In-silico characterization of GPx4 and mutant structures to investigate potential critical residues

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ID: 285005
2023
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Abstract
Glutathione Peroxidase 4 (GPx4) is a critical enzyme for survival due it being the sole enzyme responsible for repairing oxidative damage that accumulates in the membrane. To this end, it has a number of structural features that allow it to accommodate a variety of substrates, as well as be potentially allosterically regulated. Few studies have characterized the overall GPx4 enzyme in terms of overall structural features and relationships between these. This study aimed to characterize GPx4 using protein structural analysis techniques, particularly Protein Energy Networks (PENs).Three GPx4 variants were generated - U46C (treated as the WT), D21A, and R152H, and 100 ns MD simulation trajectories were generated using GROMACS. Resulting trajectories were analyzed using gRINN to investigate highly residues and shortest paths, and VMD was used to analyze H-bonds. Centrality and shortest paths analysis highlights the binding site and allosteric site as highly central for the WT, and suggests that allosteric regulation may be due to communication between these two sites. A number of critical residues (Lys31, Asp101, Lys140) were determined to be critical for for the aforementioned WT, with the latter two participating in a frequently occurring shortest path (Asp101-Leu71-Val39-Lys140) that is driven by a combination of hydrophobic and h-bond interactions. Lys140 is further highlighted due to its frequent occurrence in paths between all three sites. Mutations also highlight the electrostatic interactions, with changes in paths of electrostatic interactions involving Asp21 for both mutants. These insights offer new perspectives into GPx4 structure, particularly highlighting the binding and active sites as critical for information transfer. Such may influence future efforts in drug discovery and enzyme inhibition or activation. Keywords: Glutathione Peroxidase 4 (GPx4), Network Analysis, Protein Energy Networks, Shortest Paths, Allosteric Activation, Mutants
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persistent_1760654337_68f17401c27fa Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Cervania, Cameron Niro
Journal Malay Journal
Year 2023
DOI
DOI not found
URL
https://animorepository.dlsu.edu.ph/etdb_chem/32
Keywords Keywords not found

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