Computational Prioritization of Megalin-Aminoglycoside Recognition and Gentamicin-Associated Cellular Stress Responses.

Authors

Iris N Serratos, Gerardo Pérez-Hernández, Luis Angel Carrasco Sánchez, Cesar Millan-Pacheco, Ámbar Lopez-Macay, Claudia G Benítez Cardoza, Absalom Zamorano Carrillo, Norma Castañeda-Villa

Published in

Archives of biochemistry and biophysics. Pages 111005. Sep 19, 2026. Epub Sep 19, 2026.

Abstract

Aminoglycosides are effective antibiotics for severe infections, but their clinical use is limited by nephrotoxicity and ototoxicity resulting from drug accumulation in non-infected tissues. Megalin, an endocytic receptor expressed in renal proximal tubules and inner-ear tissues, has been proposed as a mediator of this uptake.
To evaluate whether the CR10 domain of human megalin constitutes a plausible aminoglycoside-recognition site and to prioritize compounds for experimental testing.
Seven aminoglycosides were comparatively analyzed in silico using docking and molecular dynamics simulations against megalin CR10. Gentamicin, which showed one of the most favorable predicted interaction profiles, was selected for biological evaluation. Cell viability was assessed in HEK293, HeLa, and U87MG cells, while calcium signaling and NF-κB activation were measured in HEK293 cells as indicators of cellular stress.
Gentamicin reduced viability in a cell-type-dependent manner and induced calcium and NF-κB responses in HEK293 cells. Computational analyses suggested predominantly electrostatic interactions with megalin CR10, with gentamicin, tobramycin, and neomycin showing the most favorable predicted binding energies.
The experimental and computational findings support a sequential in silico-to-in vitro workflow in which cellular assays define a gentamicin-associated stress phenotype, while molecular modeling identifies megalin CR10 as a structurally plausible aminoglycoside-recognition region that may contribute to tissue uptake or retention in organs expressing LRP2/megalin.

PMID:
42762957
Bibliographic data and abstract were imported from PubMed on 20 Sep 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.