Dataset Open Access

SIRAH-CoV2 initiative: NSP16 - NSP10 Complex (PDB id:6W4H)

Martín Soñora; Exequiel Barrera; Pablo Garay; Florencia Klein; Matías Machado; Sergio Pantano

This dataset contains the trajectory of a 10 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV2 NSP16 - NSP10 Complex with Zn ions bound (PDB id: 6W4H). Simulations have been performed using the SIRAH force field running with the Amber18 package at the Uruguayan National Center for Supercomputing (ClusterUY) under the conditions reported in Machado et al. JCTC 2019, adding 150 mM NaCl according to Machado & Pantano JCTC 2020. Zinc ions were parameterized as reported in Klein et al. 2020.

The file 6W4H_SIRAHcg_rawdata.tar contains all the raw information required to visualize (on VMD), analyze, backmap, and eventually continue the simulations using Amber18 or higher. Step-By-Step tutorials for running, visualizing, and analyzing CG trajectories using SirahTools can be found at www.sirahff.com.

Additionally, the file 6W4H_SIRAHcg_10us_prot_Zn.tar contains only the protein coordinates, while 6W4H_SIRAHcg_10us_prot_Zn_skip10ns.tar contains one frame every 10ns.

To take a quick look at the trajectory:

1- Untar the file 6W4H_SIRAHcg_10us_prot_Zn_skip10ns.tar

2- Open the trajectory on VMD using the command line:

vmd 6w4h_SIRAHcg_prot.prmtop 6w4h_SIRAHcg_prot.ncrst 6w4h_SIRAHcg_prot_Zn_10us_skip10ns.nc -e sirah_vmdtk.tcl

Note that you can use normal VMD drawing methods as vdw, licorice, etc., and coloring by restype, element, name, etc. 

This dataset is part of the SIRAH-CoV2 initiative.

For further details, please contact Martín Soñora (msonora@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).

 

Files (9.1 GB)
Name Size
6W4H_SIRAHcg_10us_prot_Zn.tar
md5:e2a8e0bb06cc12015b385756fecb9479
1.2 GB Download
6W4H_SIRAHcg_10us_prot_Zn_skip10ns.tar
md5:da7b3bd49fe20444676ba52a14676ca9
24.8 MB Download
6W4H_SIRAHcg_rawdata.tar
md5:4501ce284f9026bfe9aae56fb625cf70
7.9 GB Download
  • Klein et al., JCIM, 2020 (DOI:10.1021/acs.jcim.0c00160)

  • Machado & Pantano, Bioinformatics 2016 (DOI:10.1093/bioinformatics/btw020)

  • Machado & Pantano, JCTC 2020 (DOI:10.1021/acs.jctc.9b00953)

  • Machado et al. JCTC 2019 (DOI: 10.1021/acs.jctc.9b00006)

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