Which similarity measure is better for analyzing protein structures in a molecular dynamics trajectory?

2011 ◽  
Vol 13 (22) ◽  
pp. 10421 ◽  
Author(s):  
Pilar Cossio ◽  
Alessandro Laio ◽  
Fabio Pietrucci
2020 ◽  
Author(s):  
Lim Heo ◽  
Collin Arbour ◽  
Michael Feig

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>


2004 ◽  
Vol 37 (1) ◽  
pp. 103-109 ◽  
Author(s):  
Masaki Kojima ◽  
Alexander A. Timchenko ◽  
Junichi Higo ◽  
Kazuki Ito ◽  
Hiroshi Kihara ◽  
...  

A new algorithm to refine protein structures in solution from small-angle X-ray scattering (SAXS) data was developed based on restrained molecular dynamics (MD). In the method, the sum of squared differences between calculated and observed SAXS intensities was used as a constraint energy function, and the calculation was started from given atomic coordinates, such as those of the crystal. In order to reduce the contribution of the hydration effect to the deviation from the experimental (objective) curve during the dynamics, and purely as an estimate of the efficiency of the algorithm, the calculation was first performed assuming the SAXS curve corresponding to the crystal structure as the objective curve. Next, the calculation was carried out with `real' experimental data, which yielded a structure that satisfied the experimental SAXS curve well. The SAXS data for ribonuclease T1, a single-chain globular protein, were used for the calculation, along with its crystal structure. The results showed that the present algorithm was very effective in the refinement and adjustment of the initial structure so that it could satisfy the objective SAXS data.


1994 ◽  
Vol 116 (10) ◽  
pp. 4461-4462 ◽  
Author(s):  
K. J. McConnell ◽  
R Nirmala ◽  
M. A. Young ◽  
G. Ravishanker ◽  
D. L. Beveridge

2021 ◽  
Vol 17 (5) ◽  
pp. e1008988
Author(s):  
Nikolina ŠoŠtarić ◽  
Vera van Noort

Post-translational modifications (PTMs) play a vital, yet often overlooked role in the living cells through modulation of protein properties, such as localization and affinity towards their interactors, thereby enabling quick adaptation to changing environmental conditions. We have previously benchmarked a computational framework for the prediction of PTMs’ effects on the stability of protein-protein interactions, which has molecular dynamics simulations followed by free energy calculations at its core. In the present work, we apply this framework to publicly available data on Saccharomyces cerevisiae protein structures and PTM sites, identified in both normal and stress conditions. We predict proteome-wide effects of acetylations and phosphorylations on protein-protein interactions and find that acetylations more frequently have locally stabilizing roles in protein interactions, while the opposite is true for phosphorylations. However, the overall impact of PTMs on protein-protein interactions is more complex than a simple sum of local changes caused by the introduction of PTMs and adds to our understanding of PTM cross-talk. We further use the obtained data to calculate the conformational changes brought about by PTMs. Finally, conservation of the analyzed PTM residues in orthologues shows that some predictions for yeast proteins will be mirrored to other organisms, including human. This work, therefore, contributes to our overall understanding of the modulation of the cellular protein interaction networks in yeast and beyond.


Soft Matter ◽  
2021 ◽  
Author(s):  
Rakesh K Vaiwala ◽  
Ganapathy Ayappa

A coarse-grained force field for molecular dynamics simulations of native structures of proteins in a dissipative particle dynamics (DPD) framework is developed. The parameters for bonded interactions are derived by...


1991 ◽  
Vol 10 (4) ◽  
pp. 340-358 ◽  
Author(s):  
John Kuriyan ◽  
Klara Ösapay ◽  
Stephen K. Burley ◽  
Axel T. Brünger ◽  
Wayne A. Hendrickson ◽  
...  

2020 ◽  
Vol 32 (19) ◽  
Author(s):  
Mahzad Khoshlessan ◽  
Ioannis Paraskevakos ◽  
Geoffrey C. Fox ◽  
Shantenu Jha ◽  
Oliver Beckstein

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