2019
DOI: 10.1016/j.bpj.2019.09.011
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On the Interpretation of Force-Induced Unfolding Studies of Membrane Proteins Using Fast Simulations

Abstract: Single-molecule force spectroscopy has proven extremely beneficial in elucidating folding pathways for membrane proteins. Here, we simulate these measurements, conducting hundreds of unfolding trajectories using our fast Upside algorithm for slow enough speeds to reproduce key experimental features that may be missed using all-atom methods. The speed also enables us to determine the logarithmic dependence of pulling velocities on the rupture levels to better compare to experimental values. For simulations of a… Show more

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Cited by 12 publications
(23 citation statements)
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References 49 publications
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“…Through these and the careful treatment of the bilayer boundary position, our potential can optimally predict the bilayer thickness and protein location, as compared to the OPM (Orientations of Proteins in Membranes) method ( 55 ). Our force-induced unfolding studies using the membrane potential for GlpG and bacteriorhodopsin agree well with the experiment ( 53 ).…”
Section: Resultssupporting
confidence: 86%
See 1 more Smart Citation
“…Through these and the careful treatment of the bilayer boundary position, our potential can optimally predict the bilayer thickness and protein location, as compared to the OPM (Orientations of Proteins in Membranes) method ( 55 ). Our force-induced unfolding studies using the membrane potential for GlpG and bacteriorhodopsin agree well with the experiment ( 53 ).…”
Section: Resultssupporting
confidence: 86%
“…Our membrane-burial potential includes knowledge-based, depth- and lipid exposure–dependent energies for side-chain burial and backbone H bonding within the bilayer ( 53 , 54 ). Energies are determined from the statistics of a large training set of proteins, which accounts for both the depth Z in the membrane and the level of side-chain exposure to the lipid: Energy ( Z , exposure) ln(frequency).…”
Section: Resultsmentioning
confidence: 99%
“…The energy function used here, FF1.5, has been improved over the original function FF1.0 through the use of an updated contrastive divergence training procedure that includes more extensive sampling (SI text). We added a new membrane burial potential that dynamically accounts for the level of side-chain exposure to lipids and includes unfavorable energies for unsatisfied H-bond donors and acceptors in the membrane to allow helices to fold and unfold within the bilayer (59,60). Side-chain burial energies are determined from the statistics of a training set of proteins and accounts for the burial depth.…”
Section: Simulations Of Dses Of Glpgmentioning
confidence: 99%
“…Our membrane-burial potential includes knowledge-based, depth-dependent energies for side-chain burial and backbone hydrogen bonding within the bilayer. Helices are allowed to unfold and refold in the bilayer during the simulations (59,60). At every MD step, side-chain burial is recalculated to account for the exchange of protein-lipid interactions for protein-protein interactions as helices come into contact with each other.…”
Section: Dse Simulationsmentioning
confidence: 99%
“…Extensive enzyme kinetic and structural studies have been carried out to elucidate the proteolytic mechanisms (27)(28)(29)(30)(31)(32)(33)(34)(35)(36). Recently, GlpG has emerged as an important model for studying membrane protein folding (37)(38)(39)(40)(41)(42).…”
Section: Significancementioning
confidence: 99%