Markovian Weighted Ensemble Milestoning (M-WEM): Long-time Kinetics from Short Trajectories

D, Ray; Se, Stone; Andricioaei, Ioan

doi:10.1101/2021.06.26.450057

Cited by 3 publications

(1 citation statement)

References 119 publications

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“…OneOPES Light OneOPES A more arduous test is the ligand-binding benchmark Trypsin-Benzamidine. While this system has been routinely used for years as a benchmark for ligand-binding methods 61,[63][64][65][66][67][68][69][70][71][72][73] , it is far from trivial and still offers a significant challenge. High-resolution crystallographic experiments have recently demonstrated that individual water molecules play a crucial role in the system's binding/unbinding process 74 , so that the introduction of specialised water-focused CVs proved decisive in bringing simulations to convergence in our recent work 56 .…”

Section: Trypsin-benzamidinementioning

confidence: 99%

OneOPES, a combined enhanced sampling method to rule them all

Rizzi

Aureli

Ansari

et al. 2023

Preprint

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Enhanced sampling techniques have revolutionised molecular dynamics (MD) simulations, enabling the study of rare events and the calculation of free energy differences in complex systems. One of the main families of enhanced sampling techniques uses physical degrees of freedom called collective variables (CVs) to accelerate a system's dynamics and recover the original system's statistics. However, encoding all the relevant degrees of freedom in a limited number of CVs is challenging, particularly in large biophysical systems. Another category of techniques, such as parallel tempering, simulates multiple replicas of the system in parallel, without requiring CVs. However, these methods may explore less relevant high-energy portions of the phase space and become computationally expensive for large systems. To overcome the limitations of both approaches, we propose a replica exchange method called OneOPES that combines the power of multi-replica simulations and CV-based enhanced sampling. This method efficiently accelerates the crossing of both enthalpic and entropic barriers without the need for optimal CVs definition, parameters fine tuning nor the use of a large number of replicas, as demonstrated by its successful applications to protein-ligand binding and protein folding benchmark systems. Our approach shows promise as a new direction in the development of enhanced sampling techniques for molecular dynamics simulations, providing an efficient and robust framework for the study of complex and unexplored problems.

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Section: Trypsin-benzamidinementioning

confidence: 99%

OneOPES, a combined enhanced sampling method to rule them all

Rizzi

Aureli

Ansari

et al. 2023

Preprint

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Gaussian-Accelerated Molecular Dynamics with the Weighted Ensemble Method: A Hybrid Method Improves Thermodynamic and Kinetic Sampling

Ahn

Ojha

Amaro

et al. 2021

J. Chem. Theory Comput.

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Gaussian accelerated molecular dynamics (GaMD) is a well-established enhanced sampling method for molecular dynamics (MD) simulations that effectively samples the potential energy landscape of the system by adding a boost potential, which smoothens the surface and lowers energy barriers between states. Although equilibrium properties can be recovered exactly in principle, GaMD is unable to give time-dependent properties such as kinetics directly. On the other hand, weighted ensemble (WE) method can efficiently sample transitions between states with its many weighted trajectories, which directly yield rates and pathways. However, performance of the WE method (i.e., convergence and efficiency) depends heavily on its initial conditions or initial sampling of the potential energy landscape. Hence, we have developed a hybrid method that combines the two methods, wherein GaMD is first used to sample the potential energy landscape of the system, and WE method is subsequently used to further sample the 1 potential energy landscape and kinetic properties of interest. We show that the hybrid method can sample both thermodynamic and kinetic properties more accurately and quickly compared to using either method alone.

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WESTPA 2.0: High-performance upgrades for weighted ensemble simulations and analysis of longer-timescale applications

Russo

Zhang²,

Leung

et al. 2021

Preprint

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The weighted ensemble (WE) family of methods is one of several statistical-mechanics based path sampling strategies that can provide estimates of key observables (rate constants, pathways) using a fraction of the time required by direct simulation methods such as molecular dynamics or discrete-state stochastic algorithms. WE methods oversee numerous parallel trajectories using intermittent overhead operations at fixed time intervals, enabling facile interoperability with any dynamics engine. Here, we report on major upgrades to the WESTPA software package, an open-source, high-performance framework that implements both basic and recently developed WE methods. These upgrades offer substantial improvements over traditional WE. Key features of the new WESTPA 2.0 software enhance efficiency and ease of use: an adaptive binning scheme for more efficient surmounting of large free energy barriers, streamlined handling of large simulation datasets, exponentially improved analysis of kinetics, and developer-friendly tools for creating new WE methods, including a Python API and resampler module for implementing both binned and 'binless' WE strategies.

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Markovian Weighted Ensemble Milestoning (M-WEM): Long-time Kinetics from Short Trajectories

Cited by 3 publications

References 119 publications

OneOPES, a combined enhanced sampling method to rule them all

OneOPES, a combined enhanced sampling method to rule them all

Gaussian-Accelerated Molecular Dynamics with the Weighted Ensemble Method: A Hybrid Method Improves Thermodynamic and Kinetic Sampling

WESTPA 2.0: High-performance upgrades for weighted ensemble simulations and analysis of longer-timescale applications

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