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Markov processes serve as foundational models in many scientific disciplines, such as molecular dynamics, and their simulation forms a common basis for analysis. While simulations produce useful trajectories, obtaining macroscopic…

Chemical Physics · Physics 2024-06-11 Alexander Sikorski , Robert Julian Rabben , Surahit Chewle , Marcus Weber

The internal dynamics of strongly interacting systems and that of biomolecules such as proteins display several important analogies, despite the huge difference in their characteristic energy and length scales. For example, in all such…

Biological Physics · Physics 2015-05-30 Pietro Faccioli

We present a novel machine learning approach to understanding conformation dynamics of biomolecules. The approach combines kernel-based techniques that are popular in the machine learning community with transfer operator theory for…

Computational Physics · Physics 2019-01-24 Stefan Klus , Andreas Bittracher , Ingmar Schuster , Christof Schütte

All-atom and coarse-grained molecular dynamics are two widely used computational tools to study the conformational states of proteins. Yet, these two simulation methods suffer from the fact that without access to supercomputing resources,…

Quantitative Methods · Quantitative Biology 2022-06-13 Gregory Schwing , Luigi L. Palese , Ariel Fernández , Loren Schwiebert , Domenico L. Gatti

Molecular dynamics is based on solving Newton's equations for many-particle systems that evolve along complex, highly fluctuating trajectories. The orbital instability and short-time complexity of Newtonian orbits is in sharp contrast to…

Chemical Physics · Physics 2017-09-19 Yuriy V. Sereda , Andrew Abi Mansour , Peter J. Ortoleva

-Molecular simulations allow the study of properties and interactions of molecular systems. This article presents an improved version of the Adaptive Resolution Scheme that links two systems having atomistic (also called fine-grained) and…

Computational Engineering, Finance, and Science · Computer Science 2017-08-01 Iuliana Marin , Virgil Tudose , Anton Hadar , Nicolae Goga , Andrei Doncescu

Living systems exhibit complex yet organized behavior on multiple spatiotemporal scales. To investigate the nature of multiscale coordination in living systems, one needs a meaningful and systematic way to quantify the complex dynamics, a…

Adaptation and Self-Organizing Systems · Physics 2020-03-11 Mengsen Zhang , William D. Kalies , J. A. Scott Kelso , Emmanuelle Tognoli

The ISOKANN (Invariant Subspaces of Koopman Operators Learned by Artificial Neural Networks) framework provides a data-driven route to extract collective variables (CVs) and effective dynamics from complex molecular systems. In this work,…

Dynamical Systems · Mathematics 2026-04-08 Alexander Sikorski , Luca Donati , Marcus Weber , Christof Schütte

Classical topological concepts are applied to understand high performance computing simulations of molecules writhing in three dimensional space. These simulations produce peta-bytes of floating point data, to describe 3 dimensional changes…

Geometric Topology · Mathematics 2013-04-23 J. Li , T. J. Peters , K. E. Jordan

Interpretable reaction coordinates are essential for understanding rare conformational transitions in molecular dynamics. The Atomistic Mechanism Of Rare Events in Molecular Dynamics (AMORE-MD) framework enhances interpretability of…

Chemical Physics · Physics 2026-02-27 Jakob J. Kresse , Alexander Sikorski , Marcus Weber

Molecular dynamics simulations of folding in an off-lattice protein model reveal a nucleation scenario, in which a few well-defined contacts are formed with high probability in the transition state ensemble of conformations. Their…

Statistical Mechanics · Physics 2009-09-25 Nikolay V. Dokholyan , Sergey V. Buldyrev , H. Eugene Stanley , Eugene I. Shakhnovich

This contribution introduces a neural-network-based approach to discover meaningful transition pathways underlying complex biomolecular transformations in coherence with the committor function. The proposed path-committor-consistent…

The concept of molecular mechanics force field has been widely accepted nowadays for studying various processes in biomolecular systems. In this paper, we suggest a modification for the standard CHARMM force field that permits simulations…

We introduce MOSCITO (MOlecular Dynamics Subspace Clustering with Temporal Observance), a subspace clustering for molecular dynamics data. MOSCITO groups those timesteps of a molecular dynamics trajectory together into clusters in which the…

Machine Learning · Computer Science 2025-01-03 Anna Beer , Martin Heinrigs , Claudia Plant , Ira Assent

Finding optimal reaction coordinates and predicting accurate kinetic rates for activated processes are two of the foremost challenges of molecular simulations. We introduce an algorithm that tackles the two problems at once: starting from a…

Statistical Mechanics · Physics 2023-10-30 Line Mouaffac , Karen Palacio-Rodriguez , Fabio Pietrucci

Conformational transitions are ubiquitous in biomolecular systems, have significant functional roles and are subject to evolutionary pressures. Here we provide a first theoretical framework for topological transition, i.e. conformational…

Disordered Systems and Neural Networks · Physics 2015-09-02 Alireza Mashaghi , Abolfazl Ramezanpour

The biomolecules in and around a living cell -- proteins, nucleic acids, lipids, carbohydrates -- continuously sample myriad conformational states that are thermally accessible at physiological temperatures. Simultaneously, a given…

Biomolecules · Quantitative Biology 2014-07-15 Cameron Mura , Charles E. McAnany

While ubiquitous, energy redistribution remains a poorly understood facet of the nonequilibrium thermodynamics of biomolecules. At the molecular level, finite-size effects, pronounced nonlinearities, and ballistic processes produce behavior…

Biological Physics · Physics 2019-11-15 Justin E. Elenewski , Kirill A. Velizhanin , Michael Zwolak

Extensively exploring protein conformational landscapes remains a major challenge in computational biology due to the high computational cost involved in dynamic physics-based simulations. In this work, we propose a novel pipeline, MoDyGAN,…

Machine Learning · Computer Science 2025-07-21 Jingbo Liang , Bruna Jacobson

A major challenge in nonadiabatic molecular dynamics is to automatically and objectively identify the key reaction coordinates that drive molecules toward distinct excited-state decay channels. Traditional manual analyses are inefficient…

Chemical Physics · Physics 2025-11-18 Hangxu Liu , Yifei Zhu , Zhenggang Lan
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