Molecular dynamics simulations of molecules in uniform flow
Flow at the molecular level induces shear-induced unfolding of single proteins and can drive their assembly, the mechanisms of which are not completely understood. To be able to analyze the role of flow on molecules, we present uniform-flow molecular dynamics simulations at atomic level. The pull mo...
Gespeichert in:
| Hauptverfasser: | , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
8 February 2019
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| In: |
Biophysical journal
Year: 2019, Jahrgang: 116, Heft: 9, Pages: 1579-1585 |
| ISSN: | 1542-0086 |
| DOI: | 10.1016/j.bpj.2018.12.025 |
| Online-Zugang: | Verlag, Volltext: https://doi.org/10.1016/j.bpj.2018.12.025 Verlag, Volltext: http://www.sciencedirect.com/science/article/pii/S0006349519301092 
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| Verfasserangaben: | Ana M. Herrera-Rodríguez, Vedran Miletić, Camilo Aponte-Santamaría, and Frauke Gräter |
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| 520 | |a Flow at the molecular level induces shear-induced unfolding of single proteins and can drive their assembly, the mechanisms of which are not completely understood. To be able to analyze the role of flow on molecules, we present uniform-flow molecular dynamics simulations at atomic level. The pull module of the GRoningen MAchine for Chemical Simulations package was extended to be able to force-group atoms within a defined layer of the simulation box. Application of this external enforcement to explicit water molecules, together with the coupling to a thermostat, led to a uniform terminal velocity of the solvent water molecules. We monitored the density of the whole system to establish the conditions under which the simulated flow is well-behaved. A maximal velocity of 1.3 m/s can be generated if a pull slice of 8 nm is used, and high velocities would require larger pull slices to still maintain a stable density. As expected, the target velocity increases linearly with the total external force applied. Finally, we suggest an appropriate setup to stretch a protein by uniform flow, in which protein extensions depend on the flow conditions. Our implementation provides an efficient computational tool to investigate the effect of the flow at the molecular level. | ||
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