An efficient timer and sizer of biomacromolecular motions

Chan, Justin; Lin, Hong-Rui; Takemura, Kazuhiro; Chang, Kai‐Chun; Chang, Yuan-Yu; Joti, Yasumasa; Kitao, Akio; Yang, Lee‐Wei

doi:10.1101/384511

Cited by 3 publications

(5 citation statements)

References 50 publications

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“…This procedure should account for the barriers present along each tICA coordinate in, at least, a coarse manner. 33,81 This time, τ a , is in general different from the inverse of the eigenvalues λ IC (Eq. 10) because that time does not include the mode-dependent energy barrier.…”

Section: Testing the Tica And Le4pd Predictions Of Time Correlation F...mentioning

confidence: 99%

Identifying the leading dynamics of ubiquitin: a comparison between the tICA and the LE4PD slow fluctuations in amino acids' position

Beyerle,

Guenza

2021

Preprint

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Molecular Dynamics (MD) simulations of proteins implicitly contain the information connecting the atomistic molecular structure and proteins' biologically relevant motion, where large-scale fluctuations are deemed to guide folding and function. In the complex multiscale processes described by MD trajectories it is difficult to identify, separate, and study those large-scale fluctuations. This problem can be formulated as the need to identify a small number of collective variables that guide the slow kinetic processes. The most promising method among the ones used to study the slow, leading processes in proteins' dynamics, is the time-structure based or time-lagged independent component analysis, or tICA, which identifies the dominant components in a noisy signal. Recently, we developed an anisotropic Langevin approach for the dynamics of proteins, called the anisotropic Langevin Equation for Protein Dynamics or LE4PD-XYZ. This approach partitions the protein's MD dynamics into mostly uncorrelated, wavelength-dependent, diffusive modes. It associates to each mode a free-energy map, where one measures the spatial extension and the time evolution of the mode-dependent, slow dynamical fluctuations. Here, we compare the tICA modes' predictions with the collective LE4PD-XYZ modes. We observe that the two methods consistently identify the nature and extension of the slowest fluctuation processes. The tICA separates the leading processes in a smaller number of slow modes than the LE4PD does. The LE4PD provides time-dependent information at short times, and a formal connection to the physics of the kinetic processes that are missing in the pure statistical analysis of tICA.

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Section: Testing the Tica And Le4pd Predictions Of Time Correlation F...mentioning

confidence: 99%

Identifying the leading dynamics of ubiquitin: a comparison between the tICA and the LE4PD slow fluctuations in amino acids' position

Beyerle,

Guenza

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Large-scale, slow motions relevant to the protein's biological function typically involve crossing high energy barriers and transitions between minima on the protein's free energy surface (FES). The complexity of the FES renders those large-scale fluctuations both anharmonic and anisotropic [2][3][4][5] . A common technique used to determine the slow, functional motions of proteins is the Principal Component Analysis (PCA) 3,[5][6][7][8] .…”

Section: Introductionmentioning

confidence: 99%

“…For example, timescales have been calculated by integrating the autocorrelation function of the principal components. 4,19 The direction and magnitude of the anisotropic fluctuations have been described using either the so-called 'porcupine plots' [19][20][21][22] or a simple linear interpolation between the extreme structures in the simulation trajectory 23 . In this manuscript, we compare the predictions of the PCA approach for the fluctuations with the largest amplitude to the results of the LE4PD theory applied to the same trajectory.…”

Section: Introductionmentioning

confidence: 99%

Comparison between slow anisotropic LE4PD fluctuations and the principal component analysis modes of ubiquitin

