Assessment of an anisotropic coarse-grained model for <i>cis</i>-1,4-polybutadiene: a bottom-up approach

Tanis, Ioannis; Rousseau, Bernard; Soulard, Laurent; Lemarchand, Claire

doi:10.1039/d0sm01572e

Cited by 11 publications

(17 citation statements)

References 49 publications

(82 reference statements)

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“…Different coarse graining have distinct advantages and disadvantages, so choosing proper CG strategy is highly dependent upon specific goal in mind. CG particles are usually isotropic larger and softer particles with pairwise interactions, or simple convex anisotropic object (e.g., soft spheroids) that may be treated analytically [ 24 , 90 , 91 , 92 ]. Such simplifications provide both convenience of computation and certain deficiency for capturing physics of target molecular systems.…”

Section: DC and “Caching” In Traditional Molecular Modelingmentioning

confidence: 99%

“Dividing and Conquering” and “Caching” in Molecular Modeling

Cao

Tian

2021

IJMS

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Molecular modeling is widely utilized in subjects including but not limited to physics, chemistry, biology, materials science and engineering. Impressive progress has been made in development of theories, algorithms and software packages. To divide and conquer, and to cache intermediate results have been long standing principles in development of algorithms. Not surprisingly, most important methodological advancements in more than half century of molecular modeling are various implementations of these two fundamental principles. In the mainstream classical computational molecular science, tremendous efforts have been invested on two lines of algorithm development. The first is coarse graining, which is to represent multiple basic particles in higher resolution modeling as a single larger and softer particle in lower resolution counterpart, with resulting force fields of partial transferability at the expense of some information loss. The second is enhanced sampling, which realizes “dividing and conquering” and/or “caching” in configurational space with focus either on reaction coordinates and collective variables as in metadynamics and related algorithms, or on the transition matrix and state discretization as in Markov state models. For this line of algorithms, spatial resolution is maintained but results are not transferable. Deep learning has been utilized to realize more efficient and accurate ways of “dividing and conquering” and “caching” along these two lines of algorithmic research. We proposed and demonstrated the local free energy landscape approach, a new framework for classical computational molecular science. This framework is based on a third class of algorithm that facilitates molecular modeling through partially transferable in resolution “caching” of distributions for local clusters of molecular degrees of freedom. Differences, connections and potential interactions among these three algorithmic directions are discussed, with the hope to stimulate development of more elegant, efficient and reliable formulations and algorithms for “dividing and conquering” and “caching” in complex molecular systems.

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Section: DC and “Caching” In Traditional Molecular Modelingmentioning

confidence: 99%

“Dividing and Conquering” and “Caching” in Molecular Modeling

Cao

Tian

2021

IJMS

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“…17,[21][22][23] Implementation of MD simulations of anisotropic CG models is facilitated by well-established analytical non-bonded pair potentials, with the most commonly used being the Gay-Berne 24 and RE-squared 25 potentials for ellipsoidal particles. Advantages of using anisotropic CG models have been demonstrated in recent approaches to simulate organic material systems, [26][27][28][29] in which both large-scale conformational properties and small-scale anisotropic molecular arrangements were obtained.…”

Section: Introductionmentioning

confidence: 99%

Systematic Bottom-Up Molecular Coarse-Graining via Force Matching using Anisotropic Particles

Huang

Nguyễn

2022

Preprint

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We derive a systematic and general method for parametrizing coarse-grained molecular models consisting of anisotropic particles from fine-grained (e.g. all-atom) models for condensed-phase molecular dynamics simulations. The method, which we call anisotropic force-matching coarse-graining (AFM-CG), is based on rigorous statistical mechanical principles, enforcing consistency between the coarse-grained and fine-grained phase-space distributions to derive equations for the coarse-grained forces, masses, and moments of inertia in terms of properties of a condensed-phase fine-grained system. We verify the accuracy and efficiency of the method by coarse-graining liquid-state systems of two different anisotropic organic molecules, benzene and perylene, and show that the parametrized coarse-grained models more accurately describe properties of these systems than previous anisotropic coarse-grained models parametrized using other methods that do not account for finite-temperature and many-body effects on the condensed-phase coarse-grained interactions. The AFM-CG method will be useful for developing accurate and efficient dynamical simulation models of condensed-phase systems of molecules consisting of large, rigid, anisotropic fragments, such as nucleic acids, liquid crystals, and organic semiconductors.

