Efficient conformational sampling of proteins based on a multi-dimensional TaBoo SeArch algorithm: An application to folding of chignolin in explicit solvent

Harada, Ryuhei; Takano, Yu; Shigeta, Yasuteru

doi:10.1016/j.cplett.2015.04.039

Cited by 11 publications

(8 citation statements)

References 34 publications

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“…For example, PCA is performed using already stocked MD snapshots, providing a set of principal modes, and they are used for spanning the high-dimensional subspace. Indeed, we have adopted the principal modes to promote conformational transitions within the same concept of PaCS-MD. , Furthermore, we have established an option where the number of the RCs obtained by PCA is automatically adjusted during the actual simulations, resulting in higher conformational sampling efficiency …”

Section: Results and Discussionmentioning

confidence: 99%

“…34,49 Furthermore, we have established an option where the number of the RCs obtained by PCA is automatically adjusted during the actual simulations, resulting in higher conformational sampling efficiency. 50 In the chosen subspace, the structural diversities among these stocked MD snapshots are defined as their inner products of the principal coordinates. Therefore, a set of starting configurations is redistributed based on these inner products so that the selected configurations are structurally uncorrelated with each other.…”

Section: Resultsmentioning

confidence: 99%

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Independent Nontargeted Parallel Cascade Selection Molecular Dynamics (Ino-PaCS-MD) to Enhance the Conformational Sampling of Proteins

Yasuda

Morita

Shigeta

et al. 2021

J. Chem. Theory Comput.

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Biological functions are related to long-time protein dynamics (rare events) that are induced over microseconds. Such protein dynamics can be investigated using molecular dynamics (MD) simulations. However, the detection of rare events remains challenging using conventional MD (cMD) since the accessible timescales of cMD are shorter than those of the biological functions. Recently, the parallel cascade selection MD (PaCS-MD) has been proposed to detect such rare events, wherein transition paths are generated between a given reactant and product. As an extension, the nontargeted PaCS-MD (nt-PaCS-MD) has been proposed to predict the transition paths without requiring reference to any product. Thus, as a further extension, we herein propose independent nt-PaCS-MD, namely, Ino-PaCS-MD, wherein multiple walkers are launched from a set of different starting configurations. Each walker repeats a cycle of restarting short-time MD simulations from configurations with high potentials for making transitions to neighboring metastable states. To further enhance the sampling ability, Ino-PaCS-MD temporarily stops the conformational search and periodically resets the starting configurations so that they are uniformly distributed in a conformational subspace, thereby preventing a given protein from being trapped in one of the metastable states. As a demonstration, Ino-PaCS-MD successfully detects rare events of a maltose-binding protein as open−close transitions with a nanosecond-order simulation time, although a microsecond-order cMD simulation failed to detect these rare events, showing the high sampling efficiency of Ino-PaCS-MD.

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Section: Results and Discussionmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Independent Nontargeted Parallel Cascade Selection Molecular Dynamics (Ino-PaCS-MD) to Enhance the Conformational Sampling of Proteins

Yasuda

Morita

Shigeta

et al. 2021

J. Chem. Theory Comput.

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“…For rare event searches, a key point is how to select appropriate seeds with sufficiently high potential to make structural transitions, where measures should be given a priori so as to characterize the structural transitions of interest. Depending on differences in the measures and selection rules, we called these methods (a) the Parallel Cascade Selection Molecular Dynamics (PaCS‐MD), (b) the Fluctuation Flooding Method (FFM), (c) the TaBoo SeArch (TBSA) method, and (d) the Outlier FLOODing (OFLOOD) method (see a review article for details). Despite the simple nature of the protocols, rare events including protein folding and large‐amplitude structural transitions (domain motions, induced fit motion, etc.)…”

Section: Introductionmentioning

confidence: 99%

Sparsity‐weighted outlier FLOODing (OFLOOD) method: Efficient rare event sampling method using sparsity of distribution

2015

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As an extension of the Outlier FLOODing (OFLOOD) method [Harada et al., J. Comput. Chem. 2015, 36, 763], the sparsity of the outliers defined by a hierarchical clustering algorithm, FlexDice, was considered to achieve an efficient conformational search as sparsity-weighted "OFLOOD." In OFLOOD, FlexDice detects areas of sparse distribution as outliers. The outliers are regarded as candidates that have high potential to promote conformational transitions and are employed as initial structures for conformational resampling by restarting molecular dynamics simulations. When detecting outliers, FlexDice defines a rank in the hierarchy for each outlier, which relates to sparsity in the distribution. In this study, we define a lower rank (first ranked), a medium rank (second ranked), and the highest rank (third ranked) outliers, respectively. For instance, the first-ranked outliers are located in a given conformational space away from the clusters (highly sparse distribution), whereas those with the third-ranked outliers are nearby the clusters (a moderately sparse distribution). To achieve the conformational search efficiently, resampling from the outliers with a given rank is performed. As demonstrations, this method was applied to several model systems: Alanine dipeptide, Met-enkephalin, Trp-cage, T4 lysozyme, and glutamine binding protein. In each demonstration, the present method successfully reproduced transitions among metastable states. In particular, the first-ranked OFLOOD highly accelerated the exploration of conformational space by expanding the edges. In contrast, the third-ranked OFLOOD reproduced local transitions among neighboring metastable states intensively. For quantitatively evaluations of sampled snapshots, free energy calculations were performed with a combination of umbrella samplings, providing rigorous landscapes of the biomolecules.

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“…Note here that this cutoff value was not the firm choice. We have often faced with the problem of deciding when to finish conformational search [59][60][61][62][63]. To be more precise, one may consider the convergence of the distribution evaluated from LB-PaCS-MD.…”

Section: The Ligand Binding Path Sampling Efficiency Of Lb-pacs-mdmentioning

confidence: 99%

Ligand Binding Path Sampling Based on Parallel Cascade Selection Molecular Dynamics: LB-PaCS-MD

2022

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Parallel cascade selection molecular dynamics (PaCS-MD) is a rare-event sampling method that generates transition pathways between a reactant and product. To sample the transition pathways, PaCS-MD repeats short-time MD simulations from important configurations as conformational resampling cycles. In this study, PaCS-MD was extended to sample ligand binding pathways toward a target protein, which is referred to as LB-PaCS-MD. In a ligand-concentrated environment, where multiple ligand copies are randomly arranged around the target protein, LB-PaCS-MD allows for the frequent sampling of ligand binding pathways. To select the important configurations, we specified the center of mass (COM) distance between each ligand and the relevant binding site of the target protein, where snapshots generated by the short-time MD simulations were ranked by their COM distance values. From each cycle, snapshots with smaller COM distance values were selected as the important configurations to be resampled using the short-time MD simulations. By repeating conformational resampling cycles, the COM distance values gradually decreased and converged to constants, meaning that a set of ligand binding pathways toward the target protein was sampled by LB-PaCS-MD. To demonstrate relative efficiency, LB-PaCS-MD was applied to several proteins, and their ligand binding pathways were sampled more frequently than conventional MD simulations.

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Efficient conformational sampling of proteins based on a multi-dimensional TaBoo SeArch algorithm: An application to folding of chignolin in explicit solvent

Cited by 11 publications

References 34 publications

Independent Nontargeted Parallel Cascade Selection Molecular Dynamics (Ino-PaCS-MD) to Enhance the Conformational Sampling of Proteins

Independent Nontargeted Parallel Cascade Selection Molecular Dynamics (Ino-PaCS-MD) to Enhance the Conformational Sampling of Proteins

Sparsity‐weighted outlier FLOODing (OFLOOD) method: Efficient rare event sampling method using sparsity of distribution

Ligand Binding Path Sampling Based on Parallel Cascade Selection Molecular Dynamics: LB-PaCS-MD

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