Advanced Sampling and Modeling in Molecular Simulations for Slow and Large-Scale Biomolecular Dynamics

2022 ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 2670-2680 ◽  
Author(s):  
Jordi Juárez-Jiménez ◽  
Arun A. Gupta ◽  
Gogulan Karunanithy ◽  
Antonia S. J. S. Mey ◽  
Charis Georgiou ◽  
...  

Molecular simulations were used to design large scale loop motions in the enzyme cyclophilin A and NMR and biophysical methods were employed to validate the models.


2013 ◽  
Vol 58 ◽  
pp. 167-176 ◽  
Author(s):  
Andres Jaramillo-Botero ◽  
Qi An ◽  
Patrick L. Theofanis ◽  
William A. Goddard

2014 ◽  
Vol 6 (4) ◽  
pp. 344-344
Author(s):  
Camilo A. Jimenez-Cruz ◽  
Seung-gu Kang ◽  
Ruhong Zhou

2020 ◽  
Vol 56 (100) ◽  
pp. 15635-15638
Author(s):  
Johannes Zeman ◽  
Svyatoslav Kondrat ◽  
Christian Holm

Large-scale molecular simulations reveal two screening lengths satisfying distinct scaling relations but with unprecedented accuracy no underscreening is detected for concentrated ionic bulk systems.


2014 ◽  
Vol 6 (4) ◽  
pp. 329-343 ◽  
Author(s):  
Camilo A. Jimenez-Cruz ◽  
Seung-gu Kang ◽  
Ruhong Zhou

2020 ◽  
Author(s):  
Wei Lu ◽  
Carlos Bueno ◽  
Nicholas P. Schafer ◽  
Joshua Moller ◽  
Shikai Jin ◽  
...  

AbstractWe present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMM’s Custom Forces software framework. By utilizing GPUs, we achieve more than a 100-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a CPU.We showcase the benefits of OpenMM’s Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsen’s early Nobel prize winning experiments [1] by using OpenMM’s Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments.In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology.Author summaryThe cell’s most important pieces of machinery are large complexes of proteins often along with nucleic acids. From the ribosome, to CRISPR-Cas9, to transcription factors and DNA-wrangling proteins like the SMC-Kleisins, these complexes allow organisms to replicate and enable cells to respond to environmental cues. Computer simulation is a key technology that can be used to connect physical theories with biological reality. Unfortunately, the time and length scales accessible to molecular simulation have not kept pace with our ambition to study the cell’s molecular factories. Many simulation codes also unfortunately remain effectively locked away from the user community who need to modify them as more of the underlying physics is learned. In this paper, we present OpenAWSEM and Open3SPN2, two new easy-to-use and easy to modify implementations of efficient and accurate coarse-grained protein and DNA simulation forcefields that can now be run hundreds of times faster than before, thereby making studies of large biomolecular machines more facile.


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