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We present a method to sample reactive pathways via biased molecular dynamics simulations in trajectory space. We show that the use of enhanced sampling techniques enables unconstrained exploration of multiple reaction routes. Time…

计算物理 · 物理学 2020-07-15 Davide Mandelli , Barak Hirshberg , Michele Parrinello

Due to the time scale problem, rare events are not accessible by straight forward molecular dynamics. The presence of multiple reaction channels complicates the problem even further. The feasibility of the standard free energy based methods…

统计力学 · 物理学 2009-11-13 Titus S. van Erp

Enhanced sampling algorithms have emerged as powerful methods to extend the utility of molecular dynamics simulations and allow the sampling of larger portions of the configuration space of complex systems in a given amount of simulation…

统计力学 · 物理学 2022-12-19 Jérôme Hénin , Tony Lelièvre , Michael R. Shirts , Omar Valsson , Lucie Delemotte

Molecular dynamics simulations hold great promise for providing insight into the microscopic behavior of complex molecular systems. However, their effectiveness is often constrained by long timescales associated with rare events. Enhanced…

计算物理 · 物理学 2026-03-03 Kai Zhu , Enrico Trizio , Jintu Zhang , Renling Hu , Linlong Jiang , Tingjun Hou , Luigi Bonati

Sampled structure sequences obtained, for instance, from real-time reactivity explorations or first-principles molecular dynamics simulations contain valuable information about chemical reactivity. Eventually, such sequences allow for the…

化学物理 · 物理学 2018-04-25 Michael A. Heuer , Alain C. Vaucher , Moritz P. Haag , Markus Reiher

Atomistic modelling of phase transitions, chemical reactions, or other rare events that involve overcoming high free energy barriers usually entails prohibitively long simulation times. Introducing a bias potential as a function of an…

计算物理 · 物理学 2019-11-06 Federico Giberti , Bingqing Cheng , Gareth Aneurin Tribello , Michele Ceriotti

I give an overview of rare event simulation techniques to generate dynamical pathways across high free energy barriers. The methods on which I will concentrate are the reactive flux approach, transition path sampling, (replica-exchange)…

统计力学 · 物理学 2015-03-17 Titus S. van Erp

We review a selection of methods for performing enhanced sampling in molecular dynamics simulations. We consider methods based on collective variable biasing and on tempering, and offer both historical and contemporary perspectives. In…

统计力学 · 物理学 2014-01-03 Cameron Abrams , Giovanni Bussi

RNA function is intimately related to its structural dynamics. Molecular dynamics simulations are useful for exploring biomolecular flexibility but are severely limited by the accessible timescale. Enhanced sampling methods allow this…

生物大分子 · 定量生物学 2018-02-06 Vojtěch Mlýnský , Giovanni Bussi

Molecular Dynamics (MD) simulations are fundamental computational tools for the study of proteins and their free energy landscapes. However, sampling protein conformational changes through MD simulations is challenging due to the relatively…

生物大分子 · 定量生物学 2023-07-20 Diego E. Kleiman , Hassan Nadeem , Diwakar Shukla

Molecular dynamics simulations are widely used across chemistry, physics, and biology, providing quantitative insight into complex processes with atomic detail. However, their limited timescale of a few microseconds is a significant…

化学物理 · 物理学 2025-04-10 Ofir Blumer , Barak Hirshberg

Molecular dynamics simulations have become essential in many areas of atomistic modelling from drug discovery to materials science. They provide critical atomic-level insights into key dynamical events experiments cannot easily capture.…

生物物理 · 物理学 2024-06-14 Tiejun Wei , Balint Dudas , Edina Rosta

This review describes recent advances by the authors and others on the topic of incorporating experimental data into molecular simulations through maximum entropy methods. Methods which incorporate experimental data improve accuracy in…

化学物理 · 物理学 2019-05-15 Dilnoza B. Amirkulova , Andrew D. White

The search for pathways that optimize the formation of a particular target molecule in a reaction network is a key problem in many settings, including reactor systems. Chemical reaction networks are mathematically well represented as…

分子网络 · 定量生物学 2025-06-17 Adittya Pal , Rolf Fagerberg , Jakob Lykke Andersen , Christoph Flamm , Peter Dittrich , Daniel Merkle

We present a method for enhanced sampling of molecular dynamics simulations using stochastic resetting. Various phenomena, ranging from crystal nucleation to protein folding, occur on timescales that are unreachable in standard simulations.…

化学物理 · 物理学 2023-02-09 Ofir Blumer , Shlomi Reuveni , Barak Hirshberg

We present a procedure for enhanced sampling of molecular dynamics simulations through informed stochastic resetting. Many phenomena, such as protein folding and crystal nucleation, occur over time scales that are inaccessible in standard…

Disentangling the mechanistic details of a chemical reaction pathway is a hard problem that often requires a considerable amount of chemical intuition and a component of luck. Experiments struggle in observing short-life metastable…

化学物理 · 物理学 2019-08-01 Valerio Rizzi , Dan Mendels , Emilia Sicilia , Michele Parrinello

Processes involving multi-input multi-step reaction cascades are used in developing novel biosensing, biocomputing, and decision making systems. In various applications different changes in responses of the constituent processing steps…

分子网络 · 定量生物学 2016-08-16 Sergii Domanskyi , Vladimir Privman

Molecular dynamics (MD) simulations are useful in obtaining thermodynamic and kinetic properties of bio-molecules but are limited by the timescale barrier, i.e., we may be unable to efficiently obtain properties because we need to run…

化学物理 · 物理学 2017-08-23 Surl-Hee Ahn , Jay W. Grate , Eric F. Darve

Metadynamics is a powerful method to accelerate molecular dynamics simulations, but its efficiency critically depends on the identification of collective variables that capture the slow modes of the process. Unfortunately, collective…

化学物理 · 物理学 2023-07-17 Ofir Blumer , Shlomi Reuveni , Barak Hirshberg
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