Back

Analysis of SARS-CoV-2 ORF3a structure reveals chloride binding sites

Marquez-Miranda, V.; Rojas, M.; Duarte, Y.; Diaz-Franulic, I.; Holmgren, M.; Cachau, R.; Gonzalez-Nilo, F. D.

2020-10-22 biophysics
10.1101/2020.10.22.349522 bioRxiv
Show abstract

SARS-CoV-2 ORF3a is believed to form ion channels, which may be involved in the modulation of virus release, and has been implicated in various cellular processes like the up-regulation of fibrinogen expression in lung epithelial cells, downregulation of type 1 interferon receptor, caspase-dependent apoptosis, and increasing IFNAR1 ubiquitination. ORF3a assemblies as homotetramers, which are stabilized by residue C133. A recent cryoEM structure of a homodimeric complex of ORF3a has been released. A lower-resolution cryoEM map of the tetramer suggests two dimers form it, arranged side by side. The dimers cryoEM structure revealed that each protomer contains three transmembrane helices arranged in a clockwise configuration forming a six helices transmembrane domain. This domains potential permeation pathway has six constrictions narrowing to about 1 [A] in radius, suggesting the structure solved is in a closed or inactivated state. At the cytosol end, the permeation pathway encounters a large and polar cavity formed by multiple beta strands from both protomers, which opens to the cytosolic milieu. We modeled the tetramer following the arrangement suggested by the low-resolution tetramer cryoEM map. Molecular dynamics simulations of the tetramer embedded in a membrane and solvated with 0.5 M of KCl were performed. Our simulations show the cytosolic cavity is quickly populated by both K+ and Cl-, yet with different dynamics. K+ ions moved relatively free inside the cavity without forming proper coordination sites. In contrast, Cl- ions enter the cavity, and three of them can become stably coordinated near the intracellular entrance of the potential permeation pathway by an inter-subunit network of positively charged amino acids. Consequently, the central cavitys electrostatic potential changed from being entirely positive at the beginning of the simulation to more electronegative at the end.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

1
Frontiers in Molecular Biosciences
100 papers in training set
Top 0.1%
14.5%
2
Journal of Structural Biology
58 papers in training set
Top 0.2%
7.1%
3
ACS Chemical Neuroscience
60 papers in training set
Top 0.3%
6.2%
4
Journal of Chemical Information and Modeling
207 papers in training set
Top 0.9%
6.2%
5
Communications Biology
886 papers in training set
Top 0.4%
6.2%
6
Scientific Reports
3102 papers in training set
Top 25%
4.8%
7
Structure
175 papers in training set
Top 0.6%
4.2%
8
eLife
5422 papers in training set
Top 23%
3.9%
50% of probability mass above
9
Nature Communications
4913 papers in training set
Top 39%
3.6%
10
Cell Discovery
54 papers in training set
Top 1%
3.5%
11
The Journal of Physical Chemistry B
158 papers in training set
Top 0.7%
3.0%
12
PLOS Computational Biology
1633 papers in training set
Top 14%
2.1%
13
Proteins: Structure, Function, and Bioinformatics
82 papers in training set
Top 0.5%
1.7%
14
Journal of Chemical Theory and Computation
126 papers in training set
Top 0.5%
1.7%
15
International Journal of Molecular Sciences
453 papers in training set
Top 8%
1.7%
16
International Journal of Biological Macromolecules
65 papers in training set
Top 2%
1.6%
17
PLOS ONE
4510 papers in training set
Top 57%
1.5%
18
Biochemistry and Biophysics Reports
28 papers in training set
Top 0.9%
1.1%
19
Viruses
318 papers in training set
Top 4%
1.1%
20
The Journal of Physical Chemistry Letters
58 papers in training set
Top 1%
0.9%
21
Protein Science
221 papers in training set
Top 2%
0.8%
22
Computational and Structural Biotechnology Journal
216 papers in training set
Top 9%
0.8%
23
Cell Research
49 papers in training set
Top 3%
0.7%
24
iScience
1063 papers in training set
Top 33%
0.7%
25
Journal of Biomolecular Structure and Dynamics
43 papers in training set
Top 1%
0.7%
26
Bioinformatics
1061 papers in training set
Top 10%
0.6%
27
Biomechanics and Modeling in Mechanobiology
25 papers in training set
Top 1%
0.6%
28
The Innovation
12 papers in training set
Top 1%
0.6%
29
Cellular Signalling
14 papers in training set
Top 0.3%
0.6%
30
Biomolecules
95 papers in training set
Top 3%
0.6%