Dataset Open Access

SIRAH-CoV2 initiative: UPDATED TRAJECTORY of SARS-Cov2 Spike´s RBD / ACE2-B0AT1 complex (PDB id:6M17)

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

This dataset contains an updated trajectory of a four microseconds-long coarse-grained molecular dynamics simulation of the hexameric complex between SARS-CoV2 Spike´s RBD, ACE2, and B0AT1  (PDB id: 6M17). It substitutes the previous one on the same system, which was performed in the absence of disulfide bridges.

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 files 6M17_SIRAHcg_rawdata_0-1.tar,  6M17_SIRAHcg_rawdata_1-2.tar, 6M17_SIRAHcg_rawdata_2-3.tar, and 6M17_SIRAHcg_rawdata_3-4.tar contain 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 6M17_SIRAHcg_4us_prot.tar contains only the protein coordinates, while 6M17_SIRAHcg_4us_prot_skip10ns.tar contains one frame every 10ns.

To take a quick look at the trajectory:

1- Untar the file 6M17_SIRAHcg_4us_prot_skip10ns.tar

2- Open the trajectory on VMD 1.9.3 using the command line:

vmd 6M17_SIRAHcg_prot.prmtop 6M17_SIRAHcg_prot.ncrst 6M17_SIRAHcg_4usprot_skip.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 (30.6 GB)
Name Size
6M17_SIRAHcg_4us_prot.tar
md5:fbdedba0cbb2a384eb0ec39b130ab8b5
3.6 GB Download
6M17_SIRAHcg_4us_prot_skip10ns.tar
md5:2a9384147e7637820e5494c5d8203496
78.6 MB Download
6M17_SIRAHcg_rawdata_0-1us.tar
md5:00fba4bce1849d2baf29199f8812e0b6
6.7 GB Download
6M17_SIRAHcg_rawdata_1-2us.tar
md5:5d7c1428ddc7a10b8f3d38e0e2f71248
6.7 GB Download
6M17_SIRAHcg_rawdata_2-3us.tar
md5:49be54b3fc9a8494cc6ac58cbe88e56a
6.7 GB Download
6M17_SIRAHcg_rawdata_3-4us.tar
md5:389c99ba59b8f7450ba5cc87bf85690c
6.7 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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