Beyerle

Guenza

2021

The Journal of Chemical Physics

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Proteins' biological function and folding mechanisms are often guided by large-scale, slow motions, which involve crossing high energy barriers. In a simulation trajectory, these slow fluctuations are commonly identified using a principal component analysis (PCA). Despite the popularity of this method, a complete analysis of its predictions based on the physics of protein motion has been so far limited. This study formally connects the PCA to a Langevin model of protein dynamics and analyzes the contributions of energy barriers and hydrodynamic interactions to the slow PCA modes of motion. To do so, we introduce an anisotropic extension of the Langevin Equation for Protein Dynamics, called the LE4PD-XYZ, which formally connects to the PCA 'essential dynamics'. The LE4PD-XYZ is an accurate coarse-grained diffusive method to model protein motion, which describes anisotropic fluctuations in the protein's alpha-carbons. The LE4PD accounts for hydrodynamic effects and mode-dependent free-energy barriers. This study compares large-scale anisotropic fluctuations identified by the LE4PD-XYZ to the mode-dependent PCA's predictions, starting from a microsecond-long alpha-carbon molecular dynamics atomistic trajectory of the protein ubiquitin. We observe that the inclusion of free-energy barriers and hydrodynamic interactions has important effects on the identification and timescales of ubiquitin's slow modes..

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“…Large-scale, slow motions relevant to the protein's biological function typically involve crossing high energy barriers and transitions between minima on the protein's free energy surface (FES). The complexity of the FES renders those large-scale fluctuations both anharmonic and anisotropic [2][3][4][5][6] . A common technique used to determine the slow, functional motions of proteins is the Principal Component Analysis (PCA) 3,[6][7][8][9] .…”

Section: Introductionmentioning

confidence: 99%

“…For example, timescales have been calculated by integrating the autocorrelation function of the principal components. 4,18 The direction and magnitude of the anisotropic fluctuations have been described using either the so-called 'porcupine plots' [18][19][20][21] or a simple linear interpolation between the extreme structures in the simulation trajectory 22 . In this manuscript, we compare the predictions of the PCA approach for the amplitude and timescales of the protein's slow fluctuations to the results of the LE4PD theory applied to the same trajectory.…”

Section: Introductionmentioning

confidence: 99%

Comparison between slow, anisotropic LE4PD fluctuations and the Principal Component Analysis modes of Ubiquitin

Beyerle

Guenza

2021

Preprint

View full text Add to dashboard Cite

Proteins’ biological function and folding mechanisms are often guided by large-scale, slow motions, which involve crossing high energy barriers. In a simulation trajectory, these slow fluctuations are commonly identified using a principal component analysis (PCA). Despite the popularity of this method, a complete analysis of its predictions based on the physics of protein motion has been so far limited. This study formally connects the PCA to a Langevin model of protein dynamics and analyzes the contributions of energy barriers and hydrodynamic interactions to the slow PCA modes of motion. To do so, we introduce an anisotropic extension of the Langevin Equation for Protein Dynamics, called the LE4PD-XYZ, which formally connects to the PCA ‘essential dynamics’. The LE4PD-XYZ is an accurate coarse-grained diffusive method to model protein motion, which describes anisotropic fluctuations in the protein’s alpha-carbons. The LE4PD accounts for hydrodynamic effects and mode-dependent free-energy barriers. This study compares large-scale anisotropic fluctuations identified by the LE4PD-XYZ to the mode-dependent PCA’s predictions, starting from a microsecond-long alpha-carbon molecular dynamics atomistic trajectory of the protein ubiquitin. We observe that the inclusion of free-energy barriers and hydrodynamic interactions has important effects on the identification and timescales of ubiquitin’s slow modes.

show abstract

An efficient timer and sizer of biomacromolecular motions

Cited by 3 publications

References 50 publications

Identifying the leading dynamics of ubiquitin: a comparison between the tICA and the LE4PD slow fluctuations in amino acids' position

Identifying the leading dynamics of ubiquitin: a comparison between the tICA and the LE4PD slow fluctuations in amino acids' position

Comparison between slow anisotropic LE4PD fluctuations and the principal component analysis modes of ubiquitin

Comparison between slow, anisotropic LE4PD fluctuations and the Principal Component Analysis modes of Ubiquitin

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