The milk-derived lactoferrin inhibits V-ATPase activity by targeting its V1 domain

Lactoferrin (Lf), a bioactive milk protein, exhibits strong anticancer and antifungal activities. The search for Lf targets and mechanisms of action is of utmost importance to enhance its effective applications. A common feature among Lf-treated cancer and fungal cells is the inhibition of a proton...

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Veröffentlicht in:International journal of biological macromolecules 2021-09, Vol.186, p.54-70
Hauptverfasser: Santos-Pereira, Cátia, Rocha, Juliana F., Fernandes, Henrique S., Rodrigues, Lígia R., Côrte-Real, Manuela, Sousa, Sérgio F.
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Sprache:eng
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Zusammenfassung:Lactoferrin (Lf), a bioactive milk protein, exhibits strong anticancer and antifungal activities. The search for Lf targets and mechanisms of action is of utmost importance to enhance its effective applications. A common feature among Lf-treated cancer and fungal cells is the inhibition of a proton pump called V-ATPase. Lf-driven V-ATPase inhibition leads to cytosolic acidification, ultimately causing cell death of cancer and fungal cells. Given that a detailed elucidation of how Lf and V-ATPase interact is still missing, herein we aimed to fill this gap by employing a five-stage computational approach. Molecular dynamics simulations of both proteins were performed to obtain a robust sampling of their conformational landscape, followed by clustering, which allowed retrieving representative structures, to then perform protein-protein docking. Subsequently, molecular dynamics simulations of the docked complexes and free binding energy calculations were carried out to evaluate the dynamic binding process and build a final ranking based on the binding affinities. Detailed atomist analysis of the top ranked complexes clearly indicates that Lf binds to the V1 cytosolic domain of V-ATPase. Particularly, our data suggest that Lf binds to the interfaces between A/B subunits, where the ATP hydrolysis occurs, thus inhibiting this process. The free energy decomposition analysis further identified key binding residues that will certainly aid in the rational design of follow-up experimental studies, hence bridging computational and experimental biochemistry. [Display omitted]
ISSN:0141-8130
1879-0003
DOI:10.1016/j.ijbiomac.2021.06.200