scholarly journals Conformational and Dynamical Effects of Tyr32 Phosphorylation in K-Ras: Molecular Dynamics Simulation and Markov State Models Analysis

2019 ◽  
Vol 123 (36) ◽  
pp. 7667-7675 ◽  
Author(s):  
Mohammed Khaled ◽  
Alemayehu Gorfe ◽  
Abdallah Sayyed-Ahmad
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Dynamics Simulation ◽  
Markov State ◽  
Markov State Models ◽  
State Models

scholarly journals Reconciling simulated ensembles of apomyoglobin with experimental HDX data using Bayesian inference and multi-ensemble Markov State Models

2019 ◽  
Author(s):  
Hongbin Wan ◽  
Yunhui Ge ◽  
Asghar Razavi ◽  
Vincent A. Voelz
Keyword(s):  
Molecular Dynamics ◽  
Bayesian Inference ◽  
Conformational Dynamics ◽  
Molecular Simulations ◽  
Dynamics Simulation ◽  
Trajectory Data ◽  
Protection Factor ◽  
Markov State ◽  
Markov State Models ◽  
State Models

AbstractHydrogen/deuterium exchange (HDX) is a powerful technique to investigate protein conformational dynamics at amino acid resolution. Because HDX provides a measurement of solvent exposure of backbone hydrogens, ensemble-averaged over potentially slow kinetic processes, it has been challenging to use HDX protection factors to refine structural ensembles obtained from molecular dynamics simulations. This entails two dual challenges: (1) identifying structural observables that best correlate with backbone amide protection from exchange, and (2) restraining these observables in molecular simulations to model ensembles consistent with experimental measurements. Here, we make significant progress on both fronts. First, we describe an improved predictor of HDX protection factors from structural observables in simulated ensembles, parameterized from ultra-long molecular dynamics simulation trajectory data, with a Bayesian inference approach used to retain the full posterior distribution of model parameters.We next present a new method for obtaining simulated ensembles in agreement with experimental HDX protection factors, in which molecular simulations are performed at various temperatures and restraint biases, and used to construct multi-ensemble Markov State Models (MSMs). Finally, the BICePs algorithm (Bayesian Inference of Conformational Populations) is then used with our HDX protection factor predictor to infer which thermodynamic ensemble agrees best with experiment, and estimate populations of each conformational state in the MSM. To illustrate the approach, we use a combination of HDX protection factor restraints and chemical shift restraints to model the conformational ensemble of apomyoglobin at pH 6. The resulting ensemble agrees well with experiment, and gives insight into the all-atom structure of disordered helices F and H in the absence of heme.Graphical TOC Entry

scholarly journals Unfolding mechanism of thrombin-binding aptamer revealed by molecular dynamics simulation and Markov State Model

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Xiaojun Zeng ◽  
Liyun Zhang ◽  
Xiuchan Xiao ◽  
Yuanyuan Jiang ◽  
Yanzhi Guo ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
State Model ◽  
Dynamics Simulation ◽  
Markov State Model ◽  
Markov State

scholarly journals Optimal control of molecular dynamics using Markov state models

2012 ◽  
Vol 134 (1) ◽  
pp. 259-282 ◽  
Author(s):  
Christof Schütte ◽  
Stefanie Winkelmann ◽  
Carsten Hartmann
Keyword(s):  
Molecular Dynamics ◽  
Optimal Control ◽  
Markov State ◽  
Markov State Models ◽  
State Models

scholarly journals The mechanism of RNA base fraying: Molecular dynamics simulations analyzed with core-set Markov state models

2019 ◽  
Vol 150 (15) ◽  
pp. 154123 ◽  
Author(s):  
Giovanni Pinamonti ◽  
Fabian Paul ◽  
Frank Noé ◽  
Alex Rodriguez ◽  
Giovanni Bussi
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Markov State ◽  
Markov State Models ◽  
Core Set ◽  
State Models ◽  
Dynamics Simulations
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