Bridging the gap between lactoferrin and V-ATPase through a multi-stage computational approach

Abstract

Lactoferrin (Lf), a bioactive milk protein, exhibits strong anticancer and antifungal activities [1,2]. 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 essential for pH homeostasis called V-ATPase. Lf-driven V-ATPase inhibition leads to cytosolic acidification, ultimately causing cell death of cancer and fungal cells [24]. Given that a detailed elucidation of how Lf and V-ATPase interact is still missing, in this work we aimed to fill this gap by employing a multi-level computational approach. Molecular dynamics (MD) simulations of both proteins were performed to obtain a robust sampling of their conformational landscape, followed by clustering and protein-protein docking. Subsequently, MD simulations of the docked complexes and free binding energy calculations were carried out to evaluate the dynamic binding process and built the final ranking. This computational pipeline unraveled a putative mechanism by which Lf inhibits V-ATPase and identified key binding residues that will certainly aid in the rational design of follow-up experimental studies, bridging in this way computational and experimental biochemistry.