2017
DOI: 10.1016/j.bpj.2016.11.468
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Structure of the Ebola Virus Envelope Protein MPER/TM Domain and its Interaction with the Fusion Loop Explains their Fusion Activity

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Cited by 15 publications
(24 citation statements)
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“…In addition, some viral fusion proteins contain segments that may interact directly with cholesterol. This includes the membrane proximal region of the GP2 protein of Ebola virus that contains the sequence GXXGXXXA, suggested to interact with cholesterol [99]. The sequence GXXXG is often associated with protein dimerization, but this and similar sequences have been shown to also interact with cholesterol in the amyloid precursor protein [100].…”
Section: Role Of Cholesterol In Membrane Fusionmentioning
confidence: 99%
“…In addition, some viral fusion proteins contain segments that may interact directly with cholesterol. This includes the membrane proximal region of the GP2 protein of Ebola virus that contains the sequence GXXGXXXA, suggested to interact with cholesterol [99]. The sequence GXXXG is often associated with protein dimerization, but this and similar sequences have been shown to also interact with cholesterol in the amyloid precursor protein [100].…”
Section: Role Of Cholesterol In Membrane Fusionmentioning
confidence: 99%
“…Cholesterol has a small hydrophilic head group and a bulky steroid backbone, and is a vital component of biological membranes. Accumulating evidence supports the importance of cholesterol in various fusion events, such as exocytosis (Wasser et al, 2007;Linetti et al, 2010) and viral fusion (Klug et al, 2017;Lee et al, 2017). Cholesterol is thought to participate in membrane fusion mainly by altering the biophysical properties of the membrane, such as the fluidity, thickness, curvature, and stability of lipid bilayers (Yang et al, 2016).…”
Section: Cholesterol and Atlastin-mediated Fusionmentioning
confidence: 99%
“…Samples were loaded into quartz capillaries of 1.5 ID x 1.8 OD 100 mm length and flash frozen in liquid nitrogen then run at 80 K. DEER data were collected using a dead-time free four-pulse sequence with 16-step phase cycling (one 16 ns π/2 and two 32 ns π observe pulses separated by a 32 ns π pump pulse). (38,39) Pump and observe pulses were separated by 75 MHz. DeerAnalysis2015 or DD was used for the removal of the dipolar background from the raw DEER data, V(t)/V(0) (39-42), and Tikhonov regularization was used to extract distance distributions from the resulting form factors, F(t)/F(0) (38,43).…”
Section: Continuous Wave Eprmentioning
confidence: 99%
“…(38,39) Pump and observe pulses were separated by 75 MHz. DeerAnalysis2015 or DD was used for the removal of the dipolar background from the raw DEER data, V(t)/V(0) (39-42), and Tikhonov regularization was used to extract distance distributions from the resulting form factors, F(t)/F(0) (38,43).…”
Section: Continuous Wave Eprmentioning
confidence: 99%