Glycosyltransferases catalyze the formation of glycosidic bonds by assisting the transfer of a sugar residue from donors to specific acceptor molecules. Although structural and kinetic data have provided insight into mechanistic strategies employed by these enzymes, molecular modeling studies are essential for the understanding of glycosyltransferase catalyzed reactions at the atomistic level. For such modeling, combined quantum mechanics/molecular mechanics (QM/MM) methods have emerged as crucial. These methods allow the modeling of enzymatic reactions by using quantum mechanical methods for the calculation of the electronic structure of the active site models and treating the remaining enzyme environment by faster molecular mechanics methods. Herein, the application of QM/MM methods to glycosyltransferase catalyzed reactions is reviewed, and the insight from modeling of glycosyl transfer into the mechanisms and transition states structures of both inverting and retaining glycosyltransferases are discussed.
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http://dx.doi.org/10.1016/j.carres.2014.06.017 | DOI Listing |
Biochemistry
December 2024
Key Laboratory of Theoretical and Computational Photochemistry, Ministry of Education, College of Chemistry, Beijing Normal University, Beijing 100875, China.
Large Stokes shift red fluorescent proteins (LSS-RFPs) are of growing interest for multicolor bioimaging applications. However, their photochemical mechanisms are not fully understood. Here, we employed the QM(XDW-CASPT2//CASSCF)/MM method to investigate the excited-state proton transfer and photoisomerization processes of the LSS-RFP mKeima starting from its cis neutral isomer.
View Article and Find Full Text PDFJ Chem Theory Comput
December 2024
Aix Marseille Univ, CNRS, ICR, 13397 Marseille, France.
Electronic polarization and dispersion are decisive actors in determining interaction energies between molecules. These interactions have a particularly profound effect on excitation energies of molecules in complex environments, especially when the excitation involves a significant degree of charge reorganization. The direct reaction field (DRF) approach, which has seen a recent revival of interest, provides a powerful framework for describing these interactions in quantum mechanics/molecular mechanics (QM/MM) models of systems, where a small subsystem of interest is described using quantum chemical methods and the remainder is treated with a simple MM force field.
View Article and Find Full Text PDFCancers (Basel)
November 2024
Center of Artificial Intelligence in Precision Medicines, King Abdulaziz University, Jeddah 22254, Saudi Arabia.
Background/objectives: Human epidermal growth factor receptor 2 (HER2) is overexpressed in several malignancies, such as breast, gastric, ovarian, and lung cancers, where it promotes aggressive tumor proliferation and unfavorable prognosis. Targeting HER2 has thus emerged as a crucial therapeutic strategy, particularly for HER2-positive malignancies. The present study focusses on the design and optimization of peptide inhibitors targeting HER2, utilizing machine learning to identify and enhance peptide candidates with elevated binding affinities.
View Article and Find Full Text PDFJ Comput Chem
January 2025
Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr, Germany.
This paper reports the improvement in the efficiency of embedded-cluster model (ECM) calculations in ORCA thanks to the implementation of the fast multipole method. Our implementation is based on state-of-the-art algorithms and revisits certain aspects, such as efficiently and accurately handling the extent of atomic orbital shell pairs. This enables us to decompose near-field and far-field terms in what we believe is a simple and effective manner.
View Article and Find Full Text PDFJ Phys Chem B
December 2024
Aix Marseille Univ, CNRS, ICR, 13013 Marseille, France.
The automatic rhodopsin modeling (ARM) approach is a computational workflow devised for the automatic buildup of hybrid quantum mechanics/molecular mechanics (QM/MM) models of wild-type rhodopsins and mutants, with the purpose of establishing trends in their photophysical and photochemical properties. Despite the success of ARM in accurately describing the visible light absorption maxima of many rhodopsins, for a few cases, called outliers, it might lead to large deviations with respect to experiments. Applying ARM to rhodopsin (GR), a microbial rhodopsin with important applications in optogenetics, we analyze the origin of such outliers in the absorption energies obtained for GR wild-type and mutants at neutral pH, with a total root-mean-square deviation (RMSD) of 0.
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