2009
DOI: 10.1073/pnas.0905466106
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Constructing the equilibrium ensemble of folding pathways from short off-equilibrium simulations

Abstract: Characterizing the equilibrium ensemble of folding pathways, including their relative probability, is one of the major challenges in protein folding theory today. Although this information is in principle accessible via all-atom molecular dynamics simulations, it is difficult to compute in practice because protein folding is a rare event and the affordable simulation length is typically not sufficient to observe an appreciable number of folding events, unless very simplified protein models are used. Here we pr… Show more

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Cited by 781 publications
(752 citation statements)
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References 38 publications
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“…Recently the interest in MSMs has increased a lot, for it had been demonstrated that MSMs can be constructed even for very high dimensional systems [25]. They have been especially useful for modelling the interesting slow dynamics of biomolecules [21,[28][29][30][31][32] and materials [33] (there under the name "kinetic Monte Carlo"). If the system exhibits metastability and the jump process between the metastable sets are approximately Markovian, the corresponding MSM simply describes the Markov process that jumps between the sets with the aggregated statistics of the original process.…”
Section: Markov State Modelsmentioning
confidence: 99%
See 1 more Smart Citation
“…Recently the interest in MSMs has increased a lot, for it had been demonstrated that MSMs can be constructed even for very high dimensional systems [25]. They have been especially useful for modelling the interesting slow dynamics of biomolecules [21,[28][29][30][31][32] and materials [33] (there under the name "kinetic Monte Carlo"). If the system exhibits metastability and the jump process between the metastable sets are approximately Markovian, the corresponding MSM simply describes the Markov process that jumps between the sets with the aggregated statistics of the original process.…”
Section: Markov State Modelsmentioning
confidence: 99%
“…These transitions span large ranges of length scales, time scales and complexity, and include processes as important as folding [15,16], complex conformational rearrangements between native protein substates [17,18], and ligand binding [19]. MD simulations are becoming increasingly accepted as a tool to investigate both the structural and the dynamical features of these transitions at a level of detail that is beyond that accessible in laboratory experiments [20][21][22].…”
Section: Molecular Dynamics and Markov State Modelsmentioning
confidence: 99%
“…MSM-weighted probability distributions, both one-and two-dimensional, are obtained by binning the raw data within each MSM state and weighting it by the MSM equilibrium state population. High-flux pathways between active and inactive states and MSM state committor values are also calculated from T ij using the transition matrix definition of transition path theory 57,58 . Committor values measure the probability of reaching the active state (at values near one) before returning to the inactive state (at values near zero).…”
Section: Methodsmentioning
confidence: 99%
“…Interestingly, these four metastable states obtained from hidden MSM correspond to the energy minima basin (ms1-4) obtained using REMD data. Furthermore, we used transition path theory (TPT) [53][54][55] as implemented in PyEMMA 56 package to identify the folding paths from unfolded state. The TPT analysis suggests that transition from unfolded state (ms1) to folded state (ms4) is more preferable through intermediate ms3 than ms2 (helical state).…”
Section: Markov State Model Along Optimized Dimensions Kineticallymentioning
confidence: 99%