Dataset Open Access

SIRAH-CoV2 initiative: Nucleocapsid protein N-terminal RNA binding domain (PDB id:6M3M)

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 Nucleocapsid protein N-terminal RNA binding domain (PDB id:6M3M). 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

The files 6M3M_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 6M3M_SIRAHcg_10us_prot.tar contains only the protein coordinates, while 6M3M_SIRAHcg_10us_prot_skip10ns.tar contains one frame every 10ns.

To take a quick look at the trajectory:

1- Untar the file 6M3M_SIRAHcg_10us_prot_skip10ns.tar

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

vmd 6W4B_SIRAHcg_prot.prmtop 6W4B_SIRAHcg_prot.ncrst 6W4B_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 (4.6 GB)
Name Size
6M3M_SIRAHcg_10us_prot.tar
md5:f846b255fb4e0e89a0706f5135c07740
370.8 MB Download
6M3M_SIRAHcg_10us_prot_skip10ns.tar
md5:27850746378e750173730b5df6b9c068
7.8 MB Download
6M3M_SIRAHcg_rawdata.tar
md5:f8ffb2723053ec2d24fcf86134bfd97f
4.2 GB Download
  • Machado et al. JCTC 2019 (DOI: 10.1021/acs.jctc.9b00006)

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

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

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