Literature DB >> 20158022

Systematic coarse-graining of molecular models by the Newton inversion method.

Alexander Lyubartsev1, Alexander Mirzoev, LiJun Chen, Aatto Laaksonen.   

Abstract

Systematic construction of coarse-grained molecular models from detailed atomistic simulations, and even from ab initio simulations is discussed. Atomistic simulations are first performed to extract structural information about the system, which is then used to determine effective potentials for a coarse-grained model of the same system. The statistical-mechanical equations expressing the canonical properties in terms of potential parameters can be inverted and solved numerically according to the iterative Newton scheme. In our previous applications, known as the Inverse Monte Carlo, radial distribution functions were inverted to reconstruct pair potential, while in a more general approach the targets can be other canonical averages. We have considered several examples of coarse-graining; for the united atom water model we suggest an easy way to overcome the known problem of high pressure. Further, we have developed coarse-grained models for L- and D-prolines, dissolved here in an organic solvent (dimethylsulfoxide), keeping their enantiomeric properties from the corresponding all-atom proline model. Finally, we have revisited the previously developed coarse-grained lipid model based on an updated all-atomic force field. We use this model in large-scale meso-scale simulations demonstrating spontaneous formation of different structures, such as vesicles, micelles, and multi-lamellar structures, depending on thermodynamical conditions.

Entities:  

Year:  2010        PMID: 20158022     DOI: 10.1039/b901511f

Source DB:  PubMed          Journal:  Faraday Discuss        ISSN: 1359-6640            Impact factor:   4.008


  16 in total

1.  Understanding Missing Entropy in Coarse-Grained Systems: Addressing Issues of Representability and Transferability.

Authors:  Jaehyeok Jin; Alexander J Pak; Gregory A Voth
Journal:  J Phys Chem Lett       Date:  2019-07-30       Impact factor: 6.475

Review 2.  Bottom-up Coarse-Graining: Principles and Perspectives.

Authors:  Jaehyeok Jin; Alexander J Pak; Aleksander E P Durumeric; Timothy D Loose; Gregory A Voth
Journal:  J Chem Theory Comput       Date:  2022-09-07       Impact factor: 6.578

3.  Coarse-Grained Molecular Models of Water: A Review.

Authors:  Kevin R Hadley; Clare McCabe
Journal:  Mol Simul       Date:  2012-07-04       Impact factor: 2.178

4.  Model reduction of rigid-body molecular dynamics via generalized multipole potentials.

Authors:  Paul N Patrone; Andrew Dienstfrey; G B McFadden
Journal:  Phys Rev E       Date:  2019-12       Impact factor: 2.529

Review 5.  Bottom-Up Coarse-Grained Modeling of DNA.

Authors:  Tiedong Sun; Vishal Minhas; Nikolay Korolev; Alexander Mirzoev; Alexander P Lyubartsev; Lars Nordenskiöld
Journal:  Front Mol Biosci       Date:  2021-03-17

Review 6.  Computational Modeling of Realistic Cell Membranes.

Authors:  Siewert J Marrink; Valentina Corradi; Paulo C T Souza; Helgi I Ingólfsson; D Peter Tieleman; Mark S P Sansom
Journal:  Chem Rev       Date:  2019-01-09       Impact factor: 72.087

7.  Relative Entropy and Optimization-Driven Coarse-Graining Methods in VOTCA.

Authors:  S Y Mashayak; Mara N Jochum; Konstantin Koschke; N R Aluru; Victor Rühle; Christoph Junghans
Journal:  PLoS One       Date:  2015-07-20       Impact factor: 3.240

8.  COFFDROP: A Coarse-Grained Nonbonded Force Field for Proteins Derived from All-Atom Explicit-Solvent Molecular Dynamics Simulations of Amino Acids.

Authors:  Casey T Andrews; Adrian H Elcock
Journal:  J Chem Theory Comput       Date:  2014-10-07       Impact factor: 6.006

9.  How Water's Properties Are Encoded in Its Molecular Structure and Energies.

Authors:  Emiliano Brini; Christopher J Fennell; Marivi Fernandez-Serra; Barbara Hribar-Lee; Miha Lukšič; Ken A Dill
Journal:  Chem Rev       Date:  2017-09-26       Impact factor: 60.622

10.  Thermodynamics of Hydrophobic Amino Acids in Solution: A Combined Experimental-Computational Study.

Authors:  Lingshuang Song; Lin Yang; Jie Meng; Sichun Yang
Journal:  J Phys Chem Lett       Date:  2017-01-03       Impact factor: 6.475

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