A Computational Modeling Approach Predicts Interaction of the Antifungal Protein AFP from Aspergillus giganteus with Fungal Membranes via Its γ-Core Motif

Fungal pathogens kill more people per year globally than malaria or tuberculosis and threaten international food security through crop destruction. New sophisticated strategies to inhibit fungal growth are thus urgently needed. Among the potential candidate molecules that strongly inhibit fungal spo...

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Veröffentlicht in:	mSphere 2018-10, Vol.3 (5)
Hauptverfasser:	Utesch, Tillmann, de Miguel Catalina, Alejandra, Schattenberg, Caspar, Paege, Norman, Schmieder, Peter, Krause, Eberhard, Miao, Yinglong, McCammon, J Andrew, Meyer, Vera, Jung, Sascha, Mroginski, Maria Andrea
Format:	Artikel
Sprache:	eng
Schlagworte:	Amino acids Antifungal agents Antifungal Agents - pharmacology Aspergillus Aspergillus - classification Aspergillus - metabolism Aspergillus niger - drug effects Biological activity Biotechnology industry Cell Membrane Permeability - drug effects Chemical bonds Chromatography Computer applications Computer Simulation Food security Fungal Proteins - isolation & purification Fungal Proteins - pharmacology Fungi Fungicides Isomers Magnetic Resonance Spectroscopy Malaria Mammals Mass spectrometry Membrane proteins Membranes Microbial Sensitivity Tests Molecular dynamics Molecular Dynamics Simulation NMR Nuclear magnetic resonance Pathogens Peptides Plant cells Plasma membranes Proteins Scientific imaging Simulation Software Spectroscopy Spore germination Therapeutics and Prevention Tuberculosis
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