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Despite the significant increase in computational power, molecular modeling of protein structure using classical all-atom approaches remains inefficient, at least for most of the protein targets in the focus of biomedical research. Perhaps…

Biomolecules · Quantitative Biology 2016-11-01 Sebastian Kmiecik , Andrzej Kolinski

The most popular and universally predictive protein simulation models employ all-atom molecular dynamics (MD), but they come at extreme computational cost. The development of a universal, computationally efficient coarse-grained (CG) model…

Coarse-graining (CG) accelerates molecular simulations of protein dynamics by simulating sets of atoms as singular beads. Backmapping is the opposite operation of bringing lost atomistic details back from the CG representation. While…

Machine Learning · Computer Science 2023-03-06 Soojung Yang , Rafael Gómez-Bombarelli

Developing accurate and efficient coarse-grained representations of proteins is crucial for understanding their folding, function, and interactions over extended timescales. Our methodology involves simulating proteins with molecular…

Biomolecules · Quantitative Biology 2023-10-11 Carles Navarro , Maciej Majewski , Gianni de Fabritiis

In recent years, a few multiple-resolution modelling strategies have been proposed, in which functionally relevant parts of a biomolecule are described with atomistic resolution, while the remainder of the system is concurrently treated…

Soft Condensed Matter · Physics 2023-01-20 Raffaele Fiorentini , Thomas Tarenzi , Raffaello Potestio

In recent years, simulation methods based on the scaling of atomic potential functions, such as quasi-coarse-grained dynamics and coarse-grained dynamics, have shown promising results for modeling crystalline systems at multiple scales.…

Mesoscale and Nanoscale Physics · Physics 2024-09-11 Dong-Dong Jiang , Jian-Li Shao

A generalized understanding of protein dynamics is an unsolved scientific problem, the solution of which is critical to the interpretation of the structure-function relationships that govern essential biological processes. Here, we approach…

The unfolding of molecular complexes or biomolecules under the influence of external mechanical forces can routinely be simulated with atomistic resolution. To obtain a match of the characteristic time scales with those of experimental…

Soft Condensed Matter · Physics 2024-07-17 Marco Oestereich , Jürgen Gauss , Gregor Diezemann

Large protein assemblies, such as virus capsids, may be coarse-grained as a set of rigid domains linked by generalized (rotational and stretching) harmonic springs. We present a method to obtain the elastic parameters and overdamped…

Biomolecules · Quantitative Biology 2013-05-29 Stephen D. Hicks , C. L. Henley

We developed a multiscale approach (MultiSCAAL) that integrates the potential of mean force (PMF) obtained from all-atomistic molecular dynamics simulations with a knowledge-based energy function for coarse-grained molecular simulations in…

Biological Physics · Physics 2010-05-10 Antonios Samiotakis , Dirar Homouz , Margaret S. Cheung

Molecular dynamics simulations provide theoretical insight into the microscopic behavior of materials in condensed phase and, as a predictive tool, enable computational design of new compounds. However, because of the large temporal and…

Chemical Physics · Physics 2020-06-18 Wujie Wang , Rafael Gómez-Bombarelli

Machine-learned coarse-grained (CG) models have the potential for simulating large molecular complexes beyond what is possible with atomistic molecular dynamics. However, training accurate CG models remains a challenge. A widely used…

Folding and aggregation of proteins, the interaction between proteins and membranes, as well as the adsorption of organic soft matter to inorganic solid substrates belong to the most interesting challenges in understanding structure and…

Soft Condensed Matter · Physics 2007-12-06 Michael Bachmann , Wolfhard Janke

Significant progress in computer hardware and software have enabled molecular dynamics (MD) simulations to model complex biological phenomena such as protein folding. However, enabling MD simulations to access biologically relevant…

Biomolecules · Quantitative Biology 2019-08-02 Heng Ma , Debsindhu Bhowmik , Hyungro Lee , Matteo Turilli , Michael T. Young , Shantenu Jha , Arvind Ramanathan

A mesoscopic coarse-grain model for computationally-efficient simulations of biomembranes is presented. It combines molecular dynamics simulations for the lipids, modeled as elastic chains of beads, with multiparticle collision dynamics for…

Soft Condensed Matter · Physics 2015-06-04 Mu-Jie Huang , Raymond Kapral , Alexander S. Mikhailov , Hsuan-Yi Chen

Due to the time-scale limitations of all-atom simulation of proteins, there has been substantial interest in coarse-grained approaches. Some methods, like "Resolution Exchange," [E. Lyman et al., Phys. Rev. Lett. 96, 028105 (2006)] can…

Biological Physics · Physics 2007-05-23 F. Marty Ytreberg , Svetlana Kh. Aroutiounian , Daniel M. Zuckerman

Simulating large-scale protein dynamics using traditional all-atom molecular dynamics (MD) remains computationally prohibitive. We present a unified, universal framework for coarse-grained molecular dynamics (CG-MD) that achieves…

Atomic Physics · Physics 2026-04-16 Jinzhen Zhu

We introduce a variational approximation to the microscopic dynamics of rare conformational transitions of macromolecules. Within this framework it is possible to simulate on a small computer cluster reactions as complex as protein folding,…

Soft Condensed Matter · Physics 2015-02-19 S. a Beccara , L. Fant , P. Faccioli

-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

Coarse-grained (CG) molecular dynamics enables simulations of atomic systems such as biomolecules at timescales inaccessible to all-atom (AA) methods, but existing CG neural potentials trained via force matching capture only the gradient of…

Machine Learning · Computer Science 2026-05-14 Sanya Murdeshwar , Sanjit Shashi , Kevin Bachelor , William Noid , Ashwin Lokapally , Razvan Marinescu
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