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Efficient preparation of virus-like particles for molecular simulation and application to Zika virus


Oct 15, 2020

Paper Title:

Wrapping up Viruses at Multiscale Resolution: Optimizing PACKMOL and SIRAH Execution for Simulating the Zika Virus.

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Simulating huge biomolecular complexes of million atoms at relevant biological timescales is becoming accessible to the broad scientific community. That proves to be crucial for urgent responses against emergent diseases in real time. Yet, there are still some issues to be overcome regarding the system setup so that Molecular Dynamics (MD) simulations can be run in a simple and standard way. Here, we introduce an optimized pipeline for building and simulating enveloped virus-like particles (VLP). First, the membrane packing problem is tackled with new features and optimized options in PACKMOL. This allows to prepare accurate membrane models of thousands of lipids in the context of a VLP within a few hours using a single CPU. Then the assembly of the VLP system is done within the multiscale framework of the coarse-grained SIRAH force field. Finally, the equilibration protocol provides a system ready for production MD simulations within a few days on broadly accessible GPU resources. The pipeline is applied to study the Zika Virus as a test case for large biomolecular systems. The multiscale scheme is well preserved along the simulation as evidenced from the radial distribution function of each constituent. The VLP stabilizes at approximately 0.5 ms of MD simulation, reproducing correlations greater than 0.90 against experimental density maps from cryo-electron microscopy. Detailed structural analysis of the protein envelope also shows very good agreement in root mean square deviations and B-factors with the experimental data. A rationale for a possible role of anionic phospholipids in stabilizing the envelope is introduced. The presented pipeline can be extrapolated to study other viral systems as well as intracellular compartments, paving the way to whole cell simulations.


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