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

JB Wu and ZY Gu and JA Modica and SJ Chen and M Mrksich and GA Voth, JOURNAL OF THE AMERICAN CHEMICAL SOCIETY, 146, 30553-30564 (2024).

DOI: 10.1021/jacs.4c11892

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.

Return to Publications page