A Computational Modeling Approach Predicts Interaction of the Antifungal Protein AFP from <italic toggle="yes">Aspergillus giganteus</italic> with Fungal Membranes via Its γ-Core Motif

ABSTRACT 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 f...

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Autores principales: Tillmann Utesch, Alejandra de Miguel Catalina, Caspar Schattenberg, Norman Paege, Peter Schmieder, Eberhard Krause, Yinglong Miao, J. Andrew McCammon, Vera Meyer, Sascha Jung, Maria Andrea Mroginski
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Publicado: American Society for Microbiology 2018
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spelling oai:doaj.org-article:9c629bbaa8484a38b76934cafd8d76452021-11-15T15:22:26ZA Computational Modeling Approach Predicts Interaction of the Antifungal Protein AFP from <italic toggle="yes">Aspergillus giganteus</italic> with Fungal Membranes via Its γ-Core Motif10.1128/mSphere.00377-182379-5042https://doaj.org/article/9c629bbaa8484a38b76934cafd8d76452018-10-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSphere.00377-18https://doaj.org/toc/2379-5042ABSTRACT 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 spore germination are small cationic, cysteine-stabilized proteins of the AFP family secreted by a group of filamentous Ascomycetes. Its founding member, AFP from Aspergillus giganteus, is of particular interest since it selectively inhibits the growth of filamentous fungi without affecting the viability of mammalian, plant, or bacterial cells. AFPs are also characterized by their high efficacy and stability. Thus, AFP can serve as a lead compound for the development of novel antifungals. Notably, all members of the AFP family comprise a γ-core motif which is conserved in all antimicrobial proteins from pro- and eukaryotes and known to interfere with the integrity of cytoplasmic plasma membranes. In this study, we used classical molecular dynamics simulations combined with wet laboratory experiments and nuclear magnetic resonance (NMR) spectroscopy to characterize the structure and dynamical behavior of AFP isomers in solution and their interaction with fungal model membranes. We demonstrate that the γ-core motif of structurally conserved AFP is the key for its membrane interaction, thus verifying for the first time that the conserved γ-core motif of antimicrobial proteins is directly involved in protein-membrane interactions. Furthermore, molecular dynamic simulations suggested that AFP does not destroy the fungal membrane by pore formation but covers its surface in a well-defined manner, using a multistep mechanism to destroy the membranes integrity. IMPORTANCE Fungal pathogens pose a serious danger to human welfare since they kill more people per year than malaria or tuberculosis and are responsible for crop losses worldwide. The treatment of fungal infections is becoming more complicated as fungi develop resistances against commonly used fungicides. Therefore, discovery and development of novel antifungal agents are of utmost importance.Tillmann UteschAlejandra de Miguel CatalinaCaspar SchattenbergNorman PaegePeter SchmiederEberhard KrauseYinglong MiaoJ. Andrew McCammonVera MeyerSascha JungMaria Andrea MroginskiAmerican Society for MicrobiologyarticleAFPantifungal peptidesfungimembranesmodelingmolecular dynamicsMicrobiologyQR1-502ENmSphere, Vol 3, Iss 5 (2018)
institution DOAJ
collection DOAJ
language EN
topic AFP
antifungal peptides
fungi
membranes
modeling
molecular dynamics
Microbiology
QR1-502
spellingShingle AFP
antifungal peptides
fungi
membranes
modeling
molecular dynamics
Microbiology
QR1-502
Tillmann Utesch
Alejandra de Miguel Catalina
Caspar Schattenberg
Norman Paege
Peter Schmieder
Eberhard Krause
Yinglong Miao
J. Andrew McCammon
Vera Meyer
Sascha Jung
Maria Andrea Mroginski
A Computational Modeling Approach Predicts Interaction of the Antifungal Protein AFP from <italic toggle="yes">Aspergillus giganteus</italic> with Fungal Membranes via Its γ-Core Motif
description ABSTRACT 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 spore germination are small cationic, cysteine-stabilized proteins of the AFP family secreted by a group of filamentous Ascomycetes. Its founding member, AFP from Aspergillus giganteus, is of particular interest since it selectively inhibits the growth of filamentous fungi without affecting the viability of mammalian, plant, or bacterial cells. AFPs are also characterized by their high efficacy and stability. Thus, AFP can serve as a lead compound for the development of novel antifungals. Notably, all members of the AFP family comprise a γ-core motif which is conserved in all antimicrobial proteins from pro- and eukaryotes and known to interfere with the integrity of cytoplasmic plasma membranes. In this study, we used classical molecular dynamics simulations combined with wet laboratory experiments and nuclear magnetic resonance (NMR) spectroscopy to characterize the structure and dynamical behavior of AFP isomers in solution and their interaction with fungal model membranes. We demonstrate that the γ-core motif of structurally conserved AFP is the key for its membrane interaction, thus verifying for the first time that the conserved γ-core motif of antimicrobial proteins is directly involved in protein-membrane interactions. Furthermore, molecular dynamic simulations suggested that AFP does not destroy the fungal membrane by pore formation but covers its surface in a well-defined manner, using a multistep mechanism to destroy the membranes integrity. IMPORTANCE Fungal pathogens pose a serious danger to human welfare since they kill more people per year than malaria or tuberculosis and are responsible for crop losses worldwide. The treatment of fungal infections is becoming more complicated as fungi develop resistances against commonly used fungicides. Therefore, discovery and development of novel antifungal agents are of utmost importance.
format article
author Tillmann Utesch
Alejandra de Miguel Catalina
Caspar Schattenberg
Norman Paege
Peter Schmieder
Eberhard Krause
Yinglong Miao
J. Andrew McCammon
Vera Meyer
Sascha Jung
Maria Andrea Mroginski
author_facet Tillmann Utesch
Alejandra de Miguel Catalina
Caspar Schattenberg
Norman Paege
Peter Schmieder
Eberhard Krause
Yinglong Miao
J. Andrew McCammon
Vera Meyer
Sascha Jung
Maria Andrea Mroginski
author_sort Tillmann Utesch
title A Computational Modeling Approach Predicts Interaction of the Antifungal Protein AFP from <italic toggle="yes">Aspergillus giganteus</italic> with Fungal Membranes via Its γ-Core Motif
title_short A Computational Modeling Approach Predicts Interaction of the Antifungal Protein AFP from <italic toggle="yes">Aspergillus giganteus</italic> with Fungal Membranes via Its γ-Core Motif
title_full A Computational Modeling Approach Predicts Interaction of the Antifungal Protein AFP from <italic toggle="yes">Aspergillus giganteus</italic> with Fungal Membranes via Its γ-Core Motif
title_fullStr A Computational Modeling Approach Predicts Interaction of the Antifungal Protein AFP from <italic toggle="yes">Aspergillus giganteus</italic> with Fungal Membranes via Its γ-Core Motif
title_full_unstemmed A Computational Modeling Approach Predicts Interaction of the Antifungal Protein AFP from <italic toggle="yes">Aspergillus giganteus</italic> with Fungal Membranes via Its γ-Core Motif
title_sort computational modeling approach predicts interaction of the antifungal protein afp from <italic toggle="yes">aspergillus giganteus</italic> with fungal membranes via its γ-core motif
publisher American Society for Microbiology
publishDate 2018
url https://doaj.org/article/9c629bbaa8484a38b76934cafd8d7645
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