Comment on “Bi-layering at ionic liquid surfaces: a sum – frequency generation vibrational spectroscopy – and molecular dynamics simulation-based study” by T. Iwahashi, T. Ishiyama, Y. Sakai, A. Morita, D. Kim and Y. Ouchi, Phys. Chem. Chem. Phys., 2020, 22, 12565

2021 ◽  
Author(s):  
Moshe Deutsch ◽  
Olaf M. Magnussen ◽  
Julia Haddad ◽  
Diego Pontoni ◽  
Bridget M. Murphy ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Ionic Liquid ◽  
Molecular Dynamics Simulation ◽  
Surface Structure ◽  
Chem Phys ◽  
Dynamics Simulation ◽  
X Ray ◽  
Sum Frequency ◽  
Simulation Based ◽  
Phys Chem Chem Phys

Serious discrepancies are demonstrated between the proposed mono/bilayer surface structure and X-ray measurements, which rather support a depth-decaying multilayer surface structure.

scholarly journals Surface Structure of Quaternary Ammonium Based Ionic Liquid Studied Using Molecular Dynamics Simulation

2015 ◽  
Vol 64 (3) ◽  
pp. 219-224 ◽  
Author(s):  
Seiji KATAKURA ◽  
Naoya NISHI ◽  
Kazuya KOBAYASHI ◽  
Ken-ichi AMANO ◽  
Tetsuo SAKKA
Keyword(s):  
Molecular Dynamics ◽  
Ionic Liquid ◽  
Molecular Dynamics Simulation ◽  
Surface Structure ◽  
Quaternary Ammonium ◽  
Dynamics Simulation

Reply to the ‘Comment on “Bi-layering at ionic liquid surfaces: a sum-frequency generation vibrational spectroscopy- and molecular dynamics simulation-based study”’ by M. Deutsch, O. M. Magnussen, J. Haddad, D. Pontoni, B. M. Murphy and B. M. Ocko, Phys. Chem. Chem. Phys., 2021, DOI: 10.1039/D0CP04882H

2021 ◽  
Vol 23 (8) ◽  
pp. 5028-5030
Author(s):  
Takashi Iwahashi ◽  
Tatsuya Ishiyama ◽  
Yasunari Sakai ◽  
Akihiro Morita ◽  
Doseok Kim ◽  
...  
Keyword(s):  
Ionic Liquid ◽  
Vibrational Spectroscopy ◽  
Md Simulation ◽  
Layer Structure ◽  
Chem Phys ◽  
Dynamics Simulation ◽  
Simulation Studies ◽  
Sum Frequency ◽  
Simulation Based ◽  
Liquid Surfaces

IV-SFG vibrational spectroscopy and MD simulation studies successfully demonstrate the presence of a “head-to-head” bi-layer structure at ionic liquid surfaces.

Bi-layering at ionic liquid surfaces: a sum-frequency generation vibrational spectroscopy- and molecular dynamics simulation-based study

2020 ◽  
Vol 22 (22) ◽  
pp. 12565-12576
Author(s):  
Takashi Iwahashi ◽  
Tatsuya Ishiyama ◽  
Yasunari Sakai ◽  
Akihiro Morita ◽  
Doseok Kim ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Ionic Liquid ◽  
Vibrational Spectroscopy ◽  
Md Simulation ◽  
Layer Structure ◽  
Dynamics Simulation ◽  
Simulation Studies ◽  
Sum Frequency ◽  
Simulation Based ◽  
Liquid Surfaces

IV-SFG vibrational spectroscopy and MD simulation studies successfully demonstrate the presence of a “head-to-head” bi-layer structure at ionic liquid surfaces.

scholarly journals Correction: Molecular dynamics simulation study of distribution and dynamics of aqueous solutions of uranyl ions: the effect of varying temperature and concentration

2016 ◽  
Vol 18 (2) ◽  
pp. 1344-1345 ◽  
Author(s):  
Manish Chopra ◽  
Niharendu Choudhury
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Aqueous Solutions ◽  
Simulation Study ◽  
Chem Phys ◽  
Dynamics Simulation ◽  
Uranyl Ions ◽  
Phys Chem Chem Phys

Correction for ‘Molecular dynamics simulation study of distribution and dynamics of aqueous solutions of uranyl ions: the effect of varying temperature and concentration’ by Manish Chopra et al., Phys. Chem. Chem. Phys., 2015, 17, 27840–27850.

Improved Sampling Strategies for Protein Model Refinement based on Molecular Dynamics Simulation

2020 ◽  
Author(s):  
Lim Heo ◽  
Collin Arbour ◽  
Michael Feig
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Structure Prediction ◽  
Protein Structures ◽  
Conformational Space ◽  
Dynamics Simulation ◽  
Model Refinement ◽  
Protein Model ◽  
Lower Accuracy ◽  
Simulation Based

Protein structures provide valuable information for understanding biological processes. Protein structures can be determined by experimental methods such as X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, or cryogenic electron microscopy. As an alternative, in silico methods can be used to predict protein structures. Those methods utilize protein structure databases for structure prediction via template-based modeling or for training machine-learning models to generate predictions. Structure prediction for proteins distant from proteins with known structures often results in lower accuracy with respect to the true physiological structures. Physics-based protein model refinement methods can be applied to improve model accuracy in the predicted models. Refinement methods rely on conformational sampling around the predicted structures, and if structures closer to the native states are sampled, improvements in the model quality become possible. Molecular dynamics simulations have been especially successful for improving model qualities but although consistent refinement can be achieved, the improvements in model qualities are still moderate. To extend the refinement performance of a simulation-based protocol, we explored new schemes that focus on an optimized use of biasing functions and the application of increased simulation temperatures. In addition, we tested the use of alternative initial models so that the simulations can explore conformational space more broadly. Based on the insight of this analysis we are proposing a new refinement protocol that significantly outperformed previous state-of-the-art molecular dynamics simulation-based protocols in the benchmark tests described here. <br>

Sign in / Sign up

Export Citation Format

Share Document