Computational studies of biological processes regulated by membrane proteins require accurate modeling of membrane dynamics shaped by lipid composition and lipid-protein interactions. Achieving sufficient sampling of these interactions with all-atom molecular dynamics (MD) often demands multiple replicates and extended simulation times, particularly for large proteins embedded in physiologically relevant membrane environments. For such large-scale complex systems, efficient preparation and simulation management are essential to maximize the use of time and computational resources. To address these challenges, we developed a plugin in VMD2 that streamlines the generation of diverse membrane and membrane-protein systems. The plugin provides a step-by-step visually interactive graphical user interface (GUI) for building systems with customizable lipid compositions and sizes, specified either by ratios or absolute lipid numbers in each leaflet. It also supports adding distance constraints for system components and automation for independently generated simulation replicates. Post-build features integrate seamlessly with VMD2/NAMD3 for solvation, ionization, and minimization. Additionally, the plugin automates conversion between full-tailed lipid bilayers and our highly mobile membrane mimetic (HMMM) model, incorporating the recently parameterized organic solvent SCSE, expanded lipid support, and improved back-conversion methods that eliminate ring-piercing artifacts. Built-in validation tools check for other steric clashes, while interoperability with VMD’s QwikMD plugin extends functionality to quickly set up simulations. We also present a tutorial with practical examples demonstrating how to build and simulate complex systems for both integral and peripheral membrane proteins. Together, these tools provide an accessible and efficient framework for investigating lipid-protein interactions using enhanced membrane models.
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Cade Duckworth
Emad Tajkhorshid
University of Illinois Urbana-Champaign
Biophysical Journal
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Duckworth et al. (Sun,) studied this question.
synapsesocial.com/papers/69990de85b97ab4c14ac2855 — DOI: https://doi.org/10.1016/j.bpj.2025.11.2579