matter, Jiujiang Research Institute and Fujian Provincial Key Laboratory for Soft Functional Materials Research, Xiamen University, Xiamen 361005, People's Republic of China.
Newly-synthesized structure T (sT) hydrate show promising practical applications in hydrogen storage and transport, yet the properties remain poorly understood. Here, we develop a machine learning potential (MLP) of sT hydrogen hydrate derived from quantum-mechanical molecular dynamics simulations. Using this MLP forcefield, the structural, hydrogen diffusion, mechanical and thermal properties of sT hydrogen hydrate are extensively explored.
View Article and Find Full Text PDFJ Chem Theory Comput
January 2025
The Graduate University for Advanced Studies (SOKENDAI), 38 Nishigo-Naka, Myodaiji, Okazaki, Aichi 444-8585, Japan.
The light-harvesting complex II (LHCII) in green plants exhibits highly efficient excitation energy transfer (EET). A comprehensive understanding of the EET mechanism in LHCII requires quantum chemical, molecular dynamics (MD), and statistical mechanics calculations that can adequately describe pigment molecules in heterogeneous environments. Herein, we develop MD simulation parameters that accurately reproduce the quantum mechanical/molecular mechanical energies of both the ground and excited states of all chlorophyll (Chl) molecules in membrane embedded LHCII.
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