Title : Megamolecule Self-Assembly Networks: A Combined Computational and Experimental Design Strategy - Wu_2024_J.Am.Chem.Soc__ |
Author(s) : Wu J , Gu Z , Modica JA , Chen S , Mrksich M , Voth GA |
Ref : Journal of the American Chemical Society , : , 2024 |
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)(2), 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. |
PubMedSearch : Wu_2024_J.Am.Chem.Soc__ |
PubMedID: 39451142 |
Wu J, Gu Z, Modica JA, Chen S, Mrksich M, Voth GA (2024)
Megamolecule Self-Assembly Networks: A Combined Computational and Experimental Design Strategy
Journal of the American Chemical Society
:
Wu J, Gu Z, Modica JA, Chen S, Mrksich M, Voth GA (2024)
Journal of the American Chemical Society
: