Megamolecule Self-Assembly Networks: A Combined Computational and Experimental Design Strategy

This work describes the use of computational strategies to design megamolecule building blocks for the self-assembly of lattice networks. The megamolecules are prepared by attaching four Cutinase-SnapTag fusion proteins (CS fusions) to a four-armed linker, followed by functionalizing each fusion with a terpyridine linker. This functionality is designed to participate in a metal-mediated self-assembly process to give networks. This article describes a simulation-guided strategy for the design of megamolecules to optimize the peptide linker in the fusion protein to give conformations that are best suited for self-assembly and therefore streamlines the typically time-consuming and labor-intensive experimental process. We designed 11 candidate megamolecules and identified the most promising linker, (EAAAK)<sub>2</sub>, along with the optimal experimental conditions through a combination of all-atom molecular dynamics, enhanced sampling, and larger-scale coarse-grained molecular dynamics simulations. Our simulation findings were validated and found to be consistent with the experimental results. Significantly, this study offers valuable insight into the self-assembly of megamolecule networks and provides a novel and general strategy for large biomolecular material designs by using systematic bottom-up coarse-grained simulations.

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Publication Details

Journal
Journal of the American Chemical Society
Published
2024-10-25
DOI
https://doi.org/10.1021/jacs.4c11892
Citations
4
Primary Topic
Supramolecular Self-Assembly in Materials
Type
article
Field-Weighted Citation Impact
0.69

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article

Megamolecule Self-Assembly Networks: A Combined Computational and Experimental Design Strategy

Jiangbo Wu, Justin A. Modica, Milan Mrksich, Gregory A. Voth et al.
4 citations
Journal of the American Chemical Society
Supramolecular Self-Assembly in Materials
0.69
article

Megamolecule Self-Assembly Networks: A Combined Computational and Experimental Design Strategy

Jiangbo Wu, Justin A. Modica, Milan Mrksich, Gregory A. Voth, Sijia Chen, Zhaoyi Gu
article en
4 citations

Abstract

This work describes the use of computational strategies to design megamolecule building blocks for the self-assembly of lattice networks. The megamolecules are prepared by attaching four Cutinase-SnapTag fusion proteins (CS fusions) to a four-armed linker, followed by functionalizing each fusion with a terpyridine linker. This functionality is designed to participate in a metal-mediated self-assembly process to give networks. This article describes a simulation-guided strategy for the design of megamolecules to optimize the peptide linker in the fusion protein to give conformations that are best suited for self-assembly and therefore streamlines the typically time-consuming and labor-intensive experimental process. We designed 11 candidate megamolecules and identified the most promising linker, (EAAAK)<sub>2</sub>, along with the optimal experimental conditions through a combination of all-atom molecular dynamics, enhanced sampling, and larger-scale coarse-grained molecular dynamics simulations. Our simulation findings were validated and found to be consistent with the experimental results. Significantly, this study offers valuable insight into the self-assembly of megamolecule networks and provides a novel and general strategy for large biomolecular material designs by using systematic bottom-up coarse-grained simulations.

Journal of the American Chemical SocietyVol. 146(44)
Northwestern University (US), Chicago Institute for Psychoanalysis (US), University of Chicago (US)
Army Research Office
Openalex Percentile: Top 34%
Supramolecular Self-Assembly in Materials
0.69
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Megamolecule Self-Assembly Networks: A Combined Computational and Experimental Design Strategy — Jiangbo Wu, Justin A. Modica, et al. · Journal of the American Chemical Society (2024) | TGRS Research Map | TGRS