Literature DB >> 28117587

Coarse-Grained Molecular Simulation of the Hierarchical Self-Assembly of π-Conjugated Optoelectronic Peptides.

Rachael A Mansbach1, Andrew L Ferguson2,3.   

Abstract

Self-assembled aggregates of peptides containing aromatic groups possess optoelectronic properties that make them attractive targets for the fabrication of biocompatible electronics. Molecular-level understanding of the influence of microscopic peptide chemistry on the properties of the aggregates is vital for rational peptide design. In this study, we construct a coarse-grained model of Asp-Phe-Ala-Gly-OPV3-Gly-Ala-Phe-Asp (DFAG-OPV3-GAFD) peptides containing OPV3 (distyrylbenzene) π-conjugated cores explicitly parameterized against all-atom calculations and perform molecular dynamics simulations of the self-assembly of hundreds of molecules over hundreds of nanoseconds. We observe a hierarchical assembly mechanism, wherein approximately two to eight peptides assemble into stacks with aligned aromatic cores that subsequently form elliptical aggregates and ultimately a branched network with a fractal dimensionality of ∼1.5. The assembly dynamics are well described by a Smoluchowski coagulation process, for which we extract rate constants from the molecular simulations to both furnish insight into the microscopic assembly kinetics and extrapolate our aggregation predictions to time and length scales beyond the reach of molecular simulation. This study presents new molecular-level understanding of the morphology and dynamics of the spontaneous self-assembly of DFAG-OPV3-GAFD peptides and establishes a systematic protocol to develop coarse-grained models of optoelectronic peptides for the exploration and design of π-conjugated peptides with tunable optoelectronic properties.

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Year:  2017        PMID: 28117587     DOI: 10.1021/acs.jpcb.6b10165

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


  2 in total

1.  Integration of Machine Learning and Coarse-Grained Molecular Simulations for Polymer Materials: Physical Understandings and Molecular Design.

Authors:  Danh Nguyen; Lei Tao; Ying Li
Journal:  Front Chem       Date:  2022-01-24       Impact factor: 5.221

2.  Side Chain Geometry Determines the Fibrillation Propensity of a Minimal Two-Beads-per-Residue Peptide Model.

Authors:  Beata Szała-Mendyk; Andrzej Molski
Journal:  J Phys Chem B       Date:  2022-08-02       Impact factor: 3.466

  2 in total

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