Non-Equilibrium Molecular Dynamics Simulation Captures Potential New Drug Target: Ec-MscL Gating Mechanism Explored with External Electric Field.

Background

The emergence of multidrug-resistant bacteria, coupled with the stagnation of antibiotic discovery, underscores the urgent need for new therapeutic strategies targeting underexplored bacterial mechanisms. The Escherichia coli mechanosensitive channel of large conductance (Ec-MscL) is a highly conserved bacterial membrane protein that regulates osmotic homeostasis through gated pore formation; however, its fully open conformation remains structurally unresolved due to experimental limitations. Building upon our previous studies, in which an external electric field (EEF) was used to accelerate the translocation of the antibiotic dihydrostreptomycin (DHS) through Ec-MscL, we extend this approach to investigate peptide-scale gating transitions and identify the partially open conformation of this channel for subsequent binder design.

Methods

In this work, we employed EEF-steered molecular dynamics (MD) simulations to model the translocation of the experimentally validated permeant bovine pancreatic trypsin inhibitor (BPTI), a small positively charged peptide, through Ec-MscL. This approach enabled the capture and stabilization of an a partially open-channel conformation of Ec-MscL, which was subsequently evaluated using QMEAN structural quality assessment and MM/PBSA free-energy calculations. Using this open-state structure as a template, we performed virtual screening against a curated antibiotic library from the Community for Open Antimicrobial Drug Discovery (CO-ADD), followed by conventional MD simulations of the top-ranked candidates.

Results

Eight ligands were computationally identified that stably interact with the channel and were predicted to inhibit its closure, highlighting their potential as antibiotics or antibiotic adjuvants. In addition, four commercially available compounds were evaluated in cell viability assays, with the results suggesting that compound abJ0y affects bacterial growth.

Conclusions

Together, our study establishes a structure-guided workflow for identifying functional states of mechanosensitive channels and presents a computational pipeline for antibiotic discovery, which was further supported by the identification of a compound that reduced growth in MscL-expressing cells with potential antibacterial activity.