Understanding functional group and assembly dynamics in temperature responsive systems leads to design principles for enzyme responsive assemblies

Structural Determinants of Stimuli-Responsiveness in Amphiphilic Macromolecular Nano-assemblies

Stimuli-responsive nano-assemblies from amphiphilic macromolecules could undergo controlled structural transformations and generate diverse macroscopic phenomenon under stimuli. Due to the controllable responsiveness, they have been applied for broad material and biomedical applications, such as biologics delivery, sensing, imaging, and catalysis. Understanding the mechanisms of the assembly-disassembly processes and structural determinants behind the responsive properties is fundamentally important for designing the next generation of nano-assemblies with programmable responsiveness. In this review, we focus on structural determinants of assemblies from amphiphilic macromolecules and their macromolecular level alterations under stimuli, such as the disruption of hydrophilic-lipophilic balance (HLB), depolymerization, decrosslinking, and changes of molecular packing in assemblies, which eventually lead to a series of macroscopic phenomenon for practical purposes. Applications of stimuli-responsive nano-assemblies in delivery, sensing and imaging were also summarized based on their structural features. We expect this review could provide readers an overview of the structural considerations in the design and applications of nanoassemblies and incentivize more explorations in stimuli-responsive soft matters.

Unsupervised Data-Driven Reconstruction of Molecular Motifs in Simple to Complex Dynamic Micelles

The reshuffling mobility of molecular building blocks in self-assembled micelles is a key determinant of many their interesting properties, from emerging morphologies and surface compartmentalization, to dynamic reconfigurability and stimuli-responsiveness. However, the microscopic details of such complex structural dynamics are typically nontrivial to elucidate, especially in multicomponent assemblies. Here we show a machine-learning approach that allows us to reconstruct the structural and dynamic complexity of mono- and bicomponent surfactant micelles from high-dimensional data extracted from equilibrium molecular dynamics simulations. Unsupervised clustering of smooth overlap of atomic position (SOAP) data enables us to identify, in a set of multicomponent surfactant micelles, the dominant local molecular environments that emerge within them and to retrace their dynamics, in terms of exchange probabilities and transition pathways of the constituent building blocks. Tested on a variety of micelles differing in size and in the chemical nature of the constitutive self-assembling units, this approach effectively recognizes the molecular motifs populating them in an exquisitely agnostic and unsupervised way, and allows correlating them to their composition in terms of constitutive surfactant species.

Mucus adhesion vs. mucus penetration? Screening nanomaterials for nasal inhalation by MD simulation

Nanocarrier-aided drug delivery techniques have improved the absorption and permeability of drugs in nose-to-brain delivery. However, the molecular properties of nanocarriers during the delivery process are of great interest; in particular, the characteristics when penetrating barriers in vivo are crucial for the screening and optimization of materials for nasal inhalation. In this study, we have focused on two types of delivery systems: mucoadhesive nanoparticles (MAPs) and mucopenetrating nanoparticles (MPPs); both have been widely used for mucosal delivery, although a method for selecting the more effective type of drug carriers for mucosal delivery has not been established. Molecular dynamics (MD) simulations were used to reveal the all-atom dynamic characteristics of the interaction between different delivery systems and the nasal mucus protein MUC5AC. Among the systems tested, hydroxypropyltrimethyl ammonium chloride chitosan (HTCC) had the strongest interaction with mucin, suggesting it had better mucoadhesive performance, and that it interacted with MUC5AC more strongly than unmodified chitosan. In contrast, the mucus-penetrating material polyethylene glycol-poly lactic acid-co-glycolic acid (PEG-PLGA), had almost no interaction with MUC5AC. The results of the MD simulations were verified by in vitro experiments on nanoparticles (NPs) and mucin binding. The drug delivery performance of the four types of NPs, analyzed by in vitro and ex vivo mucosal penetration, were all generally consistent with the properties of the material predicted from the MD simulation. These clues to the molecular mechanism of MAPs and MPPs may provide useful insight into the screening and optimization of nanomaterials suitable for nasal inhalation.

Molecular bases for temperature sensitivity in supramolecular assemblies and their applications as thermoresponsive soft materials

Thermoresponsive supramolecular assemblies have been extensively explored in diverse formats, from injectable hydrogels to nanoscale carriers, for a variety of applications including drug delivery, tissue engineering and thermo-controlled catalysis. Understanding the molecular bases behind thermal sensitivity of materials is fundamentally important for the rational design of assemblies with optimal combination of properties and predictable tunability for specific applications. In this review, we summarize the recent advances in this area with a specific focus on the parameters and factors that influence thermoresponsive properties of soft materials. We summarize and analyze the effects of structures and architectures of molecules, hydrophilic and lipophilic balance, concentration, components and external additives upon the thermoresponsiveness of the corresponding molecular assemblies.

Multichannel dual protein sensing using amphiphilic supramolecular assemblies

Protein sensing strategies have implications in detection of many human pathologies. Here, a supramolecular strategy for sensing two different proteins using a multichannel readout approach is outlined. Protein-ligand binding or enzymatic cleavage can both be programmed to induce supramolecular disassembly, which leads to fluorescence enhancement via aggregation-induced emission (AIE), protein-induced fluorescence enhancement (PIFE), or disassembly-induced fluorescence enhancement (DIFE). The accompanying signal change from two different fluorophores and their patterns are then used for specific protein sensing.

Excimer-monomer fluorescence changes by supramolecular disassembly for protein sensing and quantification

A protein binding-induced supramolecular dissociation strategy is developed with the ratio of monomer and excimer fluorescence as the tool for protein sensing and quantification. Due to the "lock-and-key" strategy based on specific ligand-protein binding, the probe exhibits excellent selectivity and quantification accuracy to the protein of interest. The ratiometric approach is immune to interference from extrinsic quenchers, while preserving the opportunity to be protein specific.