Large-scale comparison of protein essential dynamics from molecular dynamics simulations and coarse-grained normal mode analyses

2010 ◽  
Vol 78 (16) ◽  
pp. 3341-3352 ◽  
Author(s):  
Aqeel Ahmed ◽  
Saskia Villinger ◽  
Holger Gohlke
Author(s):  
Mei Zheng ◽  
Andres Jaramillo-Botero ◽  
Xue-hai Ju ◽  
William A. Goddard

Developing a coarse-grained force field for polyacrylamide based on quantum mechanics equation of state.


2020 ◽  
Author(s):  
Florencia Klein ◽  
Daniela Cáceres-Rojas ◽  
Monica Carrasco ◽  
Juan Carlos Tapia ◽  
Julio Caballero ◽  
...  

<p>Although molecular dynamics simulations allow for the study of interactions among virtually all biomolecular entities, metal ions still pose significant challenges to achieve an accurate structural and dynamical description of many biological assemblies. This is particularly the case for coarse-grained (CG) models. Although the reduced computational cost of CG methods often makes them the technique of choice for the study of large biomolecular systems, the parameterization of metal ions is still very crude or simply not available for the vast majority of CG- force fields. Here, we show that incorporating statistical data retrieved from the Protein Data Bank (PDB) to set specific Lennard-Jones interactions can produce structurally accurate CG molecular dynamics simulations. Using this simple approach, we provide a set of interaction parameters for Calcium, Magnesium, and Zinc ions, which cover more than 80% of the metal-bound structures reported on the PDB. Simulations performed using the SIRAH force field on several proteins and DNA systems show that using the present approach it is possible to obtain non-bonded interaction parameters that obviate the use of topological constraints. </p>


Author(s):  
Łukasz Piotr Baran ◽  
Wojciech Rżysko ◽  
Dariusz Tarasewicz

In this study we have performed extensive coarse-grained molecular dynamics simulations of the self-assembly of tetra-substituted molecules. We have found that such molecules are able to form a variety of...


2016 ◽  
Vol 34 (4) ◽  
pp. 041509 ◽  
Author(s):  
Daniel Edström ◽  
Davide G. Sangiovanni ◽  
Lars Hultman ◽  
Ivan Petrov ◽  
J. E. Greene ◽  
...  

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