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We discuss the reliability of integral-equation methods based on several commonly used closure relations in determining the phase diagram of coarse-grained models of soft-matter systems characterized by mutually interacting soft and…

软凝聚态物质 · 物理学 2015-10-28 Roberto Menichetti , Andrea Pelissetto , Giuseppe D'Adamo , Carlo Pierleoni

The determination of potentials of mean force for solute insertion in a membrane by means of all-atom molecular dynamics simulations is often hampered by sampling issues. A multiscale approach to conformational sampling was recently…

化学物理 · 物理学 2017-10-09 Roberto Menichetti , Kurt Kremer , Tristan Bereau

High resolution low angle x-ray data are reported for the gel phase of DPPC lipid bilayers, extending the previous q range of 1.0 {\AA}-1 to 1.3 {\AA}-1, and employing a new technique to obtain more accurate intensities and form factors…

生物物理 · 物理学 2019-03-27 John F Nagle , Pierre Cognet , Fernando G. Dupuy , Stephanie Tristram-Nagle

In recent years, molecular dynamics (MD) simulations have emerged as a pivotal tool for understanding the structure, dynamics, and phase behavior in charged soft matter systems. To explore phenomena across greater length and time scales in…

计算物理 · 物理学 2024-07-18 Benjamin Bobin Ye , Shensheng Chen , Zhen-Gang Wang

Lipid membranes have complex compositions and modeling the thermodynamic properties of multi-component lipid systems remains a remote goal. In this work we attempt to describe the thermodynamics of binary lipid mixtures by mapping…

软凝聚态物质 · 物理学 2024-09-04 L. Berezovska , R. Kociurzynski , F. Thalmann

We propose a new multi-scale molecular dynamics simulation method which can achieve high accuracy and high sampling efficiency simultaneously without aforehand knowledge of the coarse grained (CG) potential and test it for a biomolecular…

生物物理 · 物理学 2009-08-05 Wenfei Li , Shoji Takada

One essential goal of constructing coarse-grained molecular dynamics (CGMD) models is to accurately predict non-equilibrium processes beyond the atomistic scale. While a CG model can be constructed by projecting the full dynamics onto a set…

计算物理 · 物理学 2024-09-19 Liyao Lyu , Huan Lei

The structure of polyelectrolytes is highly sensitive to small changes in the interactions between its monomers. In particular, interactions mediated by counterions play a significant role, and are affected by both specific molecular…

软凝聚态物质 · 物理学 2020-02-03 Pauline Bacle , Marie Jardat , Virginie Marry , Guillaume Mériguet , Guillaume Batôt , Vincent Dahirel

Coarse-graining (CG) enables molecular dynamics (MD) simulations of larger systems and longer timescales that are otherwise infeasible with atomistic models. Machine learning potentials (MLPs), with their capacity to capture many-body…

化学物理 · 物理学 2025-12-01 Weilong Chen , Franz Görlich , Paul Fuchs , Julija Zavadlav

We summarize and compare recent Molecular Dynamics simulations on the interactions of dipalmitoylphosphatidylcholine (DPPC) bilayers in the liquid crystalline phase with a number of small molecules including trehalose, a disaccharide of…

We investigate with computer simulations the critical radius of pores in a lipid bilayer membrane. Ilton et al. (2016) recently showed that nucleated pores in a homopolymer film can increase or decrease in size, depending on whether they…

软凝聚态物质 · 物理学 2017-10-26 Clark Bowman , Mark Chaplain , Anastasios Matzavinos

Coarse-grained (CG) modeling simplifies molecular systems by mapping groups of atoms into representative units. However, traditional CG approaches rely on fixed mapping rules, which limit their ability to handle diverse chemical systems and…

计算物理 · 物理学 2025-09-26 Zhixuan Zhong , Linbo Ma , Jian Jiang

In this paper, we present a coarse-grained model of DNA based on the soft ellipsoid contact potential (ECP) to evaluate the base pairing interaction properly. We extend the ellipsoid contact like potential model (ECP), suitably modified and…

软凝聚态物质 · 物理学 2026-02-10 Abhirup Das , Jayashree Saha

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…

生物大分子 · 定量生物学 2016-11-01 Sebastian Kmiecik , Andrzej Kolinski

Brute-force simulations for dynamics on very large networks are quite expensive. While phenomenological treatments may capture some macroscopic properties, they often ignore important microscopic details. Fortunately, one may be only…

物理与社会 · 物理学 2016-05-17 Chuansheng Shen , Hanshuang Chen , Zhonghuai Hou , Jürgen Kurths

We present a simple coarse-grained bead-and-spring model for lipid bilayers. The system has been developed to reproduce the main (gel-liquid) transition of biological membranes on intermediate length scales of a couple of nanometres and is…

软凝聚态物质 · 物理学 2007-05-23 Olaf Lenz , Friederike Schmid

We use a coarse grained molecular model of supported lipid bilayers to study the formation of adhesion domains. We find that this process is a first order phase transition, triggered by a combination of pairwise short range attractive…

软凝聚态物质 · 物理学 2015-06-22 Nadiv Dharan , Oded Farago

In a recent paper, J. Chem. Phys. 162, 214101 (2025), a novel approach for the rigidification of a molecular cluster was proposed, in which starting with an all-atom (AA) potential, a coarse-grained (CG) potential for the associated cluster…

化学物理 · 物理学 2025-09-08 João V. M. Pimentel , Vladimir A. Mandelshtam

We propose a data-driven, coarse-graining formulation in the context of equilibrium statistical mechanics. In contrast to existing techniques which are based on a fine-to-coarse map, we adopt the opposite strategy by prescribing a…

机器学习 · 统计学 2017-02-01 Markus Schöberl , Nicholas Zabaras , Phaedon-Stelios Koutsourelakis

Coarse-grained (CG) modeling has gained significant attention in recent years due to its wide applicability in enhancing the spatiotemporal scales of molecular simulations. While CG simulations, often performed with Hamiltonian mechanics,…

化学物理 · 物理学 2025-04-01 Jaehyeok Jin , Gregory A. Voth