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Extending the Nonbonded Cationic Dummy Model to Account for Ion-Induced Dipole Interactions
[Image: see text] Modeling metalloproteins often requires classical molecular dynamics (MD) simulations in order to capture their relevant motions, which in turn necessitates reliable descriptions of the metal centers involved. One of the most successful approaches to date is provided by the “cation...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical
Society
2017
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5672556/ https://www.ncbi.nlm.nih.gov/pubmed/29022713 http://dx.doi.org/10.1021/acs.jpclett.7b02358 |
Sumario: | [Image: see text] Modeling metalloproteins often requires classical molecular dynamics (MD) simulations in order to capture their relevant motions, which in turn necessitates reliable descriptions of the metal centers involved. One of the most successful approaches to date is provided by the “cationic dummy model”, where the positive charge of the metal ion is transferred toward dummy particles that are bonded to the central metal ion in a predefined coordination geometry. While this approach allows for ligand exchange, and captures the correct electrostatics as demonstrated for different divalent metal ions, current dummy models neglect ion-induced dipole interactions. In the present work, we resolve this weakness by taking advantage of the recently introduced 12–6–4 type Lennard-Jones potential to include ion-induced dipole interactions. We revise our previous dummy model for Mg(2+) and demonstrate that the resulting model can simultaneously reproduce the experimental solvation free energy and metal–ligand distances without the need for artificial restraints or bonds. As ion-induced dipole interactions become particularly important for highly charged metal ions, we develop dummy models for the biologically relevant ions Al(3+), Fe(3+), and Cr(3+). Finally, the effectiveness of our new models is demonstrated in MD simulations of several diverse (and highly challenging to simulate) metalloproteins. |
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