The generation of surrogate potential energy functions (PEF) that are orders of magnitude faster to compute but as accurate as the underlying training data from high-level electronic structure methods is one of the most promising applications of fitting procedures in chemistry. In previous work, we have shown that transition state force fields (TSFFs), fitted to the functional form of MM3* force fields using the quantum guided molecular mechanics (Q2MM) method, provide an accurate description of transition states that can be used for stereoselectivity predictions of small molecule reactions. Here, we demonstrate the applicability of the method for fit TSFFs to the well-established Amber force field, which could be used for molecular dynamics studies of enzyme reaction. As a case study, the fitting of a TSFF to the second hydride transfer in Pseudomonas mevalonii 3-hydroxy-3-methylglutaryl coenzyme A reductase (PmHMGR) is used. The differences and similarities to fitting of small molecule TSFFs are discussed.
The Ebola Virus (EBOV) is a deadly virus first identified in 1976 from the Ebola River region of Zaire (presently the Democratic Republic of Congo). EBOV is known for causing viral hemorrhagic fever and it can cause a high mortality rate in infected patients. VP40 is the matrix protein of EBOV (eVP40), which has an N‐terminal domain responsible for dimerization and oligomerization of the protein to form filaments of dimers at the plasma membrane inner leaflet of the host cell. The eVP40 dimerization and filament formation is necessary for viral budding from the host cell membrane. This project aims to investigate which amino acid residues in this N‐terminal dimerization domain are necessary for the protein to be able to oligomerize at the plasma membrane inner leaflet. First, computational screens were performed to determine which residues may play a role in dimerization, and then mutant plasmids with changes at these residues harboring a green fluorescent protein tag were created. Based on the computational screen, we hypothesized amino acid residues Arg52, Ile54, Ala55, Asp56, Asp57, and His61 would be essential for dimerization of eVP40. Mutants of these residues were then transfected into Cos‐7 cells and imaged using confocal microscopy and compared to WT eVP40. Cellular images were analyzed using ImageJ to determine the amount of fluorescently‐tagged protein present at the plasma membrane. Confocal imaging confirmed our central hypothesis and the computational data as these mutations had a significant loss of eVP40 plasma membrane localization. The next steps in this project will be to perform virus‐like particle (VLP) collection to further analyze the effects of point mutations on the dimerization domain as it relates to VLP formation budding out of the host cell.
Thiohemiacetals are key intermediates in the active sites of many enzymes catalyzing a variety of reactions. In the case of Pseudomonas mevalonii 3-hydroxy-3-methylglutaryl coenzyme A reductase (PmHMGR), this intermediate connects the two hydride transfer steps where a thiohemiacetal is the product of the first hydride transfer and its breakdown forms the substrate of the second one, serving as the intermediate during cofactor exchange. Despite the many examples of thiohemiacetals in a variety of enzymatic reactions, there are few studies that detail their reactivity. Here, we present computational studies on the decomposition of the thiohemiacetal intermediate in PmHMGR using both QM-cluster and QM/MM models. This reaction mechanism involves a proton transfer from the substrate hydroxyl to an anionic Glu83 followed by a C−S bond elongation stabilized by a cationic His381. The reaction provides insight into the varying roles of the residues in the active site that favor this multistep mechanism.
The application of the Quantum Guided Molecular Mechanics (Q2MM) method to transition states of enzymatic reactions to generate a transition state force field (TSFF) with the functional form of AMBER. The differences to fitting of small-molecule TSFFs and the similarities of the approach to transfer learning are discussed. The application to the transition state of the second hydride transfer in HMGCoA Reductase from Pseudomonas mevalonii is discussed. <br><br>
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