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Neuronal differentiation is regulated by nerve growth factor (NGF) and other neurotrophins. We explored the impact of NGF on mitochondrial dynamics and metabolism through time-lapse imaging, metabolomics profiling, and computer modeling studies. We show that NGF may direct differentiation by stimulating fission, thereby causing selective mitochondrial network fragmentation and mitophagy, ultimately leading to increased mitochondrial quality and respiration. Then, we reconstructed the dynamic fusion-fission-mitophagy cycling of mitochondria in a computer model, integrating these processes into a single network mechanism. Both the computational model and the simulations are able to reproduce the proposed mechanism in terms of mitochondrial dynamics, levels of reactive oxygen species (ROS), mitophagy, and mitochondrial quality, thus providing a computational tool for the interpretation of the experimental data and for future studies aiming to detail further the action of NGF on mitochondrial processes. We also show that changes in these mitochondrial processes are intertwined with a metabolic function of NGF in differentiation: NGF directs a profound metabolic rearrangement involving glycolysis, TCA cycle, and the pentose phosphate pathway, altering the redox balance. This metabolic rewiring may ensure: (a) supply of both energy and building blocks for the anabolic processes needed for morphological reorganization, as well as (b) redox homeostasis., (© 2024 The Authors. The FEBS Journal published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

The Michaelis-Menten equation is one of the most extensively used models in biochemistry for studying enzyme kinetics. However, this model requires at least a couple (e.g., eight or more) of measurements at different substrate concentrations to determine kinetic parameters. Here, we report the discovery of a novel tool for calculating kinetic constants in the Michaelis-Menten equation from only a single enzymatic assay. As a consequence, our method leads to reduced costs and time, primarily by lowering the amount of enzymes, since their isolation, storage and usage can be challenging when conducting research., (© 2019 The Authors. FEBS Letters published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

De novo designed helix-loop-helix peptide foldamers containing cis-2-aminocyclopentanecarboxylic acid residues were evaluated for their conformational stability and possible use in enzyme mimetic development. The correlation between hydrogen bond network size and conformational stability was demonstrated through CD and NMR spectroscopies. Molecules incorporating a Cys/His/Glu triad exhibited enzyme-like hydrolytic activity., (Copyright © 2018 Elsevier Inc. All rights reserved.)

The potent transcription inhibitor Actinomycin D is used with several cancers. Here, we report the discovery that this naturally occurring antibiotic inhibits two human neutral aminopeptidases, the cell-surface alanine aminopeptidase and intracellular methionine aminopeptidase type 2. These metallo-containing exopeptidases participate in tumor cell expansion and motility and are targets for anticancer therapies. We show that the peptide portions of Actinomycin D and Actinomycin X 2 are not required for effective inhibition, but the loss of these regions changes the mechanism of interaction. Two structurally less complex Actinomycin D analogs containing the phenoxazone chromophores, Questiomycin A and Actinocin, appear to be competitive inhibitors of both aminopeptidases, with potencies similar to the non-competitive macrocyclic parent compound ( K i in the micromolar range). The mode of action for all four compounds and both enzymes was demonstrated by molecular modeling and docking in the corresponding active sites. This knowledge gives new perspectives to Actinomycin D's action on tumors and suggests new avenues and molecules for medical applications., Competing Interests: CONFLICTS OF INTEREST The authors declare no conflicts of interest.