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Sun T, Minhas V, Korolev N, Mirzoev A, Lyubartsev AP, Nordenskiöld L. Bottom-Up Coarse-Grained Modeling of DNA. Front Mol Biosci 2021; 8:645527. [PMID: 33816559 PMCID: PMC8010198 DOI: 10.3389/fmolb.2021.645527] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 02/22/2021] [Indexed: 12/22/2022] Open
Abstract
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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Affiliation(s)
- Tiedong Sun
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Vishal Minhas
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Nikolay Korolev
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Alexander Mirzoev
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Alexander P. Lyubartsev
- Department of Materials and Environmental Chemistry, Stockholm University, Stockholm, Sweden
| | - Lars Nordenskiöld
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
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Lyubartsev AP, Naômé A, Vercauteren DP, Laaksonen A. Systematic hierarchical coarse-graining with the inverse Monte Carlo method. J Chem Phys 2016; 143:243120. [PMID: 26723605 DOI: 10.1063/1.4934095] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
We outline our coarse-graining strategy for linking micro- and mesoscales of soft matter and biological systems. The method is based on effective pairwise interaction potentials obtained in detailed ab initio or classical atomistic Molecular Dynamics (MD) simulations, which can be used in simulations at less accurate level after scaling up the size. The effective potentials are obtained by applying the inverse Monte Carlo (IMC) method [A. P. Lyubartsev and A. Laaksonen, Phys. Rev. E 52(4), 3730-3737 (1995)] on a chosen subset of degrees of freedom described in terms of radial distribution functions. An in-house software package MagiC is developed to obtain the effective potentials for arbitrary molecular systems. In this work we compute effective potentials to model DNA-protein interactions (bacterial LiaR regulator bound to a 26 base pairs DNA fragment) at physiological salt concentration at a coarse-grained (CG) level. Normally the IMC CG pair-potentials are used directly as look-up tables but here we have fitted them to five Gaussians and a repulsive wall. Results show stable association between DNA and the model protein as well as similar position fluctuation profile.
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Affiliation(s)
- Alexander P Lyubartsev
- Division of Physical Chemistry, Arrhenius Laboratory, Stockholm University, S 106 91 Stockholm, Sweden
| | - Aymeric Naômé
- Division of Physical Chemistry, Arrhenius Laboratory, Stockholm University, S 106 91 Stockholm, Sweden
| | | | - Aatto Laaksonen
- Division of Physical Chemistry, Arrhenius Laboratory, Stockholm University, S 106 91 Stockholm, Sweden
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Lange OF, Grubmüller H. Collective Langevin dynamics of conformational motions in proteins. J Chem Phys 2007; 124:214903. [PMID: 16774438 DOI: 10.1063/1.2199530] [Citation(s) in RCA: 86] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Functionally relevant slow conformational motions of proteins are, at present, in most cases inaccessible to molecular dynamics (MD) simulations. The main reason is that the major part of the computational effort is spend for the accurate description of a huge number of high frequency motions of the protein and the surrounding solvent. The accumulated influence of these fluctuations is crucial for a correct treatment of the conformational dynamics; however, their details can be considered irrelevant for most purposes. To accurately describe long time protein dynamics we here propose a reduced dimension approach, collective Langevin dynamics (CLD), which evolves the dynamics of the system within a small subspace of relevant collective degrees of freedom. The dynamics within the low-dimensional conformational subspace is evolved via a generalized Langevin equation which accounts for memory effects via memory kernels also extracted from short explicit MD simulations. To determine the memory kernel with differing levels of regularization, we propose and evaluate two methods. As a first test, CLD is applied to describe the conformational motion of the peptide neurotensin. A drastic dimension reduction is achieved by considering one single curved conformational coordinate. CLD yielded accurate thermodynamical and dynamical behaviors. In particular, the rate of transitions between two conformational states agreed well with a rate obtained from a 150 ns reference molecular dynamics simulation, despite the fact that the time scale of the transition (approximately 50 ns) was much longer than the 1 ns molecular dynamics simulation from which the memory kernel was extracted.
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Affiliation(s)
- Oliver F Lange
- Department of Theoretical and Computational Biophysics, Max-Planck-Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany
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Affiliation(s)
- Eduardo Zaborowski
- a Department of Chemical Physics , Weizmann Institute of Science , 76100 , Rehovot , Israel
| | - Shimon Vega
- a Department of Chemical Physics , Weizmann Institute of Science , 76100 , Rehovot , Israel
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Akkermans RLC, Briels WJ. Coarse-grained dynamics of one chain in a polymer melt. J Chem Phys 2000. [DOI: 10.1063/1.1308513] [Citation(s) in RCA: 97] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Brus J, Dybal J, Schmidt P, Kratochvíl J, Baldrian J. Order and Mobility in Polycarbonate−Poly(ethylene oxide) Blends Studied by Solid-State NMR and Other Techniques. Macromolecules 2000. [DOI: 10.1021/ma000533s] [Citation(s) in RCA: 48] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- J. Brus
- Institute of Macromolecular Chemistry, Academy of Sciences of the Czech Republic, 162 06 Prague 6, Czech Republic
| | - J. Dybal
- Institute of Macromolecular Chemistry, Academy of Sciences of the Czech Republic, 162 06 Prague 6, Czech Republic
| | - P. Schmidt
- Institute of Macromolecular Chemistry, Academy of Sciences of the Czech Republic, 162 06 Prague 6, Czech Republic
| | - J. Kratochvíl
- Institute of Macromolecular Chemistry, Academy of Sciences of the Czech Republic, 162 06 Prague 6, Czech Republic
| | - J. Baldrian
- Institute of Macromolecular Chemistry, Academy of Sciences of the Czech Republic, 162 06 Prague 6, Czech Republic
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Huber GA. Future directions for combining molecular and continuum models in protein simulations. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 1998; 69:483-96. [PMID: 9785952 DOI: 10.1016/s0079-6107(98)00021-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
In order to perform useful computer simulations on protein molecules, models that combine atomistic and continuum approaches will be necessary. The use of continuum models will reduce the number of system variables and allow studies of longer time scales. On the other hand, one will still need to retain atomic detail in certain parts of the protein molecule, such as an enzyme active site. Most of the important advances to date have been continuum models of the surrounding solvent, but simplified descriptions of the protein itself also are being developed. Finally, in order to study these several different levels of complexity simultaneously in a single simulation, it will be necessary to use modern software engineering techniques.
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Affiliation(s)
- G A Huber
- Department of Chemistry and Biochemistry, University of California-San Diego, La Jolla 92093-0365, USA.
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ZABOROWSKI BEDUARDO, VEGA SHIMON. Solid state NMR and molecular modelling of the p-xylene adduct of Dianin's compound. Mol Phys 1997. [DOI: 10.1080/002689797170824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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Whitney DR, Yaris R. Local Mechanism of Phenyl Ring π-Flips in Glassy Polycarbonate. Macromolecules 1997. [DOI: 10.1021/ma9611432] [Citation(s) in RCA: 35] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Duane R. Whitney
- Department of Chemistry, Washington University, St. Louis, Missouri 63130
| | - Robert Yaris
- Department of Chemistry, Washington University, St. Louis, Missouri 63130
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Lyubartsev AP, Laaksonen A. Calculation of effective interaction potentials from radial distribution functions: A reverse Monte Carlo approach. PHYSICAL REVIEW. E, STATISTICAL PHYSICS, PLASMAS, FLUIDS, AND RELATED INTERDISCIPLINARY TOPICS 1995; 52:3730-3737. [PMID: 9963851 DOI: 10.1103/physreve.52.3730] [Citation(s) in RCA: 553] [Impact Index Per Article: 19.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Gao J, Weiner JH. Screened intermolecular forces and covalent bond forces in polymer melts. J Chem Phys 1993. [DOI: 10.1063/1.464530] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Sen S, Cai ZX, Mahanti SD. Dynamical correlations and the direct summation method of evaluating infinite continued fractions. PHYSICAL REVIEW. E, STATISTICAL PHYSICS, PLASMAS, FLUIDS, AND RELATED INTERDISCIPLINARY TOPICS 1993; 47:273-281. [PMID: 9960001 DOI: 10.1103/physreve.47.273] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
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Romiszowski P, Yaris R. A dynamic simulation method suppressing uninteresting degrees of freedom. II. Mechanism of π flips in a lattice of benzene rings. J Chem Phys 1991. [DOI: 10.1063/1.461512] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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