Enhanced sampling methods for molecular dynamics simulations

J Hénin, T Lelièvre, MR Shirts, O Valsson… - arXiv preprint arXiv …, 2022 - arxiv.org
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 …

Driving and characterizing nucleation of urea and glycine polymorphs in water

Z Zou, ER Beyerle, ST Tsai… - Proceedings of the …, 2023 - National Acad Sciences
Crystal nucleation is relevant across the domains of fundamental and applied sciences.
However, in many cases, its mechanism remains unclear due to a lack of temporal or spatial …

[HTML][HTML] State predictive information bottleneck

D Wang, P Tiwary - The Journal of Chemical Physics, 2021 - pubs.aip.org
The ability to make sense of the massive amounts of high-dimensional data generated from
molecular dynamics simulations is heavily dependent on the knowledge of a low …

A maximum caliber approach for continuum path ensembles

PG Bolhuis, ZF Brotzakis, M Vendruscolo - The European Physical …, 2021 - Springer
The maximum caliber approach implements the maximum entropy principle for trajectories
by maximizing a path entropy under external constraints. The maximum caliber approach …

Transition path sampling as Markov chain Monte Carlo of trajectories: Recent algorithms, software, applications, and future outlook

PG Bolhuis, DWH Swenson - Advanced Theory and …, 2021 - Wiley Online Library
The development of enhanced sampling methods to investigate rare but important events
has always been a focal point in the molecular simulation field. Such methods often rely on …

Data-driven path collective variables

A France-Lanord, H Vroylandt, M Salanne… - Journal of Chemical …, 2024 - ACS Publications
Identifying optimal collective variables to model transformations using atomic-scale
simulations is a long-standing challenge. We propose a new method for the generation …

Discovering collective variables of molecular transitions via genetic algorithms and neural networks

F Hooft, A Pérez de Alba Ortíz… - Journal of chemical theory …, 2021 - ACS Publications
With the continual improvement of computing hardware and algorithms, simulations have
become a powerful tool for understanding all sorts of (bio) molecular processes. To handle …

[HTML][HTML] Classical molecular dynamics

CL Brooks, DA Case, S Plimpton, B Roux… - The Journal of …, 2021 - pubs.aip.org
This issue of JCP highlights both developments in and applications of classical molecular
simulation in 67 articles. A recent issue of JCP focused on electronic structure software …

An exploration of machine learning models for the determination of reaction coordinates associated with conformational transitions

N Naleem, CRA Abreu, K Warmuz, M Tong… - The Journal of …, 2023 - pubs.aip.org
Determining collective variables (CVs) for conformational transitions is crucial to
understanding their dynamics and targeting them in enhanced sampling simulations. Often …

[HTML][HTML] Explaining reaction coordinates of alanine dipeptide isomerization obtained from deep neural networks using Explainable Artificial Intelligence (XAI)

T Kikutsuji, Y Mori, K Okazaki, T Mori, K Kim… - The journal of …, 2022 - pubs.aip.org
A method for obtaining appropriate reaction coordinates is required to identify transition
states distinguishing the product and reactant in complex molecular systems. Recently …