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High-resolution mining of the SARS-CoV-2 main protease conformational space: supercomputer-driven unsupervised
Théo Jaffrelot Inizan1, Frédéric Célerse1,2, Olivier Adjoua1
1Sorbonne Université, LCT, UMR 7616 CNRS Paris France louis.lagardere@sorbonne-universite.fr pierre.monmarche@sorbonne-universite.fr jean-philip.piquemal@sorbonne-universite.fr.
Chemical Science
|June 25, 2021
Summary
We developed a new method for fast molecular dynamics (MD) simulations of large biological systems. This approach accurately models the SARS-CoV-2 Main Protease (Mpro) and reveals critical insights into its active site plasticity and drug interactions.
Area of Science:
- Computational Chemistry and Molecular Modeling
- Structural Biology
- Drug Discovery
Background:
- Accurate modeling of large biosystems requires efficient simulation strategies.
- Understanding the dynamics of viral proteases like SARS-CoV-2 Main Protease (Mpro) is crucial for antiviral drug development.
- Polarizable Force Fields (PFFs) offer higher accuracy but are computationally demanding for long timescales.
Purpose of the Study:
- To develop an unsupervised adaptive sampling strategy for μs-timescale molecular dynamics (MD) simulations of large biosystems using PFFs.
- To apply this strategy to model the SARS-CoV-2 Main Protease (Mpro) and investigate its conformational landscape and active site dynamics.
- To compare simulation results using the AMOEBA PFF with existing non-PFF data and experimental observations.
Main Methods:
- An unsupervised adaptive sampling strategy decomposing global exploration into parallel MD trajectories.
- Utilized the Tinker-HP package on supercomputers with numerous GPUs for accelerated simulations.
- Performed over 38 μs of all-atom MD simulations of SARS-CoV-2 Mpro using the AMOEBA PFF at physiological and lower pH.
Main Results:
- The AMOEBA PFF revealed a richer conformational space for Mpro compared to non-PFFs, highlighting active site plasticity.
- Observed asymmetry between Mpro protomers, with one exhibiting less structure and potentially modulated activity.
- Protonation of His172 at lower pH impacted the oxyanion loop stability; solvation patterns around histidines were analyzed.
Conclusions:
- The developed adaptive sampling strategy significantly reduces simulation time for large biosystems using PFFs.
- PFFs are critical for accurately capturing the complex molecular interactions and conformational dynamics of Mpro.
- Findings provide valuable insights into Mpro's structural plasticity and potential drug interaction sites, aiding antiviral drug discovery.
