Spatiotemporal Landscape for the Sophisticated Transformation of Protein Assemblies Defined by Multiple Supramolecular Interactions

Protein-Based 2D Nanoarchitectures Constructed by Heterochiral π-Stacking Dimerization of Helical Foldamers

In this study, we focus on the designability and controllability of the interaction interface between secondary structures, and discover an important interface interaction between helical secondary structures by non-covalent synthesis along the helical axis. The formation of discrete heterochiral dimers consisting of left-handed helix and right-handed helix not only helps to discover nonclassical supramolecular chirality phenomena, but also enables controllable protein assembly. Highly ordered nanostructures were thus constructed using π-stacking dimerization of helical foldamers to control tetrameric avidin proteins. The designable and modifiable primitives of artificial folded molecules enable the modification of secondary structure interfaces through non-covalent interactions, leading to the generation of unique structures and functions. These findings are of fundamental importance to the understanding of the precise assembly process of helical foldamers and can provide insights to facilitate the rational design of abiotic protein-like tertiary structures and further functionalization.

Liquid Phase Exfoliation of Protein Parent Crystals into Nanosheets and Fibrils Based on Orthogonal Supramolecular Interactions

Proteins are attractive building blocks for fabricating diverse and precise nanomaterials. However, the facile fabrication of multidimensional artificial assemblies is highly challenging. Here, inspired by the large-scale production technique of inorganic nanomaterials, we demonstrate the application of liquid phase exfoliation (LPE) on native protein ConA by the design of synthetic ligands. These ligands provide distinct in-plane and out-of-plane supramolecular interactions, allowing the generation of multidimensional architectures based on the same protein by dissociating a single interaction in solution, including 3D porous protein crystals, 2D sizable nanosheets, and 1D fibrils. Importantly, the exfoliated 2D sheets were dozens of times larger than the self-assembled nanosheets, resulting in a dramatic enhancement of the intrinsic bioactivity of the building blocks by receptor clustering and less endocytosis. These findings enable the successful application of LPE on biomacromolecules and open up an alternative avenue to generate advanced multidimensional nanomaterials, without the need for complex protein design and careful adjustment of self-assembly conditions.

High-throughput analysis of hazards in novel food based on the density functional theory and multimodal deep learning

The emergence of cultured meat presents the potential for personalized food additive manufacturing, offering a solution to address future food resource scarcity. Processing raw materials and products in synthetic food products poses challenges in identifying hazards, impacting the entire industrial chain during the industry's further evolution. It is crucial to examine the correlation of biological information at different levels and to reveal the temporal dynamics jointly. Proposed active prevention method includes four aspects: (i) Investigating the molecular-level mechanism underlying the binding and dissociation of hazards with proteins represents a novel approach to mitigate matrix effect. (ii) Identifying distinct fragments is a pivotal advancement toward developing a novel screening strategy for hazards throughout the food chain. (iii) Designing an artificial intelligence model-based approach to acquire multi-dimensional histology data also holds significant potential for various applications. (iv) Integrating multimodal data is a practical approach to enhance evaluation and feedback control accuracy.