Delineation of Folding Pathways of a β-Sheet Miniprotein

Zheng, Wenwei; Qi, Bo; Rohrdanz, Mary A.; Caflisch, Amedeo; Dinner, Aaron R.; Clementi, Cecilia

doi:10.1021/jp2076935

Cited by 43 publications

(67 citation statements)

References 43 publications

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“…The last conformations that come in equilibrium with the others are the Ch-curl conformations, which are less stable than the antiparallel β-strands and more difficult to form dynamically because of the distant N-and C-terminal strands. The observed hierarchy of the establishment of equilibrium between the characteristic conformations is in good agreement with the results of the previous studies 6,11,12,25,28,[30][31][32]45 and has allowed further insight into the process of beta3s folding. One issue of particular interest is the difference between the Cs-or and Ns-or pathways, which has been indicated in the early work 25 and confirmed in the later, the first-passage folding studies: 11,12 although Cs-or and Ns-or conformations are "symmetrical" in that each of them has one hairpin formed and the other unstructured, the Ns-or pathway prevails.…”

Section: Resultssupporting

confidence: 90%

Equilibration of Protein States: A Time Dependent Free-Energy Disconnectivity Graph

Chekmarev

2015

J. Phys. Chem. B

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The process of equilibration of protein states in a three-stranded antiparallel β-sheet miniprotein is studied using a time-dependent free energy disconnectivity graph. To determine the rates of transitions, the molecular dynamics simulation results of a recent work (Kalgin, I. V.; J. Phys. Chem. B 2013, 117, 6092) are employed. The vertices of the graph are the free energies of characteristic states of the protein, and the edges are the transition state free energies. To determine the latter, the "complete" partition function (Eyring, 1935) is used, which includes the translational partition function corresponding to the ballistic motion of the system along the reaction coordinate. The distance along the reaction coordinate that enters the translational partition function is taken to be proportional to the observation time and thus measures the number of representative points that cross the transition state surface during given time. As the time increases, the free energy barriers between the clusters of characteristic conformations (native-like, helical, and β-sheet conformations of different degree of organization) decrease and (local) equilibrium between the clusters is established. With time, these clusters are grouped into larger clusters, extending the equilibrium to a larger portion of protein states.

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Section: Resultssupporting

confidence: 90%

Equilibration of Protein States: A Time Dependent Free-Energy Disconnectivity Graph

Chekmarev

2015

J. Phys. Chem. B

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“…Furthermore, these pathways are corroborated by previous work (there is an extensive literature on this topic, see e.g. [17]–[20]), which posits that Loop 1 formation is initiated at near the loop region and “zippers up” via hydrogen bonding, and Loop 2 is formed by a hydrophobic collapse (a transition which may be inferred from the 404 → 600 edge).…”

Section: Awe Resultssupporting

confidence: 81%

Folding proteins at 500 ns/hour with Work Queue

Abdul-Wahid

Rajan

et al. 2012

2012 IEEE 8th International Conference on E-Science

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Molecular modeling is a field that traditionally has large computational costs. Until recently, most simulation techniques relied on long trajectories, which inherently have poor scalability. A new class of methods is proposed that requires only a large number of short calculations, and for which minimal communication between computer nodes is required. We considered one of the more accurate variants called Accelerated Weighted Ensemble Dynamics (AWE) and for which distributed computing can be made efficient. We implemented AWE using the Work Queue framework for task management and applied it to an all atom protein model (Fip35 WW domain). We can run with excellent scalability by simultaneously utilizing heterogeneous resources from multiple computing platforms such as clouds (Amazon EC2, Microsoft Azure), dedicated clusters, grids, on multiple architectures (CPU/GPU, 32/64bit), and in a dynamic environment in which processes are regularly added or removed from the pool. This has allowed us to achieve an aggregate sampling rate of over 500 ns/hour. As a comparison, a single process typically achieves 0.1 ns/hour.

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“…In practice, we have found that values near the low boundary of the region produce plots with more clearly visible clusters. We refer the reader to the work of Clementi et al 34,58,59 for additional considerations and algorithmic suggestions for the choice of . Table II indicates how well formed are the clusters of the optimal (k = 16) k-means partitioning.…”

Section: Appendix A: Choice Of Epsilonmentioning

confidence: 99%

Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

Nedialkova

Amat

Kevrekidis

et al. 2014

The Journal of Chemical Physics

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Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlap with clusters obtained previously by using the backbone dihedral angles as input, with small-but nontrivial-differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space.

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Delineation of Folding Pathways of a β-Sheet Miniprotein

Cited by 43 publications

References 43 publications

Equilibration of Protein States: A Time Dependent Free-Energy Disconnectivity Graph

Equilibration of Protein States: A Time Dependent Free-Energy Disconnectivity Graph

Folding proteins at 500 ns/hour with Work Queue

Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions

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