Elucidating antibiotic permeation through the Escherichia coli outer membrane: insights from molecular dynamics

Antibiotic resistance represents a critical public health threat, with an increasing number of Gram-negative pathogens demonstrating resistance to a broad range of clinical drugs. A primary challenge in enhancing antibiotic efficacy is overcoming the robust barrier presented by the bacterial outer m...

Full description

Saved in:
Bibliographic Details
Main Authors: Deylami, Javad, Chng, Shu Sin, Yong, Ee Hou
Other Authors: School of Physical and Mathematical Sciences
Format: Article
Language:English
Published: 2025
Subjects:
Online Access:https://hdl.handle.net/10356/182444
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
Description
Summary:Antibiotic resistance represents a critical public health threat, with an increasing number of Gram-negative pathogens demonstrating resistance to a broad range of clinical drugs. A primary challenge in enhancing antibiotic efficacy is overcoming the robust barrier presented by the bacterial outer membrane. Our research addresses a longstanding question: What is the rate of antibiotic permeation across the outer membrane (OM) of Gram-negative bacteria? Utilizing molecular dynamics (MD) simulations, we assess the passive permeability profiles of four commercially available antibiotics─gentamicin, novobiocin, rifampicin, and tetracycline across an asymmetric atomistic model of the Escherichia coli (E. coli) OM, employing the inhomogeneous solubility-diffusion model. Our examination of the interactions between these drugs and their environmental context during OM permeation reveals that extended hydrogen bond formation and drug-cation interactions significantly hinder the energetics of passive permeation, notably affecting novobiocin. Our MD simulations corroborate well with experimental data and reveal new implications of solvation on drug permeability, overall advancing the possible use of computational prediction of membrane permeability in future antibiotic discovery.