Literature DB >> 20550147

Molecular dynamics simulations of polyglutamine aggregation using solvent-free multiscale coarse-grained models.

Yanting Wang1, Gregory A Voth.   

Abstract

The multiscale coarse-graining (MS-CG) method is used to construct solvent-free CG models for polyglutamine peptides having various repeat lengths. Because the resulting CG models have fewer degrees of freedom than a corresponding all-atom simulations, they make it possible to study the self-assembly of polyglutamines at high concentrations for the first time by allowing for better equilibration and statistical sampling that is well beyond the range achievable by all-atom models. Molecular dynamics (MD) simulations performed with these models show that polyglutamine monomers with repeat lengths < or = 28 fluctuate between their folded and unfolded states. Monomers with 32 or more residues are stable and form alpha-helix solid structures. The degree of monomer compactness increases with chain length in both cases. CG MD simulations of equilibrium polyglutamine aggregates show that even at high concentrations, the system statistically fluctuates between heterogeneous and homogeneous configurations, rather than simply aggregates. The degree of aggregation and fluctuation increases with concentration and chain length. All of these phenomena are consistent with the experimental observations and may be explained by a mechanism that the collective nonbonded interactions between polyglutamine molecules in water solution are only weakly attractive. Finally, this work demonstrates that computer simulation of polypeptides self-assembly and aggregation, which is presently beyond the reach of all-atom MD simulations, is attainable using solvent-free MS-CG models.

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Year:  2010        PMID: 20550147     DOI: 10.1021/jp1007768

Source DB:  PubMed          Journal:  J Phys Chem B        ISSN: 1520-5207            Impact factor:   2.991


  15 in total

1.  Using a reduced dimensionality model to compute the thermodynamic properties of finite polypeptide aggregates.

Authors:  Gustavo E López; Anthony Cruz; Melyorise Sepulveda-Chervony; Juan López-Garriga; Madeline Torres-Lugo
Journal:  J Biol Phys       Date:  2012-02-02       Impact factor: 1.365

2.  A coarse-grained model for polyglutamine aggregation modulated by amphipathic flanking sequences.

Authors:  Kiersten M Ruff; Siddique J Khan; Rohit V Pappu
Journal:  Biophys J       Date:  2014-09-02       Impact factor: 4.033

3.  CAMELOT: A machine learning approach for coarse-grained simulations of aggregation of block-copolymeric protein sequences.

Authors:  Kiersten M Ruff; Tyler S Harmon; Rohit V Pappu
Journal:  J Chem Phys       Date:  2015-12-28       Impact factor: 3.488

4.  Effects of the enlargement of polyglutamine segments on the structure and folding of ataxin-2 and ataxin-3 proteins.

Authors:  Jingran Wen; Daniel R Scoles; Julio C Facelli
Journal:  J Biomol Struct Dyn       Date:  2016-05-20

5.  Emerging β-Sheet Rich Conformations in Supercompact Huntingtin Exon-1 Mutant Structures.

Authors:  Hongsuk Kang; Francisco X Vázquez; Leili Zhang; Payel Das; Leticia Toledo-Sherman; Binquan Luan; Michael Levitt; Ruhong Zhou
Journal:  J Am Chem Soc       Date:  2017-06-23       Impact factor: 15.419

6.  Parametrization of Backbone Flexibility in a Coarse-Grained Force Field for Proteins (COFFDROP) Derived from All-Atom Explicit-Solvent Molecular Dynamics Simulations of All Possible Two-Residue Peptides.

Authors:  Tamara Frembgen-Kesner; Casey T Andrews; Shuxiang Li; Nguyet Anh Ngo; Scott A Shubert; Aakash Jain; Oluwatoni J Olayiwola; Mitch R Weishaar; Adrian H Elcock
Journal:  J Chem Theory Comput       Date:  2015-04-30       Impact factor: 6.006

7.  Study of the aggregation mechanism of polyglutamine peptides using replica exchange molecular dynamics simulations.

Authors:  Miki Nakano; Kuniyoshi Ebina; Shigenori Tanaka
Journal:  J Mol Model       Date:  2013-01-05       Impact factor: 1.810

8.  An Analysis of Biomolecular Force Fields for Simulations of Polyglutamine in Solution.

Authors:  Aaron M Fluitt; Juan J de Pablo
Journal:  Biophys J       Date:  2015-09-01       Impact factor: 4.033

9.  Are long-range structural correlations behind the aggregration phenomena of polyglutamine diseases?

Authors:  Mahmoud Moradi; Volodymyr Babin; Christopher Roland; Celeste Sagui
Journal:  PLoS Comput Biol       Date:  2012-04-26       Impact factor: 4.475

10.  Structure prediction of polyglutamine disease proteins: comparison of methods.

Authors:  Jingran Wen; Daniel R Scoles; Julio C Facelli
Journal:  BMC Bioinformatics       Date:  2014-05-28       Impact factor: 3.169

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