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Advances and Applications in Bioinformatics and Chemistry : AABC (1)
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Bertho, Gildas (2)
Evrard-Todeschi, Nathalie (2)
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Innamorato, Nadia G. (1)
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Structural and Functional Characterization of Nrf2 Degradation by the Glycogen Synthase Kinase 3/β-TrCP Axis
Rojo, Ana I.
Innamorato, Nadia G.
Tobón-Velasco, Julio C.
García-Mayoral, María Flor
Van Leuven, Fred
Hayes, John D.
Molecular and Cellular Biology
The transcription factor NF-E2-related factor 2 (Nrf2) is a master regulator of a genetic program, termed the phase 2 response, that controls redox homeostasis and participates in multiple aspects of physiology and pathology. Nrf2 protein stability is regulated by two E3 ubiquitin ligase adaptors, Keap1 and β-TrCP, the latter of which was only recently reported. Here, two-dimensional (2D) gel electrophoresis and site-directed mutagenesis allowed us to identify two serines of Nrf2 that are phosphorylated by glycogen synthase kinase 3β (GSK-3β) in the sequence DSGISL. Nuclear magnetic resonance studies defined key residues of this phosphosequence involved in docking to the WD40 propeller of β-TrCP, through electrostatic and hydrophobic interactions. We also identified three arginine residues of β-TrCP that participate in Nrf2 docking. Intraperitoneal injection of the GSK-3 inhibitor SB216763 led to increased Nrf2 and heme oxygenase-1 levels in liver and hippocampus. Moreover, mice with hippocampal absence of GSK-3β exhibited increased levels of Nrf2 and phase 2 gene products, reduced glutathione, and decreased levels of carbonylated proteins and malondialdehyde. This study establishes the structural parameters of the interaction of Nrf2 with the GSK-3/β-TrCP axis and its functional relevance in the regulation of Nrf2 by the signaling pathways that impinge on GSK-3.
Contact-based ligand-clustering approach for the identification of active compounds in virtual screening
Mantsyzov, Alexey B
Advances and Applications in Bioinformatics and Chemistry : AABC
Evaluation of docking results is one of the most important problems for virtual screening and in silico drug design. Modern approaches for the identification of active compounds in a large data set of docked molecules use energy scoring functions. One of the general and most significant limitations of these methods relates to inaccurate binding energy estimation, which results in false scoring of docked compounds. Automatic analysis of poses using self-organizing maps (AuPosSOM) represents an alternative approach for the evaluation of docking results based on the clustering of compounds by the similarity of their contacts with the receptor. A scoring function was developed for the identification of the active compounds in the AuPosSOM clustered dataset. In addition, the AuPosSOM efficiency for the clustering of compounds and the identification of key contacts considered as important for its activity, were also improved. Benchmark tests for several targets revealed that together with the developed scoring function, AuPosSOM represents a good alternative to the energy-based scoring functions for the evaluation of docking results.
scoring; docking; virtual screening; CAR; AuPosSOM
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