Finding Conformational Transition Pathways from Discrete Molecular Dynamics Simulations

Sfriso, Pedro; Emperador, Agustí; Orellana, Laura; Gelpí, Josep Lluís; Orozco, Modesto

doi:10.1021/ct300494q

Cited by 29 publications

(46 citation statements)

References 92 publications

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“…However, broader patterns also emerge. For instance, the MolMovDB [20] pathways are very similar to the transitions produced by Maxwell Daemon discrete MD [21] and generally equidistant from all other pathways, suggesting that MolMovDB produces in some sense an 'average' pathway. The all-atom DIMS-MD [13,31] pathways, on the other hand, are typically farthest from any other transitions and also from each other, indicating that the method produces structurally diverse transitions [13].…”

Section: Quantitative Path Comparisonmentioning

confidence: 88%

“…7 we show a quantitative comparison of a number of apo-AdK closed → open transitions that were simulated in our earlier work [31] or were generated by publicly available servers [14,[16][17][18][20][21][22]. For each method, two pathways were generated, utilizing either inherent stochasticity in the method or small parameter variations for fully de-Sean L. Seyler and Oliver Beckstein Figure 7.…”

Section: Quantitative Path Comparisonmentioning

confidence: 99%

“…For each method, two pathways were generated, utilizing either inherent stochasticity in the method or small parameter variations for fully de-Sean L. Seyler and Oliver Beckstein Figure 7. Quantitative comparison of apo-AdK transition paths generated by a range of methods [152]: Two independent trajectories from DIMS [13,31], MAP (MinActionPath) [16], GeoPath [14], iENM [17], pathENM [18], NIMSim [22], MaxD (Maxwell Daemon discrete MD) [21], MolMovDB [20]. Distances are measured inÅ, corresponding to a Cα-RMSD [152].…”

Section: Quantitative Path Comparisonmentioning

confidence: 99%

“…The simulation of conformational transitions can be roughly subdivided into three distinct, but interdependent objectives: (1) accurately simulate conformational transition ensembles, (2) determine underlying free energy landscapes, and (3) predict transition probabilities and rates. A wide range of computational approaches to simulate rare transition events have been proposed [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24], which all, however, necessitate certain assumptions; furthermore, it is not known how accurately these different methods reproduce real transition events. Nevertheless, due to their computational efficiency in comparison to pure equilibrium MD, they remain important tools for generating transition ensembles and gaining intuition for the dynamics of macromolecular systems.…”

Section: Introductionmentioning

confidence: 99%

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Sampling large conformational transitions: adenylate kinase as a testing ground

Seyler

Beckstein

2014

Molecular Simulation

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A fundamental problem in computational biophysics is to deduce the function of a protein from the structure. Many biological macromolecules such as enzymes, molecular motors, or membrane transport proteins perform their function by cycling between multiple conformational states. Understanding such conformational transitions, which typically occur on the millisecond to second time scale, is central to understanding protein function. Molecular dynamics (MD) computer simulations have become an important tool to connect molecular structure to function but equilibrium MD simulations are rarely able to sample on time scales longer than a few microseconds-orders of magnitudes shorter than the time scales of interest. A range of different simulation methods have been proposed to overcome this time-scale limitation. These include calculations of the free energy landscape and path sampling methods to directly sample transitions between known conformations. All these methods solve the problem to sample infrequently occupied but important regions of configuration space. Many path-sampling algorithms have been applied to the closed ↔ open transition of the enzyme adenylate kinase (AdK), which undergoes a large, clamshell-like conformational transition between an open and a closed state. Here we review approaches to sample macromolecular transitions through the lens of AdK. We focus our main discussion on the current state of knowledge-both from simulations and experiments-about the transition pathways of ligand-free AdK, its energy landscape, transition rates, and interactions with substrates. We conclude with a comparison of the discussed approaches with a view towards quantitative evaluation of path-sampling methods.

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Section: Quantitative Path Comparisonmentioning

confidence: 88%

Section: Quantitative Path Comparisonmentioning

confidence: 99%

Section: Quantitative Path Comparisonmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Sampling large conformational transitions: adenylate kinase as a testing ground

Seyler

Beckstein

2014

Molecular Simulation

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“…Conformational transition pathways were generated using the BD algorithm discussed above together with a dynamic importance sampling algorithm incorporated to guide the simulation towards the target structure, instead of eigenvectors/eigenvalues obtained from ENM-NMA or MD-PCA 56,57 . The biasing function for the dynamic importance sampling was the sum of internal distances of the target structure.…”

Section: Methodsmentioning

confidence: 99%

Correlated motions are a fundamental property of β-sheets

et al. 2014

Self Cite

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Correlated motions in proteins can mediate fundamental biochemical processes such as signal transduction and allostery. The mechanisms that underlie these processes remain largely unknown due mainly to limitations in their direct detection. Here, based on a detailed analysis of protein structures deposited in the protein data bank, as well as on state-of-the art molecular simulations, we provide general evidence for the transfer of structural information by correlated backbone motions, mediated by hydrogen bonds, across b-sheets. We also show that the observed local and long-range correlated motions are mediated by the collective motions of b-sheets and investigate their role in large-scale conformational changes. Correlated motions represent a fundamental property of b-sheets that contributes to protein function.

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A method for predicting protein conformational pathways by using molecular dynamics simulations guided by difference distance matrices

Yonezawa

2016

J Comput Chem

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Here, an efficient method that predicts natural transition pathways between two endpoint states of an allosteric protein has been proposed. This method helps create structures that bridge these endpoints through multiple iterative and unbiased molecular dynamics simulations with explicit water. Difference distance matrices provide an approach for identifying states involving concerted slow motion. A series of structures are readily generated along the transition pathways of adenylate kinase. Predicted structures may be useful for an initial pathway to evaluate free energy landscapes via umbrella sampling and chain-of-states methods. © 2016 Wiley Periodicals, Inc.

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Finding Conformational Transition Pathways from Discrete Molecular Dynamics Simulations

Cited by 29 publications

References 92 publications

Sampling large conformational transitions: adenylate kinase as a testing ground

Sampling large conformational transitions: adenylate kinase as a testing ground

Correlated motions are a fundamental property of β-sheets

A method for predicting protein conformational pathways by using molecular dynamics simulations guided by difference distance matrices

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