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Projekt Druckansicht

Entwurf neuer Arginase 1 Inhibitoren zur Wiederherstellung der antitumoralen Immunantwort

Fachliche Zuordnung Pharmazie
Förderung Förderung von 2013 bis 2017
Projektkennung Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 244857959
 
Erstellungsjahr 2017

Zusammenfassung der Projektergebnisse

The aim of this project was to better understand molecular mechanisms of arginase inhibition in order to support the design of molecules able to modulate its activity. For this purpose, a careful computer-aided structural investigation of Arginase was conducted. Using molecular dynamics (MD) simulations in the microsecond range, key regions of the protein active site were identified and their flexibility was evaluated and compared. A cavity opening phenomenon was observed, involving three loops directly interacting with all known ligands, while metal coordinating regions remained motionless. In the frame of this work, a novel dynamic 3D-pharmacophore analysis method termed Dynophores was developed that allows for the construction of a single 3D-model comprising all ligand-enzyme interactions occurring throughout a complete MD trajectory. This new technique for the in silico study of intermolecular interactions allows for loop flexibility analysis coupled with movements and conformational changes of bound ligands. Presented MD studies highlight the plasticity of the size of the arginase active site, leading to the hypothesis that larger ligands can enter the cavity of arginase. The experimental testing of a targeted fragment library substituted by different aliphatic groups validated this hypothesis. The structural information reported in this study will inspire the design of the next arginase inhibitors and encourage medicinal chemists to consider protein flexibility in the frame of structure-based drug design approaches. Further application of the Dynophore tool will be useful for researchers interested in intermolecular interaction analysis and for rational drug design.

Projektbezogene Publikationen (Auswahl)

  • Computational close up on protein–protein interactions: how to unravel the invisible using molecular dynamics simulations? WIREs Comput Mol Sci, 5(5):345-359, 2015
    C. Rakers, M. Bermudez, B. G. Keller, J. Mortier, and G. Wolber
    (Siehe online unter https://doi.org/10.1002/wcms.1222)
  • The impact of molecular dynamics on drug design: applications for the characterization of ligandmacromolecule complexes, Drug Discov Today, 20(6):686-702, 2015
    J. Mortier, C. Rakers, M. Bermudez, M. S. Murgueitio, S. Riniker, and G. Wolber
    (Siehe online unter https://doi.org/10.1016/j.drudis.2015.01.003)
  • Ligand Binding Ensembles Determine Graded Agonist Efficacies at a G Protein-coupled Receptor, J Biol Chem, 291(31):16375-16389, 2016
    A. Bock, M. Bermudez, F. Krebs, C. Matera, B. Chirinda, D. Sydow, C. Dallanoce, U. Holzgrabe, M. De Amici, M. J. Lohse, G. Wolber, and K. Mohr
    (Siehe online unter https://doi.org/10.1074/jbc.M116.735431)
  • More than a look into a crystal ball: protein structure elucidation guided by molecular dynamics simulations, Drug Discov Today, 21(11):1799-1805, 2016
    M. Bermudez, J. Mortier, C. Rakers, D. Sydow, and G. Wolber
    (Siehe online unter https://doi.org/10.1016/j.drudis.2016.07.001)
  • Arginase Structure and Inhibition: Catalytic Site Plasticity Reveals New Modulation Possibilities, Nature Scientific Reports, 7(1):13616, 2017
    J. Mortier, J. R. C. Prévost, D. Sydow, S. Teuchert, C. Omieczynski, M. Bermudez, R. Frédérick, and G. Wolber
    (Siehe online unter https://dx.doi.org/10.1038/s41598-017-13366-4)
 
 

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