Magic v.3: An integrated software package for systematic structure-based coarse-graining

Mirzoev, Alexander; Nordenskiöld, Lars; Lyubartsev, Alexander P.

doi:10.1016/j.cpc.2018.11.018

Cited by 25 publications

(33 citation statements)

References 56 publications

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“…In both the CG and SCG DNA models, all effective interaction potentials are obtained in a systematic and rigorous way using the IMC method (49,50). The potentials are constructed to reproduce selected average structural properties of the fine-grained system such as radial distributions functions (RDF) between non-bonded CG sites and bond length and angle distributions for bonded sites.…”

Section: Methodsmentioning

confidence: 99%

“…The CG model is simple enough yet captures the structure form of double helix DNA and rigorously treats the electrostatic interactions. The systematic coarse-graining follows the Inverse Monte Carlo (IMC) approach to extract solvent mediated effective CG potentials for all interactions in the system (49,50) from structural properties of the underlying system. The model is validated in CG simulations of DNA persistence length as a function of monovalent salt demonstrating outstanding performance.…”

Section: Introductionmentioning

confidence: 99%

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A multiscale analysis of DNA phase separation: from atomistic to mesoscale level

Sun

Mirzoev

Minhas

et al. 2019

Nucleic Acids Research

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DNA condensation and phase separation is of utmost importance for DNA packing in vivo with important applications in medicine, biotechnology and polymer physics. The presence of hexagonally ordered DNA is observed in virus capsids, sperm heads and in dinoflagellates. Rigorous modelling of this process in all-atom MD simulations is presently difficult to achieve due to size and time scale limitations. We used a hierarchical approach for systematic multiscale coarse-grained (CG) simulations of DNA phase separation induced by the three-valent cobalt(III)-hexammine (CoHex 3+ ). Solvent-mediated effective potentials for a CG model of DNA were extracted from all-atom MD simulations. Simulations of several hundred 100-bp-long CG DNA oligonucleotides in the presence of explicit CoHex 3+ ions demonstrated aggregation to a liquid crystalline hexagonally ordered phase. Following further coarse-graining and extraction of effective potentials, we conducted modelling at mesoscale level. In agreement with electron microscopy observations, simulations of an 10.2-kb-long DNA molecule showed phase separation to either a toroid or a fibre with distinct hexagonal DNA packing. The mechanism of toroid formation is analysed in detail. The approach used here is based only on the underlying all-atom force field and uses no adjustable parameters and may be generalised to modelling chromatin up to chromosome size.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A multiscale analysis of DNA phase separation: from atomistic to mesoscale level

Sun

Mirzoev

Minhas

et al. 2019

Nucleic Acids Research

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“…Recall that G is discretized RDF and U is discretized potential energy, as formulated in IMC and implemented in the MagiC software (Mirzoev et al, 2019 ). More generally, G can be any set of observables, and U γ can represent an arbitrary parameter of potential energy.…”

Section: Bottom-up Coarse-grainingmentioning

confidence: 99%

Bottom-Up Coarse-Grained Modeling of DNA

Sun

Minhas

Korolev

et al. 2021

Front. Mol. Biosci.

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Recent advances in methodology enable effective coarse-grained modeling of deoxyribonucleic acid (DNA) based on underlying atomistic force field simulations. The so-called bottom-up coarse-graining practice separates fast and slow dynamic processes in molecular systems by averaging out fast degrees of freedom represented by the underlying fine-grained model. The resulting effective potential of interaction includes the contribution from fast degrees of freedom effectively in the form of potential of mean force. The pair-wise additive potential is usually adopted to construct the coarse-grained Hamiltonian for its efficiency in a computer simulation. In this review, we present a few well-developed bottom-up coarse-graining methods, discussing their application in modeling DNA properties such as DNA flexibility (persistence length), conformation, “melting,” and DNA condensation.

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“…For this reason, in this work, we decided to rely on the widely used MARTINI force field for what pertains to the nonbonded interactions, and we focus exclusively on easing and automatizing the parametrization of the bonded interactions in the context of combined top-down and bottom-up CG modeling approaches. Several software, such as MSCGFM, 90 VOTCA, 26 BOCS, 32 Magic, 91 and PyCGTOOL, 92 implement approaches that can be used for tuning bonded interactions, while the nonbonded ones remain constant, notably direct Boltzmann inversion (DBI), 93 , 94 IBI, 52 , 53 IMC, 51 and the g-YBG equation. 58 The g-YBG equation and DBI are direct approaches, which do not require to run simulations iteratively for refining parameters.…”

Section: Introductionmentioning

confidence: 99%

Swarm-CG: Automatic Parametrization of Bonded Terms in MARTINI-Based Coarse-Grained Models of Simple to Complex MoleculesviaFuzzy Self-Tuning Particle Swarm Optimization

et al. 2020

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We present Swarm-CG , a versatile software for the automatic iterative parametrization of bonded parameters in coarse-grained (CG) models, ideal in combination with popular CG force fields such as MARTINI. By coupling fuzzy self-tuning particle swarm optimization to Boltzmann inversion, Swarm-CG performs accurate bottom-up parametrization of bonded terms in CG models composed of up to 200 pseudo atoms within 4–24 h on standard desktop machines, using default settings. The software benefits from a user-friendly interface and two different usage modes (default and advanced). We particularly expect Swarm-CG to support and facilitate the development of new CG models for the study of complex molecular systems interesting for bio- and nanotechnology. Excellent performances are demonstrated using a benchmark of 9 molecules of diverse nature, structural complexity, and size. Swarm-CG is available with all its dependencies via the Python Package Index (PIP package: swarm-cg ). Demonstration data are available at: .

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Magic v.3: An integrated software package for systematic structure-based coarse-graining

Cited by 25 publications

References 56 publications

A multiscale analysis of DNA phase separation: from atomistic to mesoscale level

A multiscale analysis of DNA phase separation: from atomistic to mesoscale level

Bottom-Up Coarse-Grained Modeling of DNA

Swarm-CG: Automatic Parametrization of Bonded Terms in MARTINI-Based Coarse-Grained Models of Simple to Complex MoleculesviaFuzzy Self-Tuning Particle Swarm Optimization

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