State-of-the-art simulation methods against the SARS-CoV-2 virus

04 Feb 2021

This news story was originally published on the PPI4HPC website at: https://ppi4hpc.eu/news/state-art-simulation-methods-against-sars-cov-2-virus

Jean-Philip Piquemal, Professor of Theoretical Chemistry at Sorbonne University in Paris, and his team have created Tinker HP [1, 2], a massively parallel molecular dynamics package for multiscale simulations of large complex systems. Due to its design, the code is used in different computer systems, from laboratories to supercomputers, and forms the first high-performance scalable CPU/GPUs computing environment for the development and production of accurate simulations using new generation polarizable force fields such as AMOEBA.

In order to cover these computing needs, Prof Piquemal and his team were awarded HPC resources available through the PRACE Fast-Track Call, launched in March 2020, that welcomed project proposals requesting computing resources to contribute to the mitigation of the impact of the COVID-19 pandemic. The resources awarded to Prof Piquemal included a huge amount of computing power as well as data storage capabilities.

The computing power was offered by a system acquired by GENCI as part of the joint PPI4HPC procurement. Prof Piquemal’s project was awarded 20 million core hours on the Joliot-Curie supercomputer hosted at CEA, France. At the same time, for the data storage requirements, the project took advantage of the Fenix data services offered by the ICEI project. The Fenix infrastructure facilitated the storage and further accessibility of the large simulation data.

Through the simulations on the PPI4HPC system, the researchers investigated important proteins of the SARS-CoV-2 virus such as the Main protease (Mpro) [3] with high accuracy, discovering details on their targets that can prove useful in making predictions and improving the drugs against the current pandemic. The Fenix storage services have been used to share results with other scientists.

 

  1. Tinker-HP: a Massively Parallel Molecular Dynamics Package for Multiscale Simulations of Large Complex Systems with Advanced Polarizable Force Fields. L. Lagardère, L.-H. Jolly, F. Lipparini, F. Aviat, B. Stamm, Z. F. Jing, M. Harger, H. Torabifard, G. A. Cisneros, M. J. Schnieders, N. Gresh, Y. Maday, P. Ren, J. W. Ponder, J.-P. Piquemal, Chem. Sci., 2018, 9, 956-972 (Open Access), http://dx.doi.org/10.1039/C7SC04531J.
  2. Tinker-HP: Accelerating Molecular Dynamics Simulations of Large Complex Systems with Advanced Point Dipole Polarizable Force Fields using GPUs and Multi-GPUs systems. O. Adjoua, L. Lagardère, L.-H. Jolly, Arnaud Durocher, Z. Wang, T. Very, I. Dupays, T. Jaffrelot Inizan, F. Célerse, P. Ren, J. Ponder, J-P. Piquemal, 2021, J. Chem. Theory. Comput,  in press (Open Access), preprint ArXiv: https://arxiv.org/abs/2011.01207.
  3. High-Resolution Mining of SARS-CoV-2 Main Protease Conformational Space: Supercomputer-Driven Unsupervised Adaptive Sampling . T. Jaffrelot-Inizan, F. Célerse, O. Adjoua,   D. El Ahdab, L.-H. Jolly, C. Liu, P. Ren, M. Montes, N. Lagarde,  L. Lagardère, P. Monmarché, J.-P. Piquemal, Chemical Science, 2021, online (Open Access),  https://doi.org/10.1039/D1SC00145K.
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Fenix has received funding from the European Union's Horizon 2020 research and innovation programme through the ICEI project under the grant agreement No. 800858.