2018
DOI: 10.1021/acs.jpcb.8b05591
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Conformational Effects in the Transport of Glucose through a Cyclic Peptide Nanotube: A Molecular Dynamics Simulation Study

Abstract: The transport behavior of glucose through a cyclic peptide nanotube (CPN), composed of 8 × cyclo[-(Trp-d-Leu)-Gln-d-Leu-] rings embedded in DMPC lipid bilayers was examined using all-atom molecular dynamics (AAMD) simulations. Two conformational isomers of β-d-glucose, equatorial (C) and axial (C) chair conformers, were used to examine conformational effects on the hydrogen bond network, energetics, and diffusivity of glucose transport through the CPN. Calculations of the number of hydrogen bonds of the two gl… Show more

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Cited by 6 publications
(13 citation statements)
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“…It should be noted that this approach allows us to estimate D ( z ) from techniques using a time-dependent bias, e.g., the adaptive biasing force formalism and metadynamics, as well as from unbiased simulations. For the theoretical foundation and the procedure of computing D ( z ), we refer the reader to Comer et al Previous studies have shown that the choice of the sampling time interval Δ t of CV z in the BI/MC method affects the estimation of D ( z ). , Thus, we have set Δ t equal to 4 ps for all nine models studied here assuming that a constant value will lead to similar uncertainties in all cases. This approximation should be fine in the present case as the idea is to estimate semiquantitative permeation times rather than quantitatively accurate ones.…”
Section: Materials and Methodsmentioning
confidence: 99%
“…It should be noted that this approach allows us to estimate D ( z ) from techniques using a time-dependent bias, e.g., the adaptive biasing force formalism and metadynamics, as well as from unbiased simulations. For the theoretical foundation and the procedure of computing D ( z ), we refer the reader to Comer et al Previous studies have shown that the choice of the sampling time interval Δ t of CV z in the BI/MC method affects the estimation of D ( z ). , Thus, we have set Δ t equal to 4 ps for all nine models studied here assuming that a constant value will lead to similar uncertainties in all cases. This approximation should be fine in the present case as the idea is to estimate semiquantitative permeation times rather than quantitatively accurate ones.…”
Section: Materials and Methodsmentioning
confidence: 99%
“…Finally, the numbers of hydrogen bonds formed between the SLE2S-surfactant head and other ceramide (system 5) and DMPC bilayer (system 6) components were calculated while the surfactant was partitioning into the bilayers and are illustrated in Figure , where hydrogen-bond formation is defined as in ref and oxygen atoms in surfactant head sulfate and OE groups act as hydrogen-bond acceptors. , Figure a clearly shows that, although the number of SLE2S-surfactant and water-molecule hydrogen bonding interactions decreased, surfactant inside the ceramide bilayer can be stabilized through hydrogen-bonding interactions between surfactant heads and ceramide lipid molecules, where ceramide head hydroxyl and N–H groups act as hydrogen-bond donors. Such hydrogen-bonding interactions between surfactant and lipid molecules cannot be established in the DMPC bilayer because no hydrogen-bond donors exist in the DMPC molecule (Figure b).…”
Section: Resultsmentioning
confidence: 99%
“…As a result, depending on the SLE2S monomer position, the simulation time for a single US trajectory in each window varied from 30 to 80 ns, during which the first 10–60 ns and last 20 ns were used as equilibration and production runs, respectively. Two PMF profiles were generated for system 4; one at 1 bar and 350.15 K and the other at 1 bar and 313.15 K. The PMF profile generated for system 5 was calculated at 1 bar and 350.15 K, while the one generated for system 6 was obtained at 1 bar and 313.15 K. Thermodynamic integration (TI) was also employed to decompose the PMF profiles into individual components to determine the influence of each system component on the Gibbs free energy of SLE2S monomer transfer. …”
Section: Computational and Experimental Methodsmentioning
confidence: 99%
“…46−48 In our study, we set the value of Δt to be 2 ps for calculations of the position-dependent diffusion coefficient according to a previous study of glucose transport through a CPN. 20 The ABF trajectories for the PMF calculations were employed as input coordinates for the BI/MC method. The position-dependent diffusion coefficient profiles for the three protonation states were reconstructed using a fitting function given as 49 i k j j j j y…”
Section: Description Of Simulations For Transport Of Threementioning
confidence: 99%