WESTPA: An Interoperable, Highly Scalable Software Package for Weighted Ensemble Simulation and Analysis

Zwier, Matthew C.; Adelman, Joshua L.; Kaus, Joseph W.; Pratt, Adam J.; Wong, Kim F.; Rego, Nicholas B.; Suárez, Ernesto; Lettieri, Steven; Wang, David W.; Grabe, Michael; Zuckerman, Daniel M.; Chong, Lillian T.

doi:10.1021/ct5010615

Cited by 151 publications

(183 citation statements)

References 50 publications

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“…18 In this strategy, a large number of simulations, or “walkers”, are started in parallel from the initial, unbound state and evaluated for replication or combination every τ time units (according to the standard WE algorithm 13 ) to maintain the desired number of walkers per bin along a progress coordinate toward the target bound state. In our simulations, the initial and target states were the unbound and bound states, respectively, and a τ value of 50 ps was used.…”

Section: Methodsmentioning

confidence: 99%

Efficient Atomistic Simulation of Pathways and Calculation of Rate Constants for a Protein–Peptide Binding Process: Application to the MDM2 Protein and an Intrinsically Disordered p53 Peptide

Zwier

Pratt

Adelman

et al. 2016

J. Phys. Chem. Lett.

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119

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The characterization of protein binding processes — with all of the key conformational changes — has been a grand challenge in the field of biophysics. Here, we have used the weighted ensemble path sampling strategy to orchestrate molecular dynamics simulations, yielding atomistic views of protein–peptide binding pathways involving the MDM2 oncoprotein and an intrinsically disordered p53 peptide. A total of 182 independent, continuous binding pathways were generated, yielding a kon that is in good agreement with experiment. These pathways were generated in 15 days using 3500 cores of a supercomputer, substantially faster than would be possible with “brute force” simulations. Many of these pathways involve the anchoring of p53 residue F19 into the MDM2 binding cleft when forming the metastable encounter complex, indicating that F19 may be a kinetically important residue. Our study demonstrates that it is now practical to generate pathways and calculate rate constants for protein binding processes using atomistic simulation on typical computing resources.

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Section: Methodsmentioning

confidence: 99%

Efficient Atomistic Simulation of Pathways and Calculation of Rate Constants for a Protein–Peptide Binding Process: Application to the MDM2 Protein and an Intrinsically Disordered p53 Peptide

Zwier

Pratt

Adelman

et al. 2016

J. Phys. Chem. Lett.

Self Cite

119

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“…63 Trajectory segments were propagated using simulation parameters identical to those used in the brute force calculations. The cartesian coordinates of a single Na + or Cl − ion define a set of three spatial progress coordinates.…”

Section: Theory and Computational Methodsmentioning

confidence: 99%

Simulating Current–Voltage Relationships for a Narrow Ion Channel Using the Weighted Ensemble Method

Adelman

Grabe

2015

J. Chem. Theory Comput.

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Ion channels are responsible for a myriad of fundamental biological processes via their role in controlling the flow of ions through water-filled membrane-spanning pores in response to environmental cues. Molecular simulation has played an important role in elucidating the mechanism of ion conduction, but connecting atomistically detailed structural models of the protein to electrophysiological measurements remains a broad challenge due to the computational cost of reaching the necessary time scales. Here, we introduce an enhanced sampling method for simulating the conduction properties of narrow ion channels using the weighted ensemble (WE) sampling approach. We demonstrate the application of this method to calculate the current-voltage relationship as well as the non-equilibrium ion distribution at steady-state of a simple model ion channel. By direct comparisons with long brute force simulations, we show that the WE simulations rigorously reproduce the correct long-timescale kinetics of the system and are capable of determining these quantities using significantly less aggregate simulation time under conditions where permeation events are rare.

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“…This weighted ensemble (WE)[77] approach utilizes an on-the-fly protocol of removing or dividing simulation replicas[78] to achieve a convergence probability distribution of states. It scales very well with a large number of CPUs to sample a ten thousand of trajectories per iteration[79]. Another advantage of this method is that it works with both equilibrium and non-equilibrium steady states, in which one might sample conformational states in equilibrium fashion while sampling of ion permeation in a steady state.…”

Section: Thermodynamics and Statistics Of Drug Binding From MD Simmentioning

confidence: 99%

Computational membrane biophysics: From ion channel interactions with drugs to cellular function

Miranda

Ngo

Perissinotti

et al. 2017

Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics

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The rapid development of experimental and computational techniques has changed fundamentally our understanding of cellular-membrane transport. The advent of powerful computers and refined force-fields for proteins, ions, and lipids has expanded the applicability of Molecular Dynamics (MD) simulations. A myriad of cellular responses is modulated through the binding of endogenous and exogenous ligands (e.g. neurotransmitters and drugs, respectively) to ion channels. Deciphering the thermodynamics and kinetics of the ligand binding processes to these membrane proteins is at the heart of modern drug development. The ever-increasing computational power has already provided insightful data on the thermodynamics and kinetics of drug-target interactions, free energies of solvation, and partitioning into lipid bilayers for drugs. This review aims to provide a brief summary about modeling approaches to map out crucial binding pathways with intermediate conformations and free-energy surfaces for drug-ion channel binding mechanisms that are responsible for multiple effects on cellular functions. We will discuss post-processing analysis of simulation-generated data, which are then transformed to kinetic models to better understand the molecular underpinning of the experimental observables under the influence of drugs or mutations in ion channels. This review highlights crucial mathematical frameworks and perspectives on bridging different well-established computational techniques to connect the dynamics and timescales from all-atom MD and free energy simulations of ion channels to the physiology of action potentials in cellular models.

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WESTPA: An Interoperable, Highly Scalable Software Package for Weighted Ensemble Simulation and Analysis

Cited by 151 publications

References 50 publications

Efficient Atomistic Simulation of Pathways and Calculation of Rate Constants for a Protein–Peptide Binding Process: Application to the MDM2 Protein and an Intrinsically Disordered p53 Peptide

Efficient Atomistic Simulation of Pathways and Calculation of Rate Constants for a Protein–Peptide Binding Process: Application to the MDM2 Protein and an Intrinsically Disordered p53 Peptide

Simulating Current–Voltage Relationships for a Narrow Ion Channel Using the Weighted Ensemble Method

Computational membrane biophysics: From ion channel interactions with drugs to cellular function

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