Source 1primary paper2010Proceedings of the National Academy of Sciences
Toolkit/transition path sampling
transition path sampling
Also known as: transition path sampling of explicit solvent molecular dynamics trajectories
Taxonomy: Technique Branch / Method. Workflows sit above the mechanism and technique branches rather than replacing them.
Summary
Transition path sampling is a computational method applied to explicit-solvent molecular dynamics trajectories to extract atomistic features of conformational reaction networks. In the cited study, it was used to analyze the millisecond partial unfolding transition in the light-driven photocycle of photoactive yellow protein and to predict reaction coordinate models and tentative transition states.
Usefulness & Problems
Why this is useful
This method is useful for dissecting rare conformational transitions at atomistic resolution from molecular dynamics trajectory data. The cited work indicates that combining transition path sampling with likelihood maximization can infer reaction coordinates and tentative transition states without additional simulation.
Problem solved
It addresses the problem of identifying reaction-network structure and plausible reaction coordinates for millisecond light-induced conformational changes that are difficult to interpret directly from standard simulations. In the reported application, it was used for the partial unfolding transition in photoactive yellow protein.
Problem links
Need precise spatiotemporal control with light input
DerivedTransition path sampling is a computational method applied to explicit-solvent molecular dynamics trajectories to extract atomistic insight into reaction networks. In the cited study, it was used to analyze the millisecond partial unfolding transition in the photocycle of photoactive yellow protein and to support prediction of reaction coordinate models and tentative transition states.
Taxonomy & Function
Primary hierarchy
Technique Branch
Method: A concrete computational method used to design, rank, or analyze an engineered system.
Mechanisms
reaction coordinate inference by likelihood maximizationreaction coordinate inference by likelihood maximizationtransition path samplingtransition path samplingTechniques
Computational DesignTarget processes
No target processes tagged yet.
Input: Light
Implementation Constraints
cofactor dependency: cofactor requirement unknownencoding mode: genetically encodedimplementation constraint: context specific validationimplementation constraint: spectral hardware requirementoperating role: builder
The method was implemented on explicit-solvent molecular dynamics trajectories, indicating dependence on prior trajectory generation in an explicit solvent model. The provided evidence does not specify software, force fields, sampling parameters, or system preparation details.
The supplied evidence describes a single application to photoactive yellow protein and does not provide broader benchmarking, comparative performance, or independent replication. Quantitative accuracy, computational cost, and generalizability beyond this system are not specified in the provided evidence.
Validation
Cell-freeBacteriaMammalianMouseHumanTherapeuticIndep. Replication
Supporting Sources
Ranked Claims
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Likelihood maximization analysis predicted reaction coordinate models for each substep and tentative transition states without further simulation.
Likelihood maximization analysis predicts the best model for the reaction coordinates of each substep as well as tentative transition states, without further simulation.
Approval Evidence
1 source1 linked approval claimfirst-pass slug transition-path-sampling
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network
Source:
method applicationsupports
Transition path sampling of explicit solvent molecular dynamics trajectories was used to obtain atomistic insight into the reaction network of the millisecond partial unfolding transition in the photocycle of photoactive yellow protein.
We employ transition path sampling of explicit solvent molecular dynamics trajectories to obtain atomistic insight in the reaction network of the millisecond timescale partial unfolding transition in the photocycle of the bacterial sensor photoactive yellow protein.
Source:
Comparisons
Source-backed strengths
The reported strength is atomistic insight into the reaction network derived from explicit-solvent molecular dynamics trajectories. The study also reports prediction of reaction coordinate models for each substep and tentative transition states without further simulation.
Compared with mathematical model of light-induced expression kinetics
transition path sampling and mathematical model of light-induced expression kinetics address a similar problem space.
Shared frame: same top-level item type; same primary input modality: light
Compared with model bioinformatics analysis
transition path sampling and model bioinformatics analysis address a similar problem space.
Shared frame: same top-level item type; same primary input modality: light
Compared with molecular dynamics simulations
transition path sampling and molecular dynamics simulations address a similar problem space.
Shared frame: same top-level item type; same primary input modality: light
Relative tradeoffs: appears more independently replicated; looks easier to implement in practice.
Ranked Citations
- 1.