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Articles by Berk Hess
Computer Science > Distributed, Parallel, and Cluster Computing
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Bridging the molecular and the continuous pictures of wetting dynamics on hydrophilic surfaces
Nyckelord: TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Wetting; Contact Lines; Molecular Dynamics; Fluid Dynamics; Multiscale Modeling; Molecular Kinetic Theory; Physics; Fysik; Sammanfattning: The term ‘wetting' is used by the scientific community when referring to the affinity and the dynamics of liquid films, drops or menisci over solid surfaces.
Constant-pH molecular dynamics simulations of closed and open states of a proton-gated ion channel
Abstract Although traditional molecular dynamics simulations successfully capture a variety of different molecular interactions, the protonation states of titratable residues are kept static.
Near-wall depletion and layering affect contact line friction of multicomponent liquids
The main causes of energy dissipation in micro- and nanoscale wetting are viscosity and liquid-solid friction localized in the three-phase contact line region. Theoretical models predict the contact line friction coefficient to correlate with the shear viscosity of the wetting fluid. Experiments conducted to investigate such correlation have not singled out a unique scaling law between the two coefficients.
Constant-pH molecular dynamics simulations of progressive activation in a proton-gated ion channel
Abstract Allosteric activation of ligand-gated ion channels is critical to electrochemical signal transduction, yet the details of how structural transitions are induced remain unclear. The proton-gated Gloeobacter violaceus ligand-gated ion channel (GLIC) offers an invaluable model system to study this process, and with high-resolution structures available it should in principle be possible to approach computationally.
GROMACS 2023.3 Source code
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DOI 10.5281/zenodo.10017686 [](https://doi.org/10.5281/zenodo.10017686) .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.10017686.svg :target: https://doi.org/10.5281/zenodo.10017686 <a href="https://doi.org/10.5281/zenodo.10017686"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.10017686.svg" alt="DOI"></a> https://zenodo.org/badge/DOI/10.5281/zenodo.10017686.svg https://doi.org/10.5281/zenodo.10017686
By Mark Abraham, Andrey Alekseenko, Cathrine Bergh, Christian Blau, Mahesh Doijade, Vytautas Gapsys, Gaurav C. Garg, Sergey Gorelov, Alan Gray, M. Eric Irrgang, Joe Jordan, Christoph Junghans, Sebastian Keller, Carsten Kutzner, Justin A. Lemkul, Magnus Lundborg, Pascal T. Merz, Vedran Miletić, Dmitry Morozov, Szilárd Páll, Roland Schulz, Michael R. Shirts, Alexey V. Shvetsov, Philip Turner, Alessandra Villa, Artem Zhmurov, Paul Bauer, Berk Hess, Erik Lindahl, Eliane Briand, Stefan Fleischmann, Gilles Gouaillardet, Farzaneh Jalalypour, Prashanth Kanduri, Bálint Soproni, Carsten Uphoff, Sebastian Wingbermühle
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zenodo.org
Skin permeability prediction with MD simulation sampling spatial and alchemical reaction coordinates
Permeability coefficient calculations The permeability coefficient, KP, and the permeation resistance, R, were calculated as follows ( ): 1KP=R=∫Z1Z2eβΔG(z)D(z)dz, (1) where ΔG is the difference in free energy compared with the reference state, and D is the local diffusion coefficient across the skin’s barrier structure (dz). As mentioned above, we calculated the permeability through 30±6 layers of the lipid barrier.
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