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Title: Native glycosylated HIV-1 Env in silico ensemble

Abstract

The computationally modeled datasets generated in this study, namely the natively glycosylated SOSIP Env and the uniform mannose-9 glycosylated SOSIP Env ensembles will be submitted as Mendeley dataset server as required by the journal publishers, for public availability. These include two sets of Protein Data Bank (PDB)ensembles of 1000 structures each. The files are in the standardized PDB format. Each of the constituent ensemble structures are separated by the ‘END’ tag within the files. Snapshots from the beginning and end of each data set are given here. The column descriptions are as follows: Col1 –ATOM tag; Col 2 –atom number; COL 3 –atom name; COL4 –residue name; COL 5 –chain identifier; COL 6 –residue number; COL. 7,8,9 –X,Y,Z coordinates of atom in 3Dspace; COL 10 –Occupancy Factor; COL 11 -Temperature factor; COL 12 –segment identifier; COL 13 –element symbol.

Authors:
ORCiD logo ; ; ORCiD logo ; ORCiD logo ; ; ORCiD logo
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. The Scripps Research Inst., La Jolla, CA (United States)
Publication Date:
Other Number(s):
LA-UR-20-29404
DOE Contract Number:  
89233218CNA000001
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
National Institutes of Health (NIH); USDOE National Nuclear Security Administration (NNSA)
Subject:
59 BASIC BIOLOGICAL SCIENCES
OSTI Identifier:
1721702
DOI:
https://doi.org/10.17632/yds8rtfjjy.1

Citation Formats

Chakraborty, Srirupa, Bernsden, Zachary, Hengartner, Nicolas, Korber, Bette, Ward, Andrew, and Gnanakaran, Sandrasegaram. Native glycosylated HIV-1 Env in silico ensemble. United States: N. p., 2020. Web. doi:10.17632/yds8rtfjjy.1.
Chakraborty, Srirupa, Bernsden, Zachary, Hengartner, Nicolas, Korber, Bette, Ward, Andrew, & Gnanakaran, Sandrasegaram. Native glycosylated HIV-1 Env in silico ensemble. United States. doi:https://doi.org/10.17632/yds8rtfjjy.1
Chakraborty, Srirupa, Bernsden, Zachary, Hengartner, Nicolas, Korber, Bette, Ward, Andrew, and Gnanakaran, Sandrasegaram. 2020. "Native glycosylated HIV-1 Env in silico ensemble". United States. doi:https://doi.org/10.17632/yds8rtfjjy.1. https://www.osti.gov/servlets/purl/1721702. Pub date:Tue Nov 17 00:00:00 EST 2020
@article{osti_1721702,
title = {Native glycosylated HIV-1 Env in silico ensemble},
author = {Chakraborty, Srirupa and Bernsden, Zachary and Hengartner, Nicolas and Korber, Bette and Ward, Andrew and Gnanakaran, Sandrasegaram},
abstractNote = {The computationally modeled datasets generated in this study, namely the natively glycosylated SOSIP Env and the uniform mannose-9 glycosylated SOSIP Env ensembles will be submitted as Mendeley dataset server as required by the journal publishers, for public availability. These include two sets of Protein Data Bank (PDB)ensembles of 1000 structures each. The files are in the standardized PDB format. Each of the constituent ensemble structures are separated by the ‘END’ tag within the files. Snapshots from the beginning and end of each data set are given here. The column descriptions are as follows: Col1 –ATOM tag; Col 2 –atom number; COL 3 –atom name; COL4 –residue name; COL 5 –chain identifier; COL 6 –residue number; COL. 7,8,9 –X,Y,Z coordinates of atom in 3Dspace; COL 10 –Occupancy Factor; COL 11 -Temperature factor; COL 12 –segment identifier; COL 13 –element symbol.},
doi = {10.17632/yds8rtfjjy.1},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {11}
}

Works referencing / citing this record:

Quantification of the Resilience and Vulnerability of HIV-1 Native Glycan Shield at Atomistic Detail
journal, November 2020