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ZENODO
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ZENODO
Dataset . 2021
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Data sources: Datacite
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MD simulations of SARS-CoV-2 Spike Protein under static electric fields

Authors: Arbeitman, Claudia R.; Rojas, Pablo; Ojeda-May, Pedro; Garcia, Martin E.;

MD simulations of SARS-CoV-2 Spike Protein under static electric fields

Abstract

This dataset contains trajectories corresponding to all-atom MD simulations of segments of the SARS-CoV-2 Spike Protein, and in-silico mutations, under the influence of moderate external electric fields. The final structures of some of the simulations were used to perform in-silico docking with ACE2 receptor to evaluate the effect of comformational changes (docking was perform with PyDOCK). The file trajectories_6vsb_dt1ns.zip contains trajectories of simulations that were performed on a segment of the Protein Data Bank ID 6VSB comprising RBD, SD1 and SD2. The file trajectories_6m0j_dt1ns.zip correspond to the RBD in Protein Data Bank ID 6M0J. The file trajectories_in-silico_mutations_dt1ns.zip correspond to simulations performed on in-silico generated mutations following the mutations corresponding to WHO Variants of Concern UK, South Africa and Brazil. In all cases, simulations were performed at different electric field intensities ranging between 104 V/m and 107 V/m, with an extra short simulation under very high intensity (109 V/m). The file docked_structures_6m0j.zip contains the 100 best scored docked structures for each case as the output of PyDOCK. Trajectories are stored in GROMACS compressed trajectory file format (.xtc), downsampled to a 1ns timestep. Individual trajectories length are between 300 nanoseconds and 1 microsecond. In-silico docked structures are in PDB format. See linked preprint for more details.

Calculations were performed at Lichtenberg High Performance Computer of the TU Darmstadt, the High Performance Center North (HPC2N) at SNIC, and at local dedicated workstations of our group. Supported by the PhosMOrg (P/1082 232) research unit of the University of Kassel, and Joachim Herz Foundation through its Add-on Fellowship for Interdisciplinary Life Science. Acknowledgements to the Argentinian AntiCovid Consortium (Argentina) for valuable discussions, and Dr. Bernd Bauerhenne for his help with computing resources.

Keywords

covid19, sars-cov-2, covid-19, SARS-CoV-2, COVID-19, SARS-COV-2, spike protein

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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