Dataset Open Access

SIRAH-CoV2 initiative: RNA binding domain of nucleocapsid phosphoprotein (PDB id:6VYO)

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

This dataset contains the trajectory of a 10 microseconds-long coarse-grained molecular dynamics simulation of SARS-CoV2 RNA binding domain of the nucleocapsid phosphoprotein in its APO form with Zn ions bound (PDB id:6VYO, Bioassembly 1). Simulations were 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 6VYO_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 6VYO_SIRAHcg_10us_prot.tar contains only the protein coordinates, while 6VYO_SIRAHcg_10us_prot_skip10ns.tar contains one frame every 10ns.

To take a quick look at the trajectory:

1- Untar the file 6VYO_SIRAHcg_10us_prot_skip10ns.tar

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

vmd 6VYO_SIRAHcg_prot.prmtop 6VYO_SIRAHcg_prot_10us_skip10ns.ncrst 6VYO_SIRAHcg_prot_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 Florencia Klein (fklein@pasteur.edu.uy) or Sergio Pantano (spantano@pasteur.edu.uy).

Files (9.2 GB)
Name Size
6VYO_SIRAHcg_10us_prot.tar
md5:5f1193df2c44b1280859269896b46d8c
1.4 GB Download
6VYO_SIRAHcg_prot_10us_skip10ns.tar
md5:f384d0e452240734b73267f7314582c8
30.1 MB Download
6VYO_SIRAHcg_rawdata.tar
md5:3706c2ad21232fb4f1fe9cc4fa3645d3
7.7 GB Download
  • Klein et al. 2020 (DOI:10.26434/chemrxiv.11881716.v1)

  • 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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