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

• Published in: Journal of the American Chemical Society Vol. 146; no. 44; pp. 30553 - 30564
• Main Authors: Wu, Jiangbo, Gu, Zhaoyi, Modica, Justin A., Chen, Sijia, Mrksich, Milan, Voth, Gregory A.
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 06-11-2024
• ISSN: 0002-7863; 1520-5126; 1520-5126
• 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.