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“…Implementation of MD simulations of anisotropic CG models is facili-tated by well-established analytical non-bonded pair potentials, with the most commonly used being the Gay-Berne 24 and RE-squared 25 potentials for ellipsoidal particles. Advantages of using anisotropic CG models have been demonstrated in recent approaches to simulate organic material systems, [26][27][28][29] in which both large-scale conformational properties and small-scale anisotropic molecular arrangements were obtained.…”

Section: Introductionmentioning

confidence: 99%

“…Tripathy, Agarwal, and Kumar 34 used the total instantaneous force between pairs of molecules extracted from condensed-phase all-atom simulations to fit the parameters in an anisotropic CG pair potential for several different polyaromatic hydrocarbons. Tanis et al 28 used a similar force-matching approach, but instead used average pair forces and torques from condensed-phase all-atom simulations as a function of the pair configuration to fit analytical CG pair potentials. Although demonstrated to accurately reproduce properties of the FG all-atom models for specific systems, these methods do not rigorously account for many-body effects on the CG PMF, even though the molecule pairs used in the parametrization were extracted from condensed-phase simulations.…”

Section: Introductionmentioning

confidence: 99%

“…The method, which we have called anisotropic force-matching coarse-graining (AFM-CG), is a generalization to anisotropic CG particles of the multi-scale coarse-graining (MS-CG) method for isotropic CG particles, which uses force matching to relate interactions in the underlying FG model to those in the CG model. Unlike existing anisotropic force-matching methods, 28,34 the AFM-CG method is developed to approximate the FG PMF in a finite-temperature, manybody condensed-phase system without assuming pair interactions between CG particles and is not limited to specific functional forms of the CG potentials, forces, or torques. As proofof-principle, the method is applied to systems of two anisotropic molecules, benzene and perylene.…”

Section: Introductionmentioning

confidence: 99%

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Systematic bottom-up molecular coarse-graining via force and torque matching using anisotropic particles

Huang

Nguyễn

2022

Preprint

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We derive a systematic and general method for parametrizing coarse-grained molecular models consisting of anisotropic particles from fine-grained (e.g. all-atom) models for condensed-phase molecular dynamics simulations. The method, which we call anisotropic force-matching coarse-graining (AFM-CG), is based on rigorous statistical mechanical principles, enforcing consistency between the coarse-grained and fine-grained phase-space distributions to derive equations for the coarse-grained forces, torques, masses, and moments of inertia in terms of properties of a condensed-phase fine-grained system. We verify the accuracy and efficiency of the method by coarse-graining liquid-state systems of two different anisotropic organic molecules, benzene and perylene, and show that the parametrized coarse-grained models more accurately describe properties of these systems than previous anisotropic coarse-grained models parametrized using other methods that do not account for finite-temperature and many-body effects on the condensed-phase coarse-grained interactions. The AFM-CG method will be useful for developing accurate and efficient dynamical simulation models of condensed-phase systems of molecules consisting of large, rigid, anisotropic fragments, such as liquid crystals, organic semiconductors, and nucleic acids.

show abstract

Assessment of an anisotropic coarse-grained model for cis-1,4-polybutadiene: a bottom-up approach

Abstract: The spherical representation usually utilized for the coarse-grained particles of soft matter systems is an assumption and pertinent studies have shown that both structural and dynamical properties can depend on...

Cited by 11 publications

References 49 publications

“Dividing and Conquering” and “Caching” in Molecular Modeling

“Dividing and Conquering” and “Caching” in Molecular Modeling

Systematic Bottom-Up Molecular Coarse-Graining via Force Matching using Anisotropic Particles

Systematic bottom-up molecular coarse-graining via force and torque matching using anisotropic particles